Mesh_Fundamentals_14dec01

Fundamental Characteristics and Benefits Of Wireless Routing (“Mesh”) Networks

Dave Beyer Head of Nokia Wireless Routing Mountain View, California [email protected]

Wireless Communications Association International, Technical Symposium San Jose, California January 14-16, 2002

Abstract

Wireless will bring the next significant wave of broadband network services, particularly for areas difficult or costly to reach with wires. However, before a wireless networking product can be profitably and widely deployed, it must be proven capable of meeting three key business challenges:

1. Low total cost of purchase, installation, and maintenance for complete and uninterrupted wireless coverage despite difficult and changing RF environments;

2. Easy and spectrally efficient network scaling as the customer footprint and density grows, despite the relatively demanding signal-quality needs of broadband RF links; and

3. Assured and reliable service for broadband subscriber data flows with an end-to-end communication quality that matches or exceeds that available over wires.

Commercial products are now emerging based on wireless routing, which solves these challenges using an entirely different approach to the traditional cellular, point-to-multipoint network architectures. With wireless routing, every subscriber device serves as both the broadband access device for that subscriber as well as part of the network infrastructure, automatically forwarding traffic for other subscribers as needed to ensure full and continuous network coverage and facilitate network growth while providing the service assurances needed for high-speed, multimedia traffic.

This paper will review the fundamental characteristics and benefits of wireless routing (“mesh”) network architectures, how they compare with traditional point-to-multipoint networks, and how they solve the above challenges to enable the coming wave of broadband wireless networks.

mailto:[email protected]

Fundamental Characteristics and Benefits of Wireless Routing (Mesh) Networks D.Beyer

Contents 1. Wireless Routing Background ......................................................................................................4 2. Full, Robust Coverage .................................................................................................................6

2.1 Basic RF Propagation Models................................................................................................6 2.2 A Simple Model Based on Link Probability.............................................................................7 2.3 Log-Normal Path Loss Model...............................................................................................10 2.4 Robustness to Link Changes ...............................................................................................12 2.5 Effect of Radio or Other Link Improvements ........................................................................13 2.6 Providing Initial Coverage ....................................................................................................15

3. Natural Scaling...........................................................................................................................16 3.1 Signal Versus Interference Propagation...............................................................................16 3.2 Network Capacity in Large, Dense Networks .......................................................................21 3.3 Planning AirHead Sites........................................................................................................24 3.4 Growing with Increasing Customer Density..........................................................................24 3.5 Using Unlicensed Spectrum.................................................................................................25

4. Multimedia, Broadband Service..................................................................................................26 4.1 Throughput over Multiple Wireless Hops .............................................................................26 4.2 Efficient, Fair and Reliable Channel Access.........................................................................29 4.3 Quality-of-Service Support for Multimedia Traffic .................................................................32

5. Conclusion .................................................................................................................................37 6. Acknowledgments......................................................................................................................37 A. Appendix A – Signal-to-Interference Capacity Scaling Derivation...............................................38

A.1 Local Neighborhood.............................................................................................................38 A.2 Receive Power of Desired Signal.........................................................................................38 A.3 Average Transmit Power and Associated Link Distance ......................................................39 A.4 Receive Interference Power.................................................................................................40 A.5 Receive Signal-to-Interference Level ...................................................................................41

Wireless Communications Association, Technical Symposium - 14 January 2001 (rev: 14Dec01) Page 2 of 42


Acronyms & Terms

802.11 An IEEE working group developing standards for wireless local area networks. 802.16 An IEEE working group developing standards for wireless broadband access networks. Ad Hoc Not used in this paper due to the confusion between the 802.11 definition referring to a

collection of fully connected nodes, and the definition in the MANET forum referring to multihop mesh networks.

AirHead The wireless router that attaches a neighborhood wireless routing network (i.e., AirHood) to the backhaul links that lead to the operator network or Internet.

AirHood The neighborhood of wireless routers currently associated with a particular AirHead (or set of AirHeads). Somewhat analogous to a PMP sector.

DiffServ Differentiated Services. A standard being developed in the IETF to provide application-specific service to IP packets.

DSCP DiffServ Code Point. The field in IP packet headers used to determine the service to be applied to a particular packet.

EIRP Effective Isotropic Radiated Power. Measures the level of power emitted from an RF antenna. FDD Frequency Division Duplexing. A method often used in PMP networks to avoid interference

between up- and down-stream traffic in neighboring cells. IEEE Institute of Electrical and Electronics Engineers. IETF Internet Engineering Task Force. ISM Industrial, Scientific, and Medical unlicensed frequency bands: 902 to 928 MHz, 2.4 to 2.485

GHz and 5.725 to 5.875. MAC Medium Access Control. The protocol layer in a wireless network that coordinates transmission

scheduling and related issues. MANET Mobile Ad-hoc Networks. An IETF working group developing routing protocols for mobile,

wireless, multihop networks. OFDM Orthogonal Frequency Division Multiplexing. A modulation method which efficiently encodes

and modulates data on multiple orthogonal carrier frequencies, and which has recently gained favor in standards groups such as 802.11a and 802.16.

PTP Point-To-Point wireless link. PMP or PTMP Point-To-Multipoint wireless network. PMP refers to wireless “star” networks where the

transmission scheduling and other network behavior of the slave (subscriber) devices are controlled by a master (base station, or access point) device.

RF Radio Frequency. TDD Time Division Duplexing. Another method often used in PMP networks to avoid interference

between up- and down-stream traffic in neighboring cells. TDMA Time Division Multiple Access. A method for synchronizing and scheduling a wireless channel

among multiple devices. TOS Type of Service. The original field in IP packet headers used to indicate service handling. The

more recent DSCP label was defined within the original TOS field. U-NII Unlicensed National Information Infrastructure bands: 5.15 to 5.25 GHz (indoor only), 5.25 to

5.35 GHz, and 5.725 to 5.825. WLAN Wireless Local Area Network. WR Wireless Routing (as in a WR network), or Wireless Router (as in a subscriber’s WR).



1. WIRELESS ROUTING BACKGROUND

Wireless routing was introduced and developed during over two decades of research work on “packet radio” technology supported by the U.S. Defense Advanced Research Projects Agency (DARPA) at a variety of commercial, defense, and university institutions (e.g., see [Kahn78], [Jubin87], [Beyer90], [Garcia-Luna97], and [Beyer99]). Figure 1 shows a prototype packet radio system developed in these programs during the early 1980’s.

Figure 1 – Wireless router (“packet radio”) system developed during early 1980’s in a DARPA-supported research program.

Recently, low-cost commercial products have been introduced that take advantage of the unique characteristics of wireless routing for broadband access applications using network architectures like the one

presented in

Figure 2. In this architecture, wired or wireless “backhaul” links are used to pipe high-speed bandwidth into neighborhood access points called “AirHeads.” From there, wireless routers are used to distribute this bandwidth amongst the subscribers in the neighborhood using self-configuring routing and channel access protocols which automatically create wireless neighborhood “mesh” networks (or “AirHoods”) in which each wireless router automatically forwards traffic for others as needed.

This wireless routing approach has unique advantages regarding the degree of network coverage that can be provided and robustly maintained at a given cost, the ease and efficiency of scaling the network in size and density, and the level of service that can be provided to network subscribers. This paper will review the fundamental characteristics and benefits of wireless routing networks, how they compare with traditional point-to-multipoint networks, and how they solve the cost, coverage, scaling, and service challenges to enable the coming wave of broadband wireless networks.



Figure 2 – Current commercial wireless routing networks for residential broadband Internet access.



2. FULL, ROBUST COVERAGE

A well-known key challenge for wireless broadband solutions, particularly for the residential market, is to ensure sufficient and uninterrupted coverage to the target market despite cluttered and changing RF environments, and at an overall cost that’s affordable for the residential consumer business case. Point-to-multipoint (PMP) network approaches to this challenge include developing and installing better, higher, or more powerful base stations and subscriber devices, or deploying more base stations in microcellular architectures, to attempt to overcome even the worst-case “non-line-of-sight” propagation conditions in the target market.

Although the wireless routing (WR) approach can also benefit from advances in radio technology, its unique advantage derives from the ability of every device in the network to forward traffic for other devices as needed. This characteristic results in two main effects related to coverage:

1. Wireless routing networks self-configure into a microcellular architecture, with a virtual microcell around each subscriber device, thereby dramatically decreasing the link distances needed for connectivity (and increasing scalability as discussed in Section 3); and

2. Wireless routing networks automatically select the best RF links between devices, and the best multihop routes between each subscriber device and the AirHead, according to the current local propagation conditions, thus enabling the network to take advantage of the best RF propagation paths available rather than requiring the operator to plan for and purchase equipment capable of overcoming the worst-case paths expected for the lifetime of the network.

The following subsections will analyze the dramatic positive effect that the wireless routing approach brings to solve the challenge of robust coverage.

2.1 Basic RF Propagation Models

In an otherwise quiet environment, two RF devices will be able to communicate if the RF propagation characteristics between the devices result in a sufficiently low effective signal loss, including multipath effects, to permit the receiver to successfully recover each transmission with high probability (e.g., with a 10-5 bit error rate). However, predicting local RF propagation in the 2-GHz and higher frequency bands typically used for wireless broadband is complicated by the fact that the path loss is driven, to a very large degree, by the absence or presence of obstructions in the links between devices. Approaches to modeling the path loss for wireless broadband networks include the following (e.g., see [Rappaport96] and [Rappaport98]):

1. Log-Distance Model, which uses a simple, deterministic path loss formula based on distance (d) of the form dB, where C(d� 0100 /log10)( ddndC � � 0) is the constant path loss at a small reference distance (d0), and where the path loss exponent (n) is typically set to an estimate of the near worst-case exponent between the base station and subscribers in that region (e.g., 3.5 to 5.5).

2. Log-Normal Model, which extends the Log-Distance Model by including a random variable �� resulting in the path loss formula C . The path loss exponent n is set to the average propagation conditions in the area (e.g., 2.5 to 4.5), and �

� ��

�� 0100 /log10)( ddnd

� is a zero-mean Gaussian random variable with standard deviation � (in



dB), which accounts for the random likelihood of having greater or fewer obstructions in the path than the average.

