3g Radio Planning

RADIO PLANNING OF THIRD GENERATION NETWORKS IN URBAN AREAS P R Gould

Multiple Access Communications Limited, UK

INTRODUCTION Third generation (3G) radio networks based on the code division multiple access technology (CDMA) are being deployed in many countries throughout the world. Although commercial cellular networks based on the CDMA technology have been in operation since 1995, 3G networks have one major difference compared with their second generation (2G) predecessors, namely the range of services that they will support. GSM is an example 2G technology and in the early systems the maximum user data rate was around 12 kbit/s and this limited the services that could be offered to speech, low rate data and short messages (SMS). GSM has since evolved into a �2½G� technology, with the ability to offer instantaneous data rates of over 150 kbit/s through the general packet radio service (GPRS). However, 3G systems are designed to support data rates of up to 2 Mbit/s, which means that they will support a much wider range of services. It also means that the task of designing and planning 3G networks will become far more demanding because of the wide variation in the type and mix of traffic that will be offered to the 3G systems. In this paper we highlight and discuss some of the challenges that face 3G radio network design engineers as they plan and deploy their networks in urban areas, where the problems are likely to be at their most acute. CELL BREATHING One of the key features of a CDMA system is that all subscriber terminals within the network can operate on the same carrier frequency at the same time. This results in high levels of co-channel interference between the different users. Signal spreading and despreading techniques are used to suppress this interference so that user data can be recovered in the presence of this co-channel interference. The level of suppression that can be achieved is termed the processing gain, Gp. This parameter is commonly considered to be equal to the CDMA chip rate, W, divided by the user data rate, Rb, although other definitions exist. To successfully demodulate the transmitted user data

bits, the ratio of the energy per information bit, Eb, to the power spectral density (PSD) of the interference, I0, and the thermal noise, N0 must be greater than a particular threshold. This threshold is a complex parameter and its value will depend on a range of factors, including the characteristics of the radio channel, the type and power of the channel coding used and the performance of the receiver. The value of this threshold is usually estimated through the use of complex link level computer simulations. We can understand a great deal about the performance of a CDMA network by developing a simple expression for this ratio, which we refer to as Eb/I0, in terms of a number of other system parameters and variables, as follows [1].

WSNfN

RS

IE bb

)1()1(0

0 −++=

α (1)

where S is the power that must be received from each mobile at the base station, Rb is the user data rate, N is the number of active users within a particular radio cell, α is the source activity factor (or the duty cycle at which the user data are generated), W is the chip rate of the CDMA signal and f is the ratio of intercell-to-intracell interference power (the so-called f-factor). We note that the expression is based on the up-link path and it assumes that the system exhibits perfect power control (ie, all mobile transmissions are received at the base station at exactly the same power). Solving this equation for S, the required received power of each mobile at the base station, gives

)1)(1(

0

0 0

−+⋅−

⋅=

NfRW

WNRS

bIE

bIE

b

b

α . (2)

This expression can be used to demonstrate the dependency of S on the user data rate, Rb, the source activity factor, α, and the number of users, N. If we assume that Eb/I0=7 dB, α=0.5, f=0.55 and W=3.84Mchip/s, then we can examine the effect that the data rate, Rb, has on the required received power as we increase the number of active users in each cell. (We note that this is an oversimplification, since Eb/I0 can vary dramatically with the user data rate.) The results are shown in Figure 1 where the relationship between the required received power and the number of users is plotted for user data rates of 9.6, 64, 144 and 384 kb/s. We can also examine the impact of changes in the source activity for each user by setting Rb to a constant

Peter R Gould

3G Mobile Communications Technologies, 8 - 10 May 2002, Conference Publication No. 489 © IEE 2002

value (in our example 9.6kb/s is used) and plotting the relationship between N and S for different source activity values. The results are shown in Figure 2 for source activity values of 0.2, 0.3, 0.5, 0.7 and 1.

-125

-120

-115

-110

-105

-100

-95

0 10 20 30 40 50 60 70 80 90 100 110N - Number of Users Per Cell

9.6 kb/s64 kb/s144 kb/s384 kb/s

S - R

equi

red

Up-

link

Rec

eive

d Po

wer

(dBm

)

Figure 1 The impact of user data rate on required

received signal strength.

-130

-125

-120

-115

-110

-105

-100

0 10 20 30 40 50 60 70 80 90 100 110N - Number of Users Per Cell

α=0.2α=0.3α=0.5α=0.7α=1

S - R

equi

red

Up-

link

Rec

eive

d Po

wer

(dBm

)

Figure 2 The impact of source activity on required

received signal strength. These plots show the effect that the number of users, the user data rate and the source activity have on the required received power. If we consider that a mobile will have a fixed maximum transmit power, then changing the required received power that a mobile must deliver to the base station has the same effect as changing the maximum pathloss that can be tolerated between the mobile and the base station. In practical terms this means that the effective range of a base station, or the cell size, will vary depending on the number of active users within a cell, the data rates they are using and their source activity. This variation in cell size is commonly known as �cell breathing� and it is a feature of networks based on the CDMA technology. Instead of considering separately the different network variables (eg, user data rate, number of users per cell), we can combine these into a single value known as the cell load, L. This load is usually expressed as a percentage of the system pole capacity, which is the

maximum theoretical load that can be supported by a cell within the system if all of the terminals could transmit at an infinitely high power level. In Figure 3 we show the impact of cell load on the size of a cell for a speech service and a 144kb/s data service. This shows that, for a given cell load, the effective cell radius will be different for each service. This must be considered in the planning process, eg, by examining the coverage offered to each service separately.

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

0% 20% 40% 60% 80% 100%

L - Cell Loading

R -

Cel

l Rad

ius

(km

)

Speech144 kb/s

Figure 3 The impact of cell loading (L) on cell

radius (R). THE IMPORTANCE OF GOOD TRAFFIC MODELS The preceding discussion and examples show that, in designing a CDMA system, it is important to have a good idea of how the subscribers are likely to use the services to which they have access, ie, it is important to have good teletraffic models for each service. This is particularly true in urban areas where the highest levels of network loading are likely to be experienced and the full range of services is likely to be used. Based on its experience with first and second generation cellular networks, the industry has developed a good understanding of how to model speech traffic and the manner in which this is affected by factors such as call charging rates. However, data models are less well developed. Although packet data services have been around for some time (eg, cellular digital packet data), the GPRS service is still in its infancy, as far as commercial deployment is concerned, and it may take some time for widely accepted GPRS traffic models to emerge. The 3G systems are likely to support a much wider range of services including web browsing, video and audio clip download and video-conferencing. It is important to understand how the subscribers are likely to use these services and what quality levels will be acceptable for the different services (eg, what bit error rate can be tolerated or what delay is acceptable).

In some cases, it may be possible to draw on experience from non-mobile environments to develop traffic models for 3G networks. For example, an analysis of fixed network internet traffic could be used as a basis to derive traffic models for web browsing sessions. However, it is also important to realise that there will be significant differences when these services are offered in a 3G network environment. As an example, we can see that fixed internet access is moving towards a flat-fee (or unmetered) billing structure and this is likely to have a direct impact on the manner in which this service is used. On the other hand, we see that the GPRS service is commonly being billed on a �per megabyte� basis and this is likely to result in the subscriber acting in a different way when they access the internet via this medium. It is also likely that subscribers will want access to different types of information when on the move, compared to when they have access to a fixed connection, and this could lead to a significant difference in the traffic models in a mobile environment. In a radio planning context, the main interest in traffic modelling is as a means to determine the load that each subscriber is likely to exert on the network. Based on this information it is possible to ensure that the network is correctly dimensioned to provide all subscribers with high quality access to the services they wish to use. NETWORK LOADING Determining the network load generated by a particular user is a complex process since it depends on a range of different factors. We have already seen that data rate and source activity have a significant impact on this parameter. The channel configuration at the base station could also have an impact on the network loading. For example, in the UTRA system it is possible to carry packet data on both dedicated and common channels. The amount of load placed on a particular base station by an individual user will depend on the channel configuration used to carry that user�s traffic as well as the characteristics of the traffic itself. The load will also be governed by a mobile�s position within the network. For example, if a mobile is close to its base station it will transmit at a low power and thereby cause less interference into adjacent base station receivers. On the other hand, a mobile that is some distance from its serving cell will be required to transmit at a much higher power and, as a result, it will cause a higher degree of interference to surrounding cells. This demonstrates that the f-factor is dependent on the distribution of mobiles within the network as well as the relative propagation conditions between mobiles and their serving and neighbouring base stations. It also demonstrates that in addition to having good traffic and network loading models, it is also important to have good user density information, ie, a good model for where the users are likely to be at different times of the day.