3. Partition-Based Model, which extends the Log-Normal model by separately accounting for the average path loss through known obstructions over each link, thereby significantly reducing the standard deviation of the estimate.

Of these, the Partition-Based model is generally the most accurate in environments where the precise locations and types of primary obstructions are known. However, this model will not be used in this paper due to the assumption that this type of information is not, in general, known for target wireless broadband markets. The simple Log-Distance model, using a worst-case exponent, can be useful for planning point-to-multipoint networks, which must be designed largely to overcome the worst-case propagation path in any case. However, as discussed in section 2.3 below, the Log-Normal model is more appropriate for planning wireless routing networks, due to their ability to take advantage of this random variance in the path loss by automatically selecting the best links available, while avoiding (routing around) the more difficult links.

2.2 A Simple Model Based on Link Probability

Before examining the coverage characteristics using the full Log-Normal propagation model in section 2.3, let’s first examine the characteristics using a simplified version of this model, where the term ��

completely dominates the formula. In other words, the path loss between two devices in an AirHood, or between a subscriber device and the base station in a cell, is completely driven by the presence or absence of obstructions in the path and is independent of the link distance within that cell or AirHood.1 Thus, the probability of reliable communication between any two devices within the cell or AirHood (including the base station or AirHead) simplifies to a certain “link probability” (z), dependent on the RF environment for that area.

With this model, consider the case of adding a new subscriber to an existing, connected network. For a point-to-multipoint network architecture, the probability that this new subscriber will also be connected is simply equal to the link probability (z) between itself and the base station. However, for the wireless routing network, the probability is equal to the chance of being able to connect to any one or more of the existing devices in the network (including the AirHead, existing subscribers, and any “seed” nodes). For a wireless routing network with m devices, this “coverage” probability (Pc(m)) for a new subscriber can be expressed as:

mc zmP )1(1)( ��

1 Although this model is simplistic, it also resembles reality for areas where the distances between devices varies by only some low multiple. For an example of the high variability in path loss, refer to the measurements reported in [Seidel91] performed on the 900-MHz band which resulted in an average path loss exponent of 2.7 and standard deviation of 11.8. For this type of environment, the longer of two arbitrary links would need to be 7½ times the distance of the shorter link in order for the first standard deviation areas of the two links’ path loss probability curves to be non-overlapping.



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Figure 3 -- Coverage probability as a function of the link probability between any two points.

Figure 3 shows the powerful effect of the exponential factor in this coverage formula. As more wireless router devices are added to the network, the probability that the next subscriber will have coverage increases exponentially.

Using this link probability model, one can also compute the probability of a given subscriber being at a certain number of hops from the AirHead. Specifically, the chance of being at some number (y) hops from the AirHead is equal to the chance of not being at less than y hops, times the chance of being able to connect to one or more of the devices that is at less than y hops. So, given a network of m devices, the probability of being at y hops from the AirHead (Ph(m,y)) is:

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Figure 4 presents example curves for Ph(m,y) for an AirHood with 25 wireless routers and for different values for the link probability, z. For environments which exhibit a link probability between arbitrary devices of 35% or greater, this model predicts that the great majority of subscriber devices in an AirHood with 25 wireless routers will be either one or two hops from the AirHead. However, even with the link probability set to 15%, the total coverage within 4 hops of the AirHead is 99.9%. Thus, even in very difficult environments, virtually 100% coverage is still ensured using this link probability model.



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Figure 4 -- Distribution of hops from AirHead as a function of link probability.

For a comparison with fielded systems, Figure 5 presents the distribution of approximately 100 2.4-GHz wireless routers in two networks, one in downtown Mountain View, California, and another in Santa Rosa, California, a moderately-wooded residential area. The curves present the percentage of nodes located at each hop count from the AirHead. Also included is the curve for the simple link probability model using a link probability (z) of 60% (since this was the probability of being 1 hop from the AirHead in these networks). Although both networks were deployed into cluttered RF environments (one with trees, the other with trees and buildings), the overall area of the networks was fairly contained (within ½ mile radius in each case), leading to the relatively high direct (1-hop) link probability. In these networks, all of the subscribers were able to connect to the network at no more than two hops from the AirHead.

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Figure 5 – Number of hops from AirHead for subscribers in two fielded mesh networks



2.3 Log-Normal Path Loss Model

As discussed above, a more realistic model for predicting the path loss (Lab) between a pair of devices (a, b) is the Log-Normal model.

� ��

�� 0100 /log10)( ddndCLab

The Log-Normal model is particularly appropriate for estimating the coverage of wireless routing networks, due to their ability to take advantage of the best links present, while routing around the more difficult links. Therefore, simulations were used to analyze the coverage behavior of WR and PMP networks using the Log-Normal model and the following scenario parameters:

Cell or AirHood radius 1 mile (1609.3 meters) Mean path loss exponent n 3 Path loss standard deviation � 10 dB Center frequency f 5.8 GHz Reference distance d0 1 meter Reference (free space) path loss C(d0) 20 log10(4� c/f) dB [~47.8 dB] Path loss allowance for “baseline” system2 A 130 dB

For each simulation trial, the AirHead (or base station) is placed at the center and then subscriber devices are located randomly within the 1-mile radius AirHood (or cell). A random path loss is computed between each pair of devices using the Log-Normal formula, and the resulting connectivity is determined for both the WR mesh and PMP case with links between each pair of devices (a,b) for which the path loss Lab � A. 1000 trials were run for each data point. Figure 6 presents an example trial with 25 subscriber devices where the dark lines indicate links to subscribers connected in a PMP network (32 %), and the light lines indicate links to the additional subscribers covered in a WR network (total of 100%).

-1 6 0 9

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-1 6 0 9 0 1 6 0 9

Figure 6 – Example AirHood using Log-Normal path loss model.

2 The path loss allowance accounts for the transmit power plus antenna gains minus receiver sensitivity along with any cabling and connector loss. Any margin for shadow fading is ignored. For example, 24-dBm transmit power, 8-dBi transmit antenna gain, 8-dBi receive antenna gain, and - 90-dBm receiver sensitivity gives a 130 dB path loss allowance.



Figure 7 presents the coverage probability resulting from three scenarios, all using the “baseline” radio systems: a PMP network, a mesh wireless routing network, and a mesh wireless routing network where 4 “seed” nodes were first placed ½ mile to the North, South, East, and West of the AirHead, each installed with a direct link to the AirHead. In each scenario, the number of randomly located subscriber devices was then varied from 1 to 50. Of course, the PMP network is unaffected by the number of subscriber devices, the probability for network connectivity remaining at about 25.1% for all scenarios (using the same baseline radio used for the mesh simulations, no directional antennas, no high towers, etc.). For the WR network, the probability of the first subscriber is, of course, also about 25.1%. Then, as more subscribers are added to the network, the probability increases rapidly (as predicted by the simple Link Probability Model), reaching about 90% coverage with 15 subscribers, and about 99% with 25 subscribers. With the WR network primed with the 4 seed nodes, the coverage probability of the first subscriber is around 74%, and increases to 90% after just 8 subscribers.

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Figure 7 – Coverage probability versus number of devices in example scenario with Log-Normal path loss model.

Figure 8 shows the distribution for the number of hops from the AirHood for a 50-subscriber wireless routing network, with and without the 4 seed nodes, and for comparison, also shown is the distribution for the simple Link Probability model for a 50-subscriber network using a link probability of 25.1% (set to be the same as the PMP coverage probability).



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Figure 8 – Distribution of hops from AirHead in 50-subscriber scenario with Log-Normal path loss model.

2.4 Robustness to Link Changes

When designing and installing PMP wireless networks, extra link fading margin must be included to overcome some degree of potential changes in the propagation environment (e.g., new tree growth, changes in multipath fading due to new reflecting surfaces, etc.). However, when the changes are so severe that the additional fading margin is insufficient, then a subscriber outage results, typically requiring an operator (or installer) “repair visit” to reorient or reposition the subscriber antenna in an attempt to restore service.

The capability of WR networks to automatically switch to alternate paths when necessary highlights two important, related advantages of WR networks:

1. Automatic recovery from link failures substantially reducing the need for operator repair visits, and

2. A reduced link fade margin requirement thus easing installation and reducing equipment costs.

Automatic Recovery from Link Failures

When, despite any fade margin allowance, a link between two devices in a WR network becomes obstructed or otherwise fails, there is a very high probability that alternate links and paths exist that can be automatically put to use, thus avoiding subscriber outages and operator repair visits.

For example, the scenario where all of the links to and from one of the devices are lost entirely can be modeled by adding the curve “AirHead + 24” to Figure 3. This curve will very closely resemble the “AirHead + 25” curve. For instance, using a link probability of 25%, the probability of continued coverage is still 99.92% with the 24-device AirHood (versus the 99.94% probability of coverage for the 25-device AirHood). A similar result can be derived from the example scenario and Log-Normal model used for the curves presented in Figure 7.



Reduced Link Fade Margin Requirement

Because WR networks are able to automatically switch to the best links available at the time, and because the probability that such links exist is high, the additional link margin used for network planning can be reduced substantially when compared with PMP networks. For example, whereas a 10-15 dB fade margin may be employed in PMP wireless systems to overcome most (e.g., 99.9% of) fading situations, a much smaller fade margin can be sufficient for planning WR networks because there is typically no reliance on specific links.

To quantify this fade margin difference, simulations were run to determine the difference in link performance required to go from a 99.9% coverage probability to a 99.9% probability of not only having coverage, but of also having at least one alternate path for each device in the network. Specifically, 25- and 50-device AirHood simulations were run using the above scenario assumptions with the Log-Normal path loss model, but varying the path loss allowance by 1 dB for each series of trials. The path loss allowance required for a 99.9% coverage probability was compared with the path loss allowance required for a 99.9% probability of having coverage plus at least one alternate path for each device. With the 25-device AirHood tests, the resulting path loss allowance difference (or the required “mesh fade margin”) was 5 dB for both the scenarios with and without the 4 seed nodes. With the 50-device AirHoods, the resulting difference was a 6-dB mesh fade margin requirement for both the scenarios with and without seed nodes.

Therefore, assuming a 12-dB fade margin requirement for PMP networks and 6 dB for mesh WR networks, then WR networks enjoy a 6-dB fade margin advantage.