3G NETWORK PLANNING TOOLS Having good traffic and user density models available is of little benefit if they cannot be pulled together to build up an accurate picture of the network performance. Therefore, 3G network planning tools must be able to combine information about the network configuration (eg, base station positions, transmitted powers, carrier allocations) with information about the position of the users and the traffic that they are likely to generate in order to build a realistic picture of the network in terms of its coverage and the quality of service it is likely to offer. It should also be remembered that accurate propagation models are as important a requirement of 3G planning tools, as they are for 2G planning tools. Most 3G planning tools are based on some form of Monte Carlo simulation, although analytical approaches exist [2]. In the simulation, users are scattered throughout the network based on a desired (ie, forecast) traffic distribution, and then these users are allowed to initiate calls based on a chosen service. As each user is introduced, the interference levels are calculated within the network and the power level of each user is then adjusted to ensure that it is set at an appropriate value. Two distinct types of simulation-based 3G radio planning tool exist, namely, the static and the dynamic simulator. In the case of the static simulator [3,4], the users do not move and so the tool builds a picture of the network for a particular distribution of the users. This is usually termed a �snapshot�, since it represents a view of the network with one particular user configuration. In order to build a better view of the �average� network performance with a particular user distribution the static planning tools generate many snapshots, each with a different random distribution of the users, and then combine these to form a composite view of the network performance. In the case of dynamic simulators, the users are allowed to move around the network and, as far as possible, behave like real users, eg, they make and receive calls, hand over between base stations and change speed and direction. The quality of service experienced by each user can then be collected to provide an indication of the network performance in each area. If it were possible to supply both the static and dynamic planning tools with accurate information about the network and the characteristics of the users, then the dynamic tool is likely to provide a better view of the performance of the network. However, the dynamic simulator is more complex and will require more computing power and, if the characteristics of the users� motion are not modelled correctly, then it is unlikely to provide a significant performance gain when compared with a static tool.

PLANNING URBAN 3G NETWORKS To this point we have considered the issues that are common to all parts of a 3G network. We now concentrate on those issues that are specific to 3G network design in urban areas. One of the main problems associated with planning networks in cities is that these urban areas are likely to contain the most complex cell structures, eg, macrocells and microcells. Placing large cells next to small cells in a CDMA network raises some significant issues if the cells are to be operated on the same frequency [5]. In GSM networks, macrocells and microcells which cover the same or similar geographic areas will always operate on different carrier frequencies. This allows traffic to be forced onto the more efficient microcells in any areas where they can provide service, regardless of the coverage offered by the macrocells at that point. In a CDMA network that uses a common frequency for the macrocells and the microcells, the mobile should always communicate with the base station that requires the lowest transmit power. If all base stations experience the same loading, then this means that the mobile must communicate with the base station that has the lowest pathloss. Therefore, it is not possible to force traffic to a particular layer of the network. This makes the decision to use microcells in a 3G network significantly different from the decision faced by a GSM network designer. To demonstrate this point we consider the diagram in Figure 4, which shows the relationship between pathloss and distance for three microcellular base stations. If these microcells operate in isolation, then their service area will be defined by the area over which they offer the lowest pathloss to the user (assuming equal loading) and the maximum allowable pathloss that is defined by the link budget at the extremities of the coverage. These coverage areas are highlighted in the figure.