2.5 Effect of Radio or Other Link Improvements

Of course, both PMP and WR networks can take advantage of advancements in digital radio technology to increase their link ranges, data rates, and robustness to interference. These advancements can be roughly summarized as an improvement (in dB) of the signal-to-noise or signal-to-interference level that can be overcome, and corresponding receiver sensitivity, at each modulation rate. To determine how this improvement would effect coverage, the Log-Normal simulations were repeated on 25- and 50-device networks but with a “link improvement” factor (I) varying from –30 dB (degraded radios or link propagation paths) to +40 dB. The link connectivity check was modified accordingly to Lab � A+I.

Figure 9 presents the results for four scenarios: PMP, PMP + 6 dB fade margin, 50-device mesh, 50-device mesh + 4 seeds, 25-device mesh, and 25-device mesh + 4 seeds. The new scenario, “PMP + 6 dB fade margin” adds 6 dB of additional fade margin for the PMP network due to its reliance on single links between the subscribers and the base station (refer to Section 2.4 for more details).



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Figure 9 – Coverage improvement versus link performance (such as improved radio systems)

For this scenario (average path loss exponent 3, AirHood or cell radius of 1 mile, etc.), Figure 9 leads to the following conclusions:

��For an 85% coverage target, the “cost” in link performance required for the “PMP + 6dB fade” margin solution is approximately

o 35 dB greater than that required for the 50-device mesh solution, and o 30 dB greater than that required for the 25-device mesh solution.

��For a 95% coverage target, the “cost” in link performance required for the “PMP + 6dB fade” margin solution is approximately


��For a 99% coverage target, the “cost” in link performance required for the “PMP + 6dB fade” margin solution is approximately


��Between 15% and 85% coverage, the rate of increasing coverage probability is: o 2.9% more coverage per dB of improved link performance for the PMP solution,

and o 8.4% to 11% more coverage per dB of improved link performance for the 25-

and 50-device mesh solutions, respectively. Note that the “link performance improvement “ figures can also be interpreted as the result of combining multiple mechanisms to improve the link including the use of directional antennas at PMP subscriber sites, and mounting the PMP base station antenna on a high tower. However, this huge advantage in the required link performance for mesh wireless routing versus point-to-multipoint approach translates into mesh radio systems with much lower cost, AirHead



antennas mounted lower and less exposed to outside interference than their base station counterparts resulting in higher link data rates, and subscriber devices which are easier to install and more robust to link changes.

Although wireless routing methods can be used in combination with virtually any radio technology, it essentially shifts the system economics and planning from sophisticated but expensive infrastructures and radio technologies, which attempt to overcome obstructions and subsequent environmental changes by “brute force” radio and signal processing methods, to a mesh of smart devices running protocol software on components that have enjoyed the benefits of a couple decades on the “Moore’s Law" cost-performance curve.

2.6 Providing Initial Coverage

Of course, in order for the coverage and robustness benefits of mesh wireless routing networks to take effect, some number of WR devices must be operating in the area. Various approaches that can help ensure this initial and continued robust coverage include:

��Using a “targeted marketing” approach to roll out pockets of coverage quickly, one area at a time, rather than in a scattered manner.

��Installing some number of “seed nodes” into an area, either at first-adopter home or office sites, or on utility poles or other locations to which the operator has access. As illustrated in Figure 7, installation of only a handful of seed nodes can have a dramatic effect on the coverage probability for the first subscribers. These “seed nodes” need only be used for initial network coverage, and can optionally be removed after a sufficient number of subscribers are connected to the wireless router network.



3. NATURAL SCALING

Growing the footprint and density of wireless routing networks benefits from the unique characteristic that interference is attenuated at a faster rate (per distance traveled) than the rate for the desired signals in typical networks. This section will review the cause and nature of this powerful trait, which allows wireless routing networks to grow and re-use channels with less planning and increased spectral efficiency than alternative methods.

3.1 Signal Versus Interference Propagation

For a given RF channel, system scalability can be considered as the modulation rate that can be sustained over an active link despite the sum of interference power being received by all of the other active transmitters out to the radio horizon. Critical parameters for this computation are the average path loss exponents for the propagation paths followed by the interfering signals versus that for the intended signals.

Due to the usual strategy of mounting PMP base stations on towers to achieve sufficient coverage, each base station must be designed and deployed to be capable of receiving transmissions from a range of subscriber devices within its cell (with propagation paths around a mean 1/r3 path loss factor, for example), despite interference from other base stations (e.g., close to 1/r2 path loss factor � “I1” on the left side of Figure 10), or from subscriber devices in other cells that happen to have a relatively clear path to the local base station (e.g., also close to 1/r2 path loss factor � “I2” on the right side of Figure 10). Even when base stations use sector antennas oriented to avoid direct co-channel interference in the main lobes of the antennas, the front-to-back ratios of these antennas are still often insufficient to counter the near free-space path conditions between the base stations. Therefore, at the base station receiver, the propagation paths of the major sources of interference often have a more favorable path loss exponent than that for the paths to many of the subscribers within its cell. Raising the base station antenna further improves the coverage within that cell, but at the cost of stronger interference.

Figure 10 – Interference scenarios at point-to-multipoint base station receivers.

Also, a similar problem is due to the interference received at a subscriber device from transmissions by other base stations that happen to have a clear path to this subscriber. These problems are exacerbated when subscriber devices are moved indoors, due to the increased variations in the path loss between the subscriber devices and base stations.



A number of PMP strategies have evolved to combat this unfavorable interference problem that include the use of:

��Frequency Division Duplexing (FDD) or synchronized Time Division Duplexing (TDD) among all base stations within each region, to avoid interference from other base stations, at the cost of essentially fixing the up- & down-stream bandwidths throughout the region as well as increased equipment costs (for duplexers needed for FDD) or increased scheduling overhead (due to the long guard times needed for synchronized TDD throughout a region),

��Directional antennas at the subscriber device to focus its transmit power, and receive gain, on the intended base station, at the cost of reliance on the single link between the subscriber and the base station, more costly installations which require trained personnel, and more operator repair visits when this link fails,

��More careful sectorization and channel planning, with increased installation costs, and

��More sophisticated radio equipment to filter out the interference and better extract the desired signal, at increased equipment expense.

In wireless routing networks, this relationship between the propagation path loss exponents of the interference versus the desired signals has the opposite relationship! As discussed in Section 2.1, local path-loss characteristics are highly variable, dependent largely on the presence and type of any obstructions in the paths. In the case of wireless routing networks, the selection of the active links to be used is not random; the links selected are the best available which ensure overall network connectivity. In addition, because of the lack of high base station towers (even at the AirHead), and assuming that the nearby devices are coordinated to avoid interfering transmissions (see Sections 3.2 and 4.2), then the propagation paths of the interference signals will more closely follow the mean path-loss exponent of the region. For example, for interfering signals to follow a clear path to receiving devices in a wireless routing network, it is typically not enough for the interferer to be located in a remotely visible location (as is the case for the PMP scenarios in Figure 10), but both the interfering and receiving subscriber or AirHead devices must be located in this way, with a clear path to each other. More often, even when a distant, potentially visible interfering device is transmitting in a WR network, the receiving device will still be shielded by neighborhood “clutter” (as in Figure 11).

Therefore, the active links in a mesh network are not only generally shorter than the links needed in a PMP network, but will also tend to encounter path loss exponents that are lower (e.g., 1/r2.5) than the mean path-loss exponent of the region (e.g., 1/r3) over which the interfering signals propagate.



Figure 11 – Interference scenario in wireless routing network.

This is a key, unique characteristic of mesh networks which allows it to scale to large networks while maintaining dynamic TDMA transmission scheduling, adaptive to the up- and down-stream traffic needs, easing installation and planning costs, and using high-volume radio components which are affordable for residential business cases. In other words, the basic physics of scaling to large networks favors wireless routing.

To estimate a typical path loss distribution for the active links in a wireless routing network, the simulation scenario described in Section 2.5 was run for a 50-device mesh network, with a link performance degradation of -6 dB, which results in a 99% coverage probability (see Figure 9). Then, each link in the mesh network was assigned a modulation rate based on the highest supportable rate for the path loss over that link, in accordance with Table 1.

Table 1 – Modulation rates supportable over a range of path loss and signal-to-noise values for “baseline” radio.

Link data rate (Mbps) 3 6 9 12 18 24 36 48 54

Max. link path loss (dB) 124 123 121 119 116 112 108 107

Max. signal-to-noise (dB) 16 17 19 21 24 28 32 33

(Note that in this scenario, the maximum path loss allowance for any link is 124 dB rather than the 130 dB specified in Section 2.3, due to the -6 dB link degradation used.) The active links were then determined by computing the minimum delay paths between each subscriber device and the AirHead using the Dijkstra shortest path algorithm with the reciprocal of the data rate as the delay “cost” of each link. (See Section 4.1 for a related analysis on this choice of routing paths.)

Figure 12 presents an example trial showing all of the wireless routing links on the left, and only the active, minimum-delay-path links on the right. Notice that due to the random variable used in the Log-Normal path loss model, the minimum delay paths often follow trajectories that

3 The path loss figures correspond to an 802.11a-compliant radio (see [802.11a]) improved by 6 dB over the minimum 802.11a receive sensitivity requirements, if using 8 dBi omni-directional antennas and 20 dBm transmit power for example. The baseline signal-to-noise values were set using a fixed offset (representing reasonable noise figure and implementation loss values) from these receive sensitivity values.



are not the most geographically direct between each subscriber and the AirHead.4 As a side comparison, Figure 13 presents another example trial using the Log-Distance model with the path loss exponent reduced to 2.5, to ensure connectivity. As expected, with all randomness in the path loss formula removed, the minimum delay paths do follow trajectories that are much more geographically direct (e.g., notice the absence of any crossing links in Figure 13).

-1 6 0 9

0

1 6 0 9

-1 6 0 9 0 1 6 0 9

-1 6 0 9

0

1 6 0 9

-1 6 0 9 0 1 6 0 9

Figure 12 -- 50-device wireless routing network showing all of the usable links (on left) and only the active, minimum-delay-path links on the right (path loss exponent 3, standard deviation 10 dB).

-1 6 0 9

0

1 6 0 9

-1 6 0 9 0 1 6 0 9

Figure 13 – 50-device wireless routing network with active, minimum-delay-path links shown (path loss exponent 3, standard deviation 0 dB).