Distance

Path

loss

Microcell 1Microcell 2Microcell 3

Maximum Allowable Pathloss

Microcell 1 Coverage

Area


Area


Area

Figure 4 The coverage area of microcells in a

microcell only network. If we introduce an oversailing macrocell into this network, as shown in Figure 5, that uses the same carrier frequency then we can see that the coverage area of the three microcells is changed. Microcell 1 is the closest to the macrocell site (located at the left hand edge of the

figure) and its coverage is significantly reduced because it becomes dominated by the macrocell. Figure 5 also shows that Microcell 1 and Microcell 2 no longer provide contiguous coverage and the mobile must hand over to the macrocell as it moves between these microcells. We can also see that the coverage of Microcell 3 is less affected by the introduction of the macrocell because it is some distance from the macrocell site.

Distance Pa

thlo

ss

MacrocellMicrocell 1Microcell 2Microcell 3



Area


Area


Area

Figure 5 The coverage area of microcells with an

oversailing macrocell. One way to address this issue and cause the microcells to serve over a larger area is to artificially increase the pathloss between the mobile and the microcell receiver, eg, by inserting an attenuator into the receiver path. However, this approach is only suitable in specific applications since it will cause the mobiles to transmit at a higher power, which will decrease the capacity of the system. Alternatively, the macrocellular and microcellular base stations could be operated on different carrier frequencies, which will allow the more efficient microcells to serve over a much larger area. However, this approach is not without its problems. Inter-frequency Handover and Compressed Mode When macrocells and microcells share a common carrier frequency, the mobile can operate in soft handover between these two different types of cell and benefit from the associated performance gains. If, on the other hand, the macrocells and microcells are operated on different carrier frequencies, then any switch between the different network layers will involve an inter-frequency handover, which means that the benefits of soft handover are lost. Before performing an inter-frequency handover, the mobile must make a series of measurements on the target cell and this requires the use of down-link (and possibly up-link) compressed mode. In compressed mode, the user data rate is increased to allow breaks in the CDMA transmissions to occur, within which the mobile is able to take measurements on the carrier frequency of the target cell. Studies have shown [6,7]

that compressed mode can increase the overall mobile transmitted power by between 2 and 4 dB, which will have a significant impact on the network coverage and capacity. Adjacent Channel Interference In networks in which the macrocells and microcells operate on different frequencies it is possible for a mobile to come close to one base station whilst communicating with a more distant base station. If the two base stations operate on adjacent carrier frequencies (or even second adjacent carriers), then this could give rise to adjacent channel interference problems. To demonstrate this issue we return to Figure 5. We can see that if the macrocells and microcells operate on different frequencies, then the service area of Microcell 1 returns to the level shown in Figure 4 and a mobile can be connected to Microcell 1 even though it is very close to the macrocell. However, Figure 5 shows that the pathloss to Microcell 1 is much greater than the pathloss to the macrocell when the mobile is close to the macrocell (ie, towards the left hand side of the figure). Therefore, close to the macrocell the mobile that is connected to Microcell 1 will be transmitting at a much greater power than mobiles in the same area that are connected to the macrocell. This difference in received power at the macrocell could result in adjacent channel interference problems, which must be considered when planning the 3G network. Macrocell Capacity Limitations Dedicating carrier frequencies for microcell-only use could have a dramatic impact on the capacity of the macrocell layer. For example, a network operator with only two frequency division duplex (FDD) carrier frequencies must sacrifice more than half of the capacity of the macrocell layer to provide a dedicated microcell carrier frequency. This means that the decision to frequency partition the macrocells and microcells is complex and it will depend on the specific cell site deployment on the two layers, as well as the traffic distribution within the network and the extent to which different services are used. DEDICATED AND SHARED CARRIERS One way of compromising between these two extreme frequency assignment positions is to have some carriers that are shared between the different layers and some carriers that are dedicated to either the microcells or the macrocells. This provides the flexibility to force traffic to a particular layer if required, but it also allows the benefits of soft handover to be enjoyed as the mobile moves between layers. Once again, the approach is not without its complications. For example, the coverage area of a shared and non-shared carrier could be different, even though they are associated with the same