Returning to the Log-Normal model, and the problem of determining a typical path loss distribution for the active links in WR versus PMP networks, 200 simulation trials were performed with the 50-device mesh case and the PMP case. For each case, the link

4 Note that this characteristic highlights a key problem in basing the micro-routing decisions (e.g., within an AirHood) on geographic coordinates, rather than on the actual RF quality of the links between the devices.



performance (or “system gain”) was set according to the analysis performed in Section 2.5 to ensure 99% coverage. This meant using a link performance degradation of –6 dB from the baseline radio and path loss allowance for the WR case, and a +33 dB link performance improvement for the PMP case. For example, this 39 dB difference can be accounted for by the use of directional antennas at the PMP subscriber devices, by higher power and more sophisticated PMP radios, and higher base station antenna towers. The resulting path loss and distances for the links for all trials is shown in Figure 14. Because the wireless routing network selects the best links available, the average path loss exponent for the active links is considerably lower (2.49)5 than the simulation scenario’s mean path loss exponent (3.0), and even further from the average path loss for the PMP links (3.31).6 Also, the average distance for the active links in the mesh network was approximately half that for the PMP network (608 versus 1069 meters).7 In actual deployments, coverage targets for individual AirHoods or base station cells can typically be much less than 99% due to the additional chance of being connected to devices or base stations in neighboring AirHoods or cells. However, 99% is used above to minimize the skew in the path loss results caused by the subscriber devices with the greatest path loss links which were not able to connect to the network, and thus were not included in the results. Nevertheless, to ensure that the resulting relationships were also valid at lower coverage rates, the simulation was repeated using an 85% coverage target, which required a link degradation of -10 dB for the 50-device mesh scenario, and +19 dB for the PMP network. Figure 15 presents the path loss distribution results. The average path loss exponents were 2.45 for the mesh network and 3.08 for the PMP network, and again, the average link distance for the mesh network was approximately half that for the PMP network (551 versus 1031 meters).8

5 Except where noted, the average path loss exponent was computed using the average of the absolute path loss factors rather than the average of the logarithmic (dB) values. 6 Note that this value is greater than the mean path loss setting (3.0) due to the way that the Log-Normal path loss model distributes values around the mean using a standard deviation in units of dB rather than in absolute values. If instead the path loss exponents of all of the data points for the PMP case are first computed individually, and then the average of these exponents is computed, then the result is a path loss exponent of 2.987, which is only slightly less than 3.0 due to the 99% (less than full) coverage, and the fact that the links to subscribers that were not reached had the greatest path loss values. 7 Note that for the wireless routing scenario in , the path loss values are capped (at 124 dB) due to the use of alternate links to obtain the 99% coverage target, rather than by requiring radios and installations with high link performance. On the other hand, for the PMP scenario, much better link performance is required to achieve the 99% coverage target and the cap is instead in the distance dimension, at the 1-mile radius from the base station.

Figure 14

8 In the PMP case in F , there is also an apparent cap in the path loss dimension, due to the 15% of devices that can’t be reached.

igure 15



60

80

100

120

140

160

10 100 1000 10000Distance for active mesh links (meters)

Path

loss

(dB) n=2

n=3

n=2.49

60

80

100

120

140

160

10 100 1000 10000Distance for PMP links (meters)

Path

loss

(dB) n=2

n=3

Figure 14 – Path loss versus distance for the active links in a 50-device mesh network (left) and for the links in a PMP network (right), normalized with link performance settings that provide 99% coverage for each case.

60

80

100

120

140

160

10 100 1000 10000Distance for active mesh links (meters)

Path

loss

(dB) n=2

n=3

n=2.45

60

80

100

120

140

160

10 100 1000 10000Distance for PMP links (meters)

Path

loss

(dB) n=2

n=3

Figure 15 – Path loss versus distance, with scenarios normalized to provide 85% coverage for each case.

3.2 Network Capacity in Large, Dense Networks

This subsection will further examine the consequences of the scaling advantages for wireless routing networks discussed in section 3.1 above, particularly as they relate to the overall capacity of large, dense networks. For this analysis, we will use the 4-channel deployment model illustrated in Figure 16.



The entire network, out to the radio horizon, at radius Rh. Outside of the local region, devices (and AirHoods) are assumed to use the local AirHood’s channel according to an average density.

The “local region,” radius Rl, consisting of this local AirHood plus a collection of surrounding AirHoods, all of which use a channel other than the one being used in the local AirHood.

3 4

1 2

4

2

4 4 3

The “AirHood” of radius Ra, including the AirHead, within which transmissions are coordinated to avoid collisions, and where, in a dense network, a single channel is shared.

Figure 16 – Definition of the AirHood, the Local Region, and the rest of the regional network.

By having each device choose its active links amongst its nearest 8 neighbor devices (nearest in an RF sense), and by using adaptive power control to ensure that each transmission reaches the intended receiver at approximately a target receive level (adjusted by the regional noise conditions), then the average signal to interference ratio (SIR) for any transmission can be determined using the following equation (refer to Appendix A for the derivation):

DR

horizonvisiblehorizonradioRDNR

RRR

yaDTSIR

xT

h

l

yh

yl

xT

TB

dBmdBm

dBmdBm

�

�

�

30002

3/4~/3000

1110)2(2

1010log10

)2/(1

2261010

10

��

�

��

��

�

�

��

�

��

��

��

��

��

��

where Rl is the radius of the local region (see Figure 18), RT is the distance corresponding to the average transmit power, x is the average path loss exponent for the active links, y is the mean path loss exponent for the region, TdBm is the target receive signal level, BdBm is the noise floor, a is the average transmit duty cycle for each wireless router, D is the density of wireless routers in devices per square km, and N-1 is the average diameter, in hops, of each AirHood.9

Using this SIR equation, Figure 17 presents an example of the modulation rates that can be supported in a wireless routing network as the density of the network increases given the following assumptions:

9 With frequency hopping radios, the analysis is similar, except that the interference from the neighboring AirHoods can be handled as a statistical chance for collisions (resulting in occasional retransmissions), and the interference outside of the local region is lowered significantly by setting the density parameter D to the actual device density divided by the number of orthogonal hopping frequencies.



��802.11a (unimproved) radios using the signal-to-noise values listed in Table 1, and “improved” radios with signal-to-noise values which are 3 dB lower than those in the table;

��Transmit power control limitations are ignored; ��Use of four, 802.11a channels throughout the network; ��Noise floor value of -95 dBm; ��Mean path loss exponents of 3.0 for the region and 2.5 for the active links (see Section

3.1);10 ��50-km radius to radio horizon (total of about 4 million devices at 500 per sq-km); and ��50-device AirHoods with diameters of 3 hops, each busy with transmission activity 75%

of the time.

0

10

20

30

40

50

60

0 100 200 300 400 500

Wireless routers per square km

Link

dat

a ra

tes

- Mbp

s

802.11a radio

802.11a improved by 3 dB

0

50

100

150

200

250

300

0 100 200 300 400 500

Wireless routers per square km

Mbp

s pe

r squ

are

km

802.11a radio

802.11a improved by 3 dB

Figure 17 – Reliable wireless routing link data rates (left) and capacity per square km (right) for 802.11a-style radios as network density increases.

Because of its ability to adaptively shrink the “microcells” around each wireless router using power control and adaptive neighbor and routing algorithms, and by keeping the number of wireless routers per AirHood roughly constant (by injecting new backhaul links into new AirHead sites as the density increases), the total capacity per unit area is able to increase at a nearly linear rate with increasing density.

Note that this analysis also suggests that in regions with few buildings, trees, hills or other “clutter” between neighborhoods, the wireless router antennas should be mounted relatively low (i.e., not raised on a high mast), to ensure a significant path-loss exponent between itself and devices in remote AirHoods, while still maintaining connectivity to devices in its own AirHood.

10 When computed from the interference power received, the average path loss exponent for nearby interference sources will actually be greater than 3.0 (see footnote 6); however, this average exponent will approach 3.0 for remote sources due to the diminishing influence of the random variable in the Log-Normal path loss formula with increasing distance.



3.3 Planning AirHead Sites

To consolidate backhaul bandwidth and installation costs, AirHeads can be grouped at AirHead sites. Figure 18 presents a typical scenario for the 4-channel deployment model, where each AirHead site is equipped with a wired or point-to-point wireless backhaul link and 4 AirHeads with sector antennas directed toward the four supported AirHoods. Sector antennas are normally used at the AirHead site to avoid adjacent-channel interference among the co-located AirHeads, and to more effectively reach the 1-hop subscriber devices of the corresponding AirHood.

Note that this deployment model is also consistent with Figure 16, with AirHeads grouped at the AirHood corners. Also note that the capacity analysis performed in Section 3.2 assumes the use of omni-directional antennas for all of the wireless routers, so that analysis is actually pessimistic regarding the interference received from remote AirHeads, and the vulnerability of AirHeads from remote interference.

2 1 2 1 1

3

1

4 3

2 1

4 3

2 1

2 1

3 3 4

2 1

3 4

1

Channel being used by this AirHood.

AirHead sites with 4 AirHeads (one per channel) and one P2P backhaul link.

Figure 18 – Typical 4-channel wireless routing deployment.

3.4 Growing with Increasing Customer Density

The nature of wireless routing permits an economically attractive migration to increasingly dense networks, rather than requiring the initial infrastructure build-out to be sized according to the eventual, target subscriber density. This gives operators the flexibility to install an initial infrastructure that’s sized appropriately for the initial subscriber density, and then, with the benefit of revenue from the first subscribers, continue to build-out the network infrastructure as the subscriber density increases. This benefit is due to the following WR characteristics:

��The WR protocol software can automatically reduce its transmit power and adapt to using the nearest set of neighbor devices and best paths to the AirHead according to the network density.

��As the network density increases, the operator can setup new AirHead sites, or install additional AirHeads at current AirHead sites, and then re-associate some of the existing subscriber devices with the new AirHeads as appropriate, or even have the subscriber devices select the nearest AirHead automatically. In particular, no operator visit is needed to re-orient the subscriber’s antenna.



Therefore, the microcells around each WR naturally scale down in size, and the AirHoods of each neighborhood network are easily split, to permit efficient reuse of the RF spectrum throughout the region even with dramatic increases in subscriber density.

3.5 Using Unlicensed Spectrum

The scaling and coverage characteristics of wireless routing networks described above also have an important, indirect consequence of permitting the reliable use of “unlicensed” frequency bands. In the U.S., these bands include the Industrial Scientific and Medical (ISM) bands of 902 to 928 MHz, 2.4 to 2.485 GHz and 5.725 to 5.875, and the Unlicensed National Information Infrastructure (U-NII) bands of 5.15 to 5.25 GHz (indoor only), 5.25 to 5.35 GHz, and 5.725 to 5.825. WR characteristics that make possible the reliable use unlicensed frequency bands includes the following.

��The shorter and lower-path-loss links in a WR network result in a reduced transmit power requirement for each link. This enables the use of radios which comply with the unlicensed transmit power regulations (e.g., 4 Watt effective isotropic radiated power (EIRP) for the ISM and upper U-NII bands), in addition to decreasing the costs of the RF amplifier.

��Because the WR antennas are mounted low, within the neighborhood “clutter” (no high base station antennas), and because the active links in the WR network are intelligently selected, the interference from outside sources (including other unlicensed products) is attenuated at a much greater rate than that for the active links in the WR network (see Section 3.1).

Of course, the ability to employ unlicensed frequency bands has a dramatic effect on cost and flexibility of wireless broadband solutions due to:

��Zero cost for spectrum license; ��Low cost radio equipment by taking advantage of components developed for other

unlicensed applications (such as wireless LAN); ��After equipment certification, no reliance on FCC approvals for roll-outs into each

market; and ��National or global spectrum availability, depending on the band.



4. MULTIMEDIA, BROADBAND SERVICE

Although the coverage and scalability benefits of wireless mesh networks are often reasonably evident, the quality of service capabilities and benefits for handling multimedia broadband traffic are often not as apparent. In particular, a couple of common questions are:

1. “Doesn’t the act of forwarding traffic over multiple wireless hops necessarily result in lower end-to-end throughput?” and

2. “Aren’t wireless mesh networks too chaotic to provide the bandwidth and delay quality-of-service assurances needed for multimedia traffic like voice?”

This section reviews possible sources for these questions and discusses characteristics and design approaches for mesh networks that enable them to meet and exceed the demands of high-speed multimedia traffic.

4.1 Throughput over Multiple Wireless Hops

Rather than sending packets directly from a subscriber unit to the base station (or AirHead) over a direct link, mesh networks tend to route the packets through some number of (e.g., 1 to 3) intermediate subscriber devices before reaching the AirHead. Therefore, multiple transmissions are required for each packet before it has arrived at the AirHead, rather than the single transmission needed in a point-to-multipoint system. It is then natural to predict that these multiple transmissions will result in a lower overall end-to-end throughput.11 However, this prediction ignores one of the key features of wireless networks – their ability to adapt the modulation rate based on the individual quality of each link. With this feature, smart wireless routers can automatically increase the modulation rate to take advantage of the lower path loss of the shorter links involved in multihop paths.

As an example using standard 802.11a-style radios12 (see [802.11a]) with the signal-to-noise specifications in Table 1, and each with identical, omni-directional antennas, consider the choice of routing over a single direct link from a subscriber device to the base station (or AirHead) versus routing through an intermediate device that’s centered between the other two devices. For the case of the routed path, two transmissions must be made for every packet rather than one if the direct link is used. However, assuming that equal transmit powers are used in each case, equal noise environments at the receivers, and a 1/r2 path loss factor, then there will be a 6-dB advantage in the signal-to-noise ratio for each of the transmissions over the routed path versus that for the direct link. For 802.11a radios, this 6 dB advantage can translate to being able to use the 18 Mbps rather than 6 Mbps modulation rate for those transmissions. Therefore, for this case, the effective potential throughput over the routed path would actually be 50% greater than that for the direct link (9 Mbps effective throughput versus 6 Mbps), while generating 33% less total

Figure 19 – Choice of using direct link versus routed path.

Intermediate device AirHead Subscriber

11 This discussion also assumes that single-transceiver wireless routers are used for the subscriber devices to minimize their cost. 12 Note that this only refers to the 802.11a physical layer specifications, and not the 802.11 MAC protocol (see inset titled “802.11 ‘ad hoc’ doesn’t mean multihop” for a related discussion on this).



co-channel interference power into other neighborhoods due to the reduced total time required for the two transmissions.

For path loss exponents greater than 2, the advantage for the multihop route is even greater. For instance, using a 1/r3 path loss factor in the above example, and with the distances reduced to allow comparison against the same 6-Mbps data rate over the direct link, then the multihop links would be able to use the 24 Mbps waveform resulting in a 100% potential throughput advantage (12 versus 6 Mbps) and 50% reduction in interference generated to other neighborhoods. Table 2 compares the effective throughput of using the direct link versus using a multihop route for a variety of path loss exponents and number of equally spaced intermediate forwarding devices.

Table 2 – Throughput comparison for direct links versus multihop routes Using 802.11a-compliant radios.

able 2

Case Path loss

exponent

Direct link modulation

rate13

Number of intermediate forwarders

Multihop modulation

rates

Effective multihop

throughput14

Multihop throughput advantage

1 2 6 Mbps 1 18 Mbps 9 Mbps 50% 2 2 6 Mbps 2 24 Mbps 8 Mbps 33% 3 2 6 Mbps 3 36 Mbps 9 Mbps 50% 4 3 6 Mbps 1 24 Mbps 12 Mbps 100% 5 3 6 Mbps 2 36 Mbps 12 Mbps 100% 6 3 6 Mbps 3 54 Mbps 13.5 Mbps 125% 7 4 6 Mbps 1 36 Mbps 18 Mbps 200% 8 4 6 Mbps 2 54 Mbps 18 Mbps 200% 9 4 6 Mbps 3 54 Mbps 13.5 Mbps 125%15

Figure 20 compares the performance benefit of selecting the two-hop route versus the direct link for different values of the path loss exponent. Notice that the performance improvement for the two-hop path increases at nearly the rate of the path loss exponent squared. For example, as the path loss exponent doubles from 2.2 to 4.4, the performance improvement increases by a factor of 4.

13 To ease comparison, the absolute link distances are modified so that the modulation rate achievable over the direct link is 6 Mbps for each case. Across the range of the standard 6 and 54 Mbps 802.11a modulation rates, the increase in data rate per dB in receive signal is fairly consistent, at approximately 2.7 Mbps per dB of signal improvement. 14 This table assumes the communication of relatively large (e.g., 1000-byte) packets, so that per-packet overhead such as framing and MAC headers can be ignored. Also, fast-forwarding hardware or software is assumed which is capable of forwarding IP packets at a rate that’s faster than they can be transmitted or received over the radio interface. 15 The multihop throughput of case 9 in T is limited by the maximum 802.11a data rate of 54-Mbps, and thus has an additional 7dB of margin over each link compared with the other cases.



0%

50%

100%

150%

200%

250%

300%

350%

400%

2 2.5 3 3.5 4 4.5 5 5.5 6

Path loss exponent

Thro

ughp

ut a

dvan

tage

of 2

-hop

pat

h

Figure 20 – Throughput advantage of the two-hop path versus the direct link for increasing values of the path loss exponent using 802.11a-compliant radios.

Note that the following additional considerations have not been included in this analysis:

1. In highly obstructed regions, and with proper scheduling among sufficiently isolated devices, mesh networks can also support simultaneous transmissions over multiple links within single AirHoods. Such transmissions can of course result in a further increase in performance for the mesh approach, within the limits of the capacity at any traffic concentration point (in particular, at the AirHead).

2. Because wireless routers are able to select the neighbor routers to use for forwarding packets based on the best RF-quality links available -- both at the link layer when selecting neighbor links, and at the routing layer when selecting alternate paths to and from the AirHead -- these multihop paths will tend to use links with lower path-loss exponents and better multipath fading conditions than the direct link to the AirHead, potentially leading to even higher modulation rates. However, this improvement is balanced somewhat by the fact that these paths will in general involve intermediate devices that are not along the direct line between the subscriber and the AirHead.

Comparison with Point-to-Multipoint

In point-to-multipoint networks, the path loss (and associated performance disadvantage) for the longer links is sometimes overcome by the use of directional antennas at the subscriber end.16 Such use of directional antennas also reduces the amount of (and vulnerability to) noise to (from) subscriber devices in other neighborhood cells. However, the link-range advantage of directional antennas is either limited by the relatively low EIRP transmit power limits of unlicensed bands, or requires the use of licensed bands, which have higher EIRP limits. Also, use of directional antennas at the subscriber premise is accompanied by the disadvantages of

16 For example, for case 8 in (1/r4 path loss factor comparing the direct link to a multihop path with two forwarding nodes), the throughput of the direct link can be improved to equal the multihop throughput by using a subscriber antenna with 5dB additional directional gain (e.g., using 13 dBi directional antennas versus 8 dBi gain omni-directional antennas for the multihop case).

Table 2



increased installation costs, increased vulnerability to environmental changes that may obstruct a subscriber’s link, and scaling limitations due to the need to re-steer subscriber antennas to associate them with different base stations when splitting cells or balancing capacities.

These scenarios also assume that the noise level at each of the receivers is the same. However, to meet coverage requirements, point-to-multipoint architectures typically require that the base station be mounted on relatively high towers. For coverage purposes, this has the desired effect of reducing the path loss to near free-space characteristics for a portion of the path toward the subscriber devices (thus increasing the receive signal strength for the up- and down-stream links); however, this is accompanied by the undesirable effect of also reducing the path loss from, and increasing the effect of, interfering transmissions in the region (in addition to the increased cost and logistics in locating, leasing, obtaining needed approvals for, and installing the base station towers). This interference problem must then be overcome by more careful channel planning and/or by the use of more sophisticated radio equipment.

Lastly, because base station towers with omni-directional or sector antennas are not required for mesh networks, fully adaptive TDD/TDMA channel scheduling can be used to optimally match the up- and down-stream traffic requirements of each AirHood. However, PMP networks must often resort to FDD or synchronized TDD methods (synchronized across all base stations within a region) to avoid base station-to-base station interference, essentially fixing the up- and down-stream bandwidths (by spectral bandwidth in the FDD case and by time in the TDD case). See Section 3.1 for more details on this.

4.2 Efficient, Fair and Reliable Channel Access

The wireless channel in multihop mesh networks comes with unique challenges to fair, efficient and reliable transmission scheduling and link-layer service. Unlike point-to-point wireless or wired links, each transmission must be coordinated among multiple neighbor devices; unlike other shared networks such as Ethernet or fully-connected wireless networks, the set of devices affected by each transmission differs greatly depending on which device is transmitting; and unlike point-to-multipoint wireless networks, there is no master controller within the range of every device to coordinate scheduling (also, see the inset box titled “802.11 ‘ad hoc’ doesn’t mean multihop”). Furthermore, transmissions by pairs of devices that are unable to successfully communicate can result in collisions at the receiver(s) (known as the “hidden terminal problem”), and for further complication, devices that are within hearing range of each other are still sometimes able to successfully transmit packets simultaneously to neighbor devices that are isolated from the other transmitter, but would be restrained from doing so using traditional channel access protocols.

These challenges have required the development of new channel access methods, designed specifically for multihop mesh networks. With these new methods, combined with Internet DiffServ-compliant packet handling, wireless mesh networks can become seamless extensions of the wired Internet, able to handle the service demands of multimedia broadband traffic as well or better than the rest of the Internet, only with wireless links between the routers rather than wired links.

In order to provide the reader with a concrete design approach able to meet the service challenges of multihop mesh networks, the following sections outline the key characteristics of the mesh-mode channel access extensions currently included in the IEEE’s draft 802.16 MAC standard. Section 4.3 then discusses how these channel access methods can be extended by



QoS-sensitive classification and packet handling methods to ensure high-quality service for multimedia traffic.17

Network Timing Structure

First, the network uses a distributed protocol to ensure that all devices in the network are synchronized to the same time base. Time is measured in microseconds, slots, frames, and super-frames. Slots are 2x microseconds in duration, there are 256 slots in a frame, and there are 2y frames in a super-frame. The first 2z slots in each frame are reserved for control packets, with the remainder of the frame being used primarily for data packets. (x, y & z are integers.) The first control portion of each super-frame is reserved for “network configuration” packets, while the control portion of the other frames is used for “data scheduling” control packets. Figure 21 presents an example timing structure using the values: 32 �s per slot, 32 slots in the control portion of each frame, and 8 frames per super-frame.

65,536-�s super-frame

Network Configuration Control

Data Scheduling Control

Network Configuration Control

224-slot (7,168-�s) data portion

256-slot (8,192-�s) frame

32-slot (1,024-�s) control portion

32-�s slot

Figure 21 -- Example timing structure for multihop mesh network.

Network Configuration

The first control portion in each super-frame is used for network configuration packets (the first ~1 ms in every ~65-ms super-frame in the above example). The main purposes for these packets are:

�� Initialization and maintenance of network synchronization;

�� Support for secure network entry of new devices;

�� Detection of new or lost links between devices;

�� Measurement of the link qualities and path loss between devices; and

17 The channel access and QoS methods described are also those used in the Nokia RoofTop Wireless Routing product family.



�� Dissemination of the information needed by the distributed scheduling algorithm used for these network configuration packet transmissions.

Data portion of frame

Dist. sched. A � 2 1 � A

Distributed scheduling 2 � 3Channel 2 �

Channel 1 �

A

AirHead

2 Subscriber 2

3

Subscriber 3

1

Subscriber 1

Figure 22 -- Simple example network and data transmission schedule.

Because of their “boot-strapping” role, the scheduling of these network configuration packets uses a fair, robust, and completely distributed algorithm, which ensures collision-free transmissions among the devices in each local area. Also, by including a phantom device in the scheduling, periodic measurements of the background noise can be made. With the noise level and path loss information per link, the transmit power and modulation rate can be set appropriately according to the network density and signal quality of each link.

Data Transmission Scheduling

The remaining control portions of each frame are used for transmitting data scheduling control packets. The transmission scheduling for these control packets can be efficiently determined by the device being used as an Internet access point (i.e., the AirHead). For example, super-frames can be further grouped into “scheduling epochs.” During the first half of each scheduling epoch, the current persistent traffic demands at each wireless router within an AirHood are reported up to the nearest AirHead. The AirHead then computes a revised AirHood schedule and, during the second half of the scheduling epoch, distributes this schedule throughout the AirHood to become effective at the next scheduling epoch boundary. The AirHood schedule consists of a list of active links, each associated with a {slot range, channel assignment, frame number offset, and frame occurrence rate} set, to be used during that scheduling epoch. In addition, the AirHood schedule can include a list of unscheduled slot ranges, which can be used by the distributed scheduling method described below. These assignments are then used in each frame to transmit data across the active links in a collision-free manner. Figure 22 presents a simple example network and the snapshot of the schedule for a particular frame which supports two active traffic flows, one down-stream from the Internet to subscriber 3, and one up-stream flow from subscriber 1 to the Internet, and which assumes availability of two channels for use by this AirHood.

With this scheduling method, and with proper subscriber provisioning (see Section 4.3), the per-hop latency for at least for the high priority traffic will be bounded. For instance, with active links that are allocated slot ranges in each frame, the per-hop latency for the high priority traffic will be limited to about 8 ms using the timing structure of Figure 21. Note also that data packets should be fragmented (and reassembled) at the link-layer to efficiently fill the slot range in each frame for each active link. Also, link-layer acknowledgments with selective retransmissions should be used to ensure reliable delivery of each packet (or packet fragment) across each link; therefore, each active link must also be assigned at least a minimally-sized



slot range in the reverse direction for transmission of the acknowledgment packet. (These small reverse slot ranges are not included in the figure above for clarity.)

Between schedule assignments, and to handle sporadic traffic needs on otherwise inactive links, distributed data scheduling can be used. Distributed schedule control packets are transmitted during the unscheduled portions of the current schedule, and are used to quickly establish new, transient slot ranges for links. These transient slot ranges are valid only for the number of frames indicated in the distributed schedule establishment packets (based on the instantaneous traffic demand for the corresponding link), and any conflict with a new AirHood schedule when it becomes effective (at a scheduling epoch boundary) is resolved by terminating the conflicting slots established by the distributed schedule.

This approach to the channel access methods allows for the efficient transmission scheduling of mesh wireless routing networks in both a distributed manner with the arrival of brief traffic bursts, and for “persistent” flows lasting about a half second or more in a manner that provides latency and throughput assurances for the duration of the traffic flow.

Comparison with Point-to-Multipoint

The methods described in this section to synchronize the network and establish AirHood schedules have similarities with the methods specified in the draft 802.16 standard for point-to-multipoint networks. However, for multihop mesh networks, these 802.16 PMP methods required extensions to perform the AirHood scheduling across multiple hops from the AirHead, to allow for distributed scheduling between scheduling epochs, and to provide distributed scheduling methods for the network configuration and network entry packets.

On the other hand, the 802.11 MAC layer operates very differently using a prioritized contention-based protocol. Even in point-to-multipoint wireless LAN networks, this protocol does not provide reliable assurances for service-sensitive traffic under heavy traffic loads. However, the 802.11e task group (see [802.11e]) is currently working on extensions to this MAC protocol to substantially enhance its QoS support in point-to-multipoint WLAN networks.

4.3 Quality-of-Service Support for Multimedia Traffic

Section 4.2 described a MAC-layer approach, compliant with the draft 802.16 standard, for wireless routing networks capable of providing latency and throughput assurances for user traffic flows, while efficiently adapting to changing traffic demands. This section presents wireless routing quality-of-service (QoS) methods that utilize this MAC-layer to ensure that its assurances are applied to the end-to-end traffic flows that require them. (Note that given the MAC approach outlined in Section 4.2, the methods in this section are to a large extent applicable to any IP network product, particularly near the subscriber “edge.”)

These QoS methods involve the following primary components: 1. Regulation and classification of packets at the entry (or “ingress”) points to the wireless

routing network. 2. Prioritized scheduling, retransmissions, and intelligent packet dropping over each link in

the network according to the selected “class,” “drop precedence,” and “reliability” for each packet.

3. Appropriate operator provisioning of per-subscriber service levels.



This section will review the role that each of these plays in order to provide the Internet DiffServ-compliant QoS assurances needed for multimedia broadband service. (Also, see Internet references [RFC2597], [RFC2598], [RFC2474], and [RFC2475].)

Ingress Regulation and Classification

At the boundary of the wireless routing network, packets are classified according to the type of application and the level of service provided to a particular user. Figure 23 outlines the ingress packet processing. First, the packet is classified into one of four target “assured forwarding” classes (AF1 to AF4),18 and also marked with a (e.g., 2-bit) reliability value. As described in the next subsection, packets belonging to the AF1 class receive the most favorable per-hop treatment, and the reliability marking is used to determine how many retransmissions are attempted for each link. One other possible outcome of the classification process is the “Filter Drop” instruction, which results for packets that match the “firewall” rules configured into the classification lookup. These packets are simply dropped without further processing. The class and reliability classification can be done either by accepting the DiffServ Codepoint (DSCP) of the received packet’s Type-of-Service (TOS) field, or by classifying the packet according to a lookup based on the packet’s source and destination IP addresses, protocol, TCP or UDP port numbers, and TOS-field settings.19

Packet for forwarding

marked with {AF class,

reliability & drop precedence}

Regulate and mark drop

precedence

Police per-class

flows

Filter

Classify and mark AF class

& reliability Ingress Packet

Filter Drop Regulator Drop

Figure 23 -- Ingress Packet Classification and Regulation.

The next step polices the level of traffic in each AF class being injected into the network by this subscriber (or destined for a particular subscriber at the AirHead). Therefore, the traffic activity for each AF class is monitored, and whenever a subscriber’s average rate exceeds that subscriber’s limit for a particular class, AFx, then a given microflow that was assigned to that class is downgraded to class AFx+1. (In this policing phase, there is no limit on the level of AF4 traffic.) A microflow is defined as a particular {source address, destination address, IP protocol, source port, destination port} quintuplet. An entire microflow is downgraded, rather than, for example, selecting packets at random among multiple microflows to avoid packet reordering in the network (which can cause disruptions in end-to-end transport protocols or applications). Over time, as the measured traffic rates for each AF class permit, microflows can also be upgraded back to their target class.

Finally, the overall subscriber flows are compared against the peak, average, and guaranteed minimum flows provisioned for this subscriber. Traffic within the peak flow limit is accepted into the network, but marked with a “drop precedence” setting according to whether it is above the average limit (DP set to 2), below the average but above the guaranteed minimum (DP set

18 Actually, there may also be other classes such as the Expedited Forwarding (EF) and Best Effort (BE) classes; however, these are not included for clarity of this discussion. 19 The methods used to configure the data structures involved in this lookup are outside the scope of this document. However, these methods could combine statically configured entries to recognize certain port ranges for example, with dynamically updated entries based on an explicit flow establishment protocol or on detection of higher-layer flow setup packets as they are forwarded by the ingress routers.



to 1), or below the guaranteed minimum (DP set to 0). Traffic in excess of the provisioned peak flow limit for this subscriber is dropped.

Per-Hop Packet Handling

Following the above ingress operation, each packet traversing the wireless network is tagged with a service-handling triplet: {Assured Forwarding (AF) Class, Drop Precedence (DP), Reliability}. This information allows each wireless router along the packet’s path to provide service-specific handling to control congestion intelligently, to set link parameters according to the needed packet reliability, and to schedule packets according to their urgency. In particular:

�� Each wireless router maintains a set of queues for each link corresponding to the various traffic classes, AF1 to AF4. When a link becomes available for transmission of new packets, the packets are selected from the classes according to an algorithm which gives the highest priority to the AF1 queue, the next highest priority to the AF2 queue, and so on.20 As an example consequence, as long as the bandwidth scheduled for a given link is sufficient to transmit the packets that may arrive in the link’s AF1 queue during a frame period, then those packets tagged with AF1 will experience a single-frame delay, at most, across each hop (which is about 8 ms using the example described in Section 4.2).

�� When the link queues in a wireless router become too large (requiring many frames to empty them and threatening exhaustion of the router’s memory resources), then packets are dropped using a random early dropping algorithm weighted according to the Drop Precedence tags on the packets. Therefore, for example, when the network encounters congestion, packets belonging to subscribers that are above their provisioned average flow rates will be the first to be dropped.

�� Lastly, the packet’s reliability setting is used to indicate how many retransmissions should be attempted before the packet is discarded or returned to the routing layer. For example: “0” for a single transmission, “1” to attempt up to one retransmission, “2” to attempt up to three retransmissions, and “3” to attempt up to six retransmissions. The classifier’s selection of the reliability setting will depend both on the timeliness and the importance of the application data. For wireless networks, it is typically more efficient to retransmit packets at the link layer rather than rely on retransmissions using end-to-end protocols. However, for data that quickly becomes stale (e.g., voice), only a small number of transmission attempts are appropriate.

20 To ensure that no class is “starved” of bandwidth regardless of the traffic load, this packet selection algorithm could also include a “bandwidth” component whereby each queue is ensured of at least some percentage of the link bandwidth, given that the queue has packets to transmit.




802.11 “ad hoc” doesn’t mean multihop

A point of confusion in the wireless networking industry is due to the multiple uses of the phrase “ad hoc.” In some contexts, such as in the MANET (Mobile Ad hoc Networks) working group of the Internet Engineering Task Force (IETF), “ad hoc” is used to describe multihop mesh networks due to their distributed, self-configuring nature. However, “ad hoc” has also been used in the specification of the 802.11 MAC protocol to describe a channel access mode that can be used in “a network composed solely of stations within mutual communication range of each other.” In other words, the 802.11 “ad hoc” mode is designed for use in a wireless network where all of the nodes have a direct one-hop link to each other. However, because of the prevalence of 802.11 devices, it is tempting to use them, complete with their MAC protocol, in multihop mesh prototypes. In small networks, such prototypes are able to pass “proof-of-concept” demonstrations. However, as the size, density, or traffic load increases, these networks quickly encounter the limitations of this MAC protocol applied to an environment for which it wasn’t designed.

The 802.11 MAC operates in one of two primary modes: one mode is designed for the traditional point-to-multipoint WLAN architecture where the Access Point controls access to the channel; another “ad hoc” mode allows nodes to schedule transmissions in a distributed, contention-based manner using a request-to-send (RTS), clear-to-send (CTS) setup handshake before each packet burst. For small, mesh networks in which every node is a direct neighbor of either or both of the nodes of every link in the network, and relatively tame traffic conditions, the 802.11 ad hoc channel access mode can perform reasonably well because neighbor nodes that overhear the setup handshake will avoid making interfering transmissions for the duration of the packet burst, and because the carrier sensing is more likely to indicate a condition for which it is indeed better to remain silent. However, as the size, density, or traffic demands of the network increases, the performance of the 802.11 MAC degrades substantially due to issues such as: collisions by “hidden terminals,” particularly among the RTS and CTS packets; insufficient support for fair treatment of multiple traffic streams; and unwise decisions based on carrier sensing. In particular, the following problems surface:

�� Low throughput – The 802.11 MAC protocols are ill equipped to efficiently coordinate the transmissions of multiple nodes with packets to send in a multihop mesh network. One result is low end-to-end throughput for the user traffic. The problems encountered include collisions among simultaneous transmissions, and wasted airtime during which transmissions could have been made successfully.

�� High latency and latency variance – Because the 802.11 MAC protocol is contention-based, combined with other problems mentioned above for multihop mesh networks, it is unable to provide the latency guarantees needed for services like voice, or useful for improving TCP performance. Task Group E of the IEEE 802.11 standards group is working on extensions that should improve its quality of service performance in point-to-multipoint networks (see [802.11e]).

�� Extreme unfairness – The 802.11 MAC protocol has no guaranteed method for informing neighbor nodes of the traffic demands for the links to them. This leads to extreme unfairness in the servicing of multiple simultaneous traffic streams that flow through shared network nodes.

�� Unreliable link quality assessment – The 802.11 MAC protocol has no mechanism to reliably monitor the quality of the links among neighboring nodes. Therefore, higher layer protocols must rely on measures such as the success rate of periodic probe packets, which are themselves unreliable due to problems identified above. The consequences include: false indications of link failures (causing unneeded routing perturbations); delayed detection of new links; and overly coarse approximations of the link qualities resulting in poor decisions for the transmit power and/or modulation rates to be used for each link.

For further information on some of the performance problems with using the 802.11 MAC protocol for multihop mesh networks, see [Xu01] and [UCSC-MAC].


Network Service Provisioning

With the MAC-layer and QoS mechanisms described above, it becomes possible to provision the services of an AirHood according to subscriber service agreements and while providing the appropriate level of per-subscriber assurances for: 21

��Latency – for latency-sensitive traffic (e.g., some number of voice “lines”), and

��Bandwidth – specified as guaranteed, average and peak bandwidth levels.

For example, given an AirHood with 10 small business and 40 residential subscribers with a relatively spread-out distribution pattern for the distance from the AirHead (25%, 50%, 15%, 10% for 1-, 2-, 3-, and 4-hop residential subscribers, and 50%, 50% for 1- and 2-hop business subscribers; see Section 2), that all links are using the 802.11a 24-Mbps modulation rate or better, that the total network overhead is 25% (so effective link speeds are 18 Mbps), that 16-kbps encoding is used for the voice streams, that only a single channel is available to the AirHood, and assuming the worst case that only a single transmission at a time is possible within the AirHood, then the following represents a reasonable provisioning using a 10-to-1 statistical multiplexing ratio for the average bandwidth computation.

10 small businesses Number of assured voice calls 422 Guaranteed bandwidth 768 kbps23 Average bandwidth 3 Mbps Peak bandwidth 6 Mbps

40 residential subscribers Number of assured voice calls 2 Average bandwidth 1.5 Mbps Peak bandwidth 3 Mbps

As another example, an all-residential AirHood with 100 subscribers could be provisioned with the same level of service provided for the residential subscribers in the above table by using the same assumptions except for relaxing the statistical multiplexing ratio for the average bandwidth computation to 18-to-1.

21 This AirHood provisioning could be done by computing the capacity limits of the AirHood given its connectivity and link data rates, or by following conservative guidelines based on the size of the AirHood and typical link data rates in the target environment. 22 In this example, all voice calls will be classified as AF1 traffic (highest priority user traffic), and the number of voice calls with assured service is used to limit the amount of traffic classified as AF1 for a given subscriber. E.g., for a subscriber provisioned for up to four 16-kbps voice streams, the AF1 flow limit will be set to 64 kbps. 23 Because the network is fully adaptive to the up- and down-stream needs, bandwidth is provisioned as the total allowance for up- and down-stream traffic rates.



5. CONCLUSION

The purpose of this document is to present the fundamental core characteristics of wireless routing (mesh) networks with attention to the cost, coverage, scaling, and service benefits it provides for wireless broadband access networks. Example benefits include:

��Full coverage of residential neighborhoods with substantially lower system gain than required for point-to-multipoint architectures, translating directly to lower equipment costs, increased installation flexibility, etc. For example, to reach an 85% to 99% coverage target, 50-device wireless routing networks require 35 to 45 dB (respectively) lower system gain than is required for point-to-multipoint networks, using the scenario presented in Section 2.5 (cells or AirHoods 1-mile in radius, mean path loss exponent of 3, etc.).

��Natural scaling to large, dense networks, and the reliable use of unlicensed frequency bands, which are enabled by a favorable relationship between the propagation characteristics of the active links in the network and the paths followed by the interference, versus point-to-multipoint networks which must cope with an unfavorable relationship between these signals (see Sections 3.1 and 3.2).

��Automatic selection of routing links combined with adaptive setting of the modulation rate used for each link to actually increase the end-to-end bandwidth of subscriber traffic streams by routing over multiple hops, rather than attempting to use the longer, possibly more obstructed, direct links (see Section 4.1).

��The automatic use of alternate paths when links fail, which substantially reduces the need for operator “repair” visits and reduces the fading margin needed for the system (again translating to lower equipment costs, etc.). Specifically, approximately 6 dB of decreased shadow fading margin is required compared with point-to-multipoint (see Section 2.4).

Of course, complete wireless router products require a full complement of other capabilities to address the needs both of an infrastructure router, and as an access device for the end subscriber. These requirements can include:

�� Full Internet Protocol support to permit the wireless mesh networks to serve as seamless extensions of the Internet;

�� Home gateway functions (such as the Internet’s DHCP and NAT protocols) to ease the connection and permit self-configuration of the home networking devices;

�� An efficient, Internet-compatible routing protocol able to integrate link quality and link modulation rate into routing decisions;

�� Network synchronization, link quality management and scheduling algorithm support for the MAC-layer framework described in Section 4.2; and

�� Support for network management, subscriber provisioning, network security, and remote, “over-the-air” firmware upgrades.

6. ACKNOWLEDGMENTS

This paper benefited greatly by the helpful review and discussions with Darren Lancaster, Greg Desbrisay, Andy Kelm, JJ Garcia-Luna-Aceves, and Nico VanWaes, and also by editorial help from Jo Albers and graphical contributions from Darci Hermann.



A. APPENDIX A – SIGNAL-TO-INTERFERENCE CAPACITY SCALING DERIVATION24

A.1 Local Neighborhood

1. The network deployment illustrated in Figure 16 is used for this analysis.

2. A node’s local neighborhood is defined as the radius (Rn) required for the node to reach its 8 nearest neighbors (RF-wise). A node’s “local region” of radius (Rl) is then computed as N (e.g., 2 to 5) times the neighborhood radius. For a wireless router network, Rl is roughly 1 to 1½ times the distance between AirHoods that are using the same channel. For nodes scattered randomly over a plane at density D nodes/km2, the average radius Rl equals:

metersDR

DRNRR

metersD

NR

n

nnl

l

�

�

�

10003

9

3000

2

��

��

��

.

Rn

i Raj Rl

3. Transmission scheduling and channel assignment are coordinated such that there will be only a single transmission (that from node i to node j) within radius lR around receiver j.

4. Nodes use adaptive power control to ensure that the signal arrives at the intended receiver at some target level, TdBm.

A.2 Receive Power of Desired Signal

1. The receive power (P) into the antenna port of a receiving node from an arbitrary transmitting node can be approximated with the following formula where y is the path loss exponent, r is the distance between the nodes (in meters), X is the transmit power used, Ax is the transmitter antenna gain minus connector losses, Ar is the receive antenna gain minus connector losses, and C accounts for the reference far-field path loss.

)(log10 10 ryCAAXP rxdBm ��

2. However, local path-loss characteristics are highly variable, dependent mainly on the presence and type of any obstructions in the path. The selection of links chosen by a mesh network to use for routing packets is not random; they are the best links available between nearby nodes. Therefore, estimating the path loss for these links requires the use of a significantly lower average path loss exponent (x).

24 This analysis is similar to the one performed by T. Shepard in [Shepard95]. Some key differences are that Shepard used only a single path-loss exponent for both the signal and the interference, and assumed multi-transceiver radios with a high spreading gain modulation which simplifies channel assignment and transmission scheduling considerations.



3. Given that the receive power at the intended receiver is TdBm (ensured by adapting the emitted power at the transmitter appropriately), the propagation formula between transmitting node i and the intended receiver j is given by:

)(log10)( 10 rxCAArXT rxdBm ��

4. Using the average transmit power X, associated link distance RT (derived below), and solving for C:

)(log10 10 TdBmrx RxTAAXC ��

A.3 Average Transmit Power and Associated Link Distance

1. The transmit power for any link can be derived from above:

xCAAT

mw

rxCAAT

mw

rxdBmdBm

rrX

rX

rxCAATrX

rxdBm

rxdBm

10

10)(log10

10

10)(

10)(

)(log10)(10

��

��

�

�

��

2. Assuming an equal likelihood of transmitting to each of a node’s routing neighbors, then the average transmit power (X), and associated link distance (RT), can be computed by integrating the transmit power required to reach each of the neighbors up to this average distance, and setting that to equal the same integration from that distance to the edge of the nodes neighborhood area, at radius Rn.

DR

orRR

RRR

xr

xr

drrdrr

drrrdrrr

drrrXDdrrrXD

xT

nx

T

TnT

R

R

xRx

R

R

xR x

R

R

xCAAT

R xCAAT

R

R

R

xxx

n

T

T

n

T

T

n

T

rxdBmT

rxdBm

n

T

T

�

��

30002

,2

22

1010

)(2)(2

)2/(1

)2/(1

2

0

2

1

0

1

100

10

0

222

��

�

��

�

�

�

�

�

�

��

��

��

��

��

��

��

��

��



3. The average transmit power is thus:

� �

)(log10

,)(log102log2

10210

210

10

1010

)2/(10

)2/(110

TrxdBmdBm

nrxdBmdBm

xn

xxCAAT

mw

xn

xCAAT

mw

RxCAATX

orRxxxCAATX

RX

RXrxdBm

rxdBm

��

�

�

��

�

�

��

��

��

��

A.4 Receive Interference Power

1. The average interference power P received at node j from an arbitrary interfering transmitter at distance r is:

)(log10)(log10)()(log10

1010

10

ryRxTPRrryCAAXP

TdBmdBm

lrxdBm

��

��

2. Converting to mWatts:

y

xT

T

mW

ryRxT

mW

ryRxT

mW

rRP

P

P

dBm

TdBm

TdBm

��

��

�

�

��

10

10)(log10

10)(log10

10

10)(log10)(log10

10

101010

101010

1010

3. Outside of the receiver’s local region, nodes will be using the same channel used by this AirHood with a 25% probability due to the 4-channel architecture used for this analysis. So, given that the density of nodes on the same channel is D/4 [or (D/4)x10-6) nodes/sq-meter] and given an average transmit duty cycle a for each node, then the total interference power PT received by node j from all interfering transmitters (from Rl out to the radio horizon Rh) plus the thermal noise floor BdBm is:

r j

Rl

��

��

��

��

��

��

��

��

��

��

��

��

��

�

��

�

2261010

261010

161010

61010

1110)2(2

1010

)2(12

1041010

12104

1010

2104

1010

yh

yl

xT

TBTmW

R

Ry

xT

TBTmW

R

R yxT

TBTmW

R

R y

xT

TBTmW

RRR

yaDP

ryDaRP

drr

DaRP

drrDarRP

dBmdBm

h

l

dBmdBm

h

l

dBmdBm

h

l

dBmdBm

�

�

�

�

dr



4. Converting back to dBm:

��

�

�

��

�

��

��

��

��

�� 2261010

1011

10)2(21010log10 y

hyl

xT

TBTdBm RR

RyaDP

dBmdBm� .

A.5 Receive Signal-to-Interference Level

The receive signal-to-interference level is therefore given by:

DRorRR

horizonvisiblehorizonradioRDNRwhere

RRR

yaDTSIR

PTSIR

xTn

xT

h

l

yh

yl

xT

TB

dBmdBm

TdBmdBmdBm

dBmdBm

�

�

�

300022

3/4~/3000

1110)2(2

1010log10

)2/(1)2/(1

2261010

10

��

�

��

��

�

�

��

�

��

��

��

��

�

��

��



REFERENCES

[802.11] IEEE, “Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) specifications.” IEEE Standard 802.11, June, 1999.

[802.11a] IEEE 802.11, Amendment 1, “High-speed Physical Layer (PHY) in the 5 GHz band,” IEEE Standard 802.11a, June, 1999.

[802.11e] Task Group E of the IEEE 802.11 standards group, web address: http://grouper.ieee.org/groups/802/11 .

[Beyer90] D.A. Beyer, “Accomplishments of the DARPA Survivable Adaptive Networks (SURAN) Program,” Proceedings of MILCOM Conference (Monterey, California: 1990).

[Beyer99] D.A. Beyer, M.D. Vestrich, and J.J. Garcia-Luna-Aceves, “The Rooftop Community Network: Free, High-Speed Network Access for Communities,” chapter in “The First 100 Feet: Options for Internet and Broadband Access,” The MIT Press, Cambridge, Massachusetts, 1999, ISBN 0-262-58160-4.

[Garcia-Luna97] J.J. Garcia-Luna-Aceves, C.L. Fullmer, E. Madruga, D.A. Beyer and T. Frivold, "Wireless Internet Gateways (WINGS)", Proc. IEEE MILCOM'97, Monterey, California, November 2-5, 1997.

[Jubin87] J. Jubin and J. Tornow, “The DARPA Packet Radio Network Protocols,” Proceedings of the IEEE (January, 1987).

[Kahn78] R.E. Kahn, S.A. Gronemeyer et al, “Advances in Packet Radio Technology,” Proceedings of the IEEE (November, 1978).

[Rappaport96] T.S. Rappaport, “Wireless Communications: Principles & Practice,” Prentice Hall, Inc., Upper Saddle River, NJ, 1996, ISBN 0-13-375536-3.

[Rappaport98] T.S. Rappaport, “RF Propagation and System Design Techniques for Broadband Wireless Applications from 5 to 40 GHz,” 1998 Bellcore Horizons Workshop, available via http://www.mprg.ee.vt.edu.

[RFC2597], [RFC2598], [RFC2474], and [RFC2475] Internet “Request for Comments” (RFC) documents, available at http://www.ietf.org/rfc.html .

[Seidel91] S.Y. Seidel, T.S. Rappaport, S. Jain, M. Lord, and R. Singh, “Path Loss, Scattering and Multipath Delay Statistics in Four European Cities for Digital Cellular and Microcellular Radiotelephone,” IEEE Transactions on Vehicular Technology, Vol. 40, No. 4, pp. 721-730, November, 1991.

[Shepard95] T.J. Shepard, “Decentralized Channel Management in Scaleable Multihop Spread-Spectrum Packet Radio Networks” (doctorial thesis, Massachusetts Institute of Technology, MIT/LCS/TR-670, 1995).

[UCSC-MAC] “Media Access Control” section of the Computer Communications Research Group’s web site at the University of California, Santa Cruz, maintained by Prof. J.J. Garcia-Luna-Aceves: http://www.cse.ucsc.edu/research/ccrg .

[Xu01] Xu, S, Tarek, S, “Does IEEE 802.11 MAC Protocol Work Well in Multi-hop Wireless Ad Hoc Networks?” IEEE Communications, June 2001.


http://grouper.ieee.org/groups/802/11

http://www.mprg.ee.vt.edu/

http://www.ietf.org/rfc.html

http://www.cse.ucsc.edu/research/ccrg

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