cell site. How should this be handled in the network radio resource allocation algorithms? Should traffic be balanced between all carriers or should some carriers be preferentially loaded? CONCLUSIONS In this paper we have examined some of the key issues facing radio network design engineers as they set about planning third generation networks in urban areas. We have shown the importance of having good models for traffic and user distribution in radio network planning and we have also discussed the requirements of 3G planning tools. We have highlighted some of the challenges associated with using multi-tier cellular structures (eg, macrocells and microcells) and discussed some of the factors that will influence design decisions. At present, most of the focus of 3G network operators is understandably on network rollout. However, if 3G becomes the runaway success that we all hope it will be, then the problems of designing high capacity, high quality urban networks are likely to present themselves sooner rather than later. Therefore, the issues presented in this paper need to be considered now and network operators should be working with their vendors to ensure that vendor technology roadmaps contain the necessary features to address these issues as and when they occur. REFERENCES 1 Steele R, Lee C-C, Gould P, 2001, GSM, cdmaOne and 3G Systems, John Wiley & Sons, Chichester.

2 Nawrocki M J and Wieckowski T W, 2001, �Modelling Aspects and Output Results of WCDMA Network Simulation Software�, Advanced Technologies, Applications and Market Strategies for 3G Conference, Krakow, Poland, June 17-20.

3 Beddoes T and Thompson D, 2001, �Planning Ideas for 3G Networks�, Land Mobile Magazine, May, pp 23-25.

4 Dehghan S, Lister D, Owen R and Jones P, 2000, �W-CDMA capacity planning issues�, IEE Electronics and Comms Journ, Vol 12, No 3, June, pp 101-118.

5 Shapira J, 1994 �Microcell Engineering in CDMA Cellular Networks�, IEE Trans Veh Tech, Vol 43, No 4, pp 817-825.

6 Holma H, Toskala A, 2000, W-CDMA for UMTS - Radio Access for Third Generation Mobile Communications, John Wiley & Sons Ltd, Chichester.

7 Toskala A, Lehtinen O, and Kinnunen P, 1999, �UTRA GSM Handover from Physical Layer Perspective�, Proceedings of the ACTS Summit 1999, Sorrento, Italy, pp 57-61.

Radio Planning of 3G Networks in Urban Areas

3G20029 May 2002

Peter GouldConsulting Services Director

Multiple Access Communications Limited

Contents

� Hierarchical Networks� Multiple Layers in 3G Networks� Frequency Partitioning� Call Admission Control� Planning Example� Conclusions

Hierarchical Networks

� In current second generation networks, multiple cellular layers can be used to satisfy the requirements of the users.� Indoor picocells to provide high quality in-

building coverage.� Street microcells to provide high capacity.� Oversailing macrocells to provide wide

area coverage.



� These networks work most efficiently if, in general, the traffic is forced to the smallest available cell.

� Some exceptions exist, eg, fast moving mobiles.

� Different network layers will use different carrier frequencies in the same area.

Multiple Layers in 3G Networks

� In 3G UTRA networks, all Node Bs can use the same carrier frequency.

� To ensure the most efficient use of the radio resources, the user equipment (UE) should use the Node B that requires the lowest UE and Node B transmitted powers.


� If a mobile connects to a Node B that requires a higher transmitted power, the interference within the network will be increased.

� This will lower the overall capacity of the network and/or the network coverage footprint will shrink.

� Therefore, it makes less sense to force UEs to �sub-optimum� cells.


� The transmitted power is influenced by � the pathloss between the Node B and the

UE� the interference (loading) at the Node B

and the UE.� We can examine this issue in a

uniformly loaded network.

Microcell Only Network

Distance

Path

loss

Microcell 1Microcell 2Microcell 3



Area


Area


Area

(or t

x po

wer

)

Multiple Layer Network

Distance

Path

loss

MacrocellMicrocell 1Microcell 2Microcell 3



Area


Area


Area

(or t

x po

wer

)

Frequency Partitioning

� If an operator has a number of carrier frequencies available, different carriers can be used in different layers.

� This allows traffic to be forced to particular layers.

� However, it raises a number of other areas of concern.

Soft vs Hard Handover

� In a single frequency network, handover between all the network layers can be soft.

� In a multi-frequency network, hard handovers are required.

� The use of hard handovers has a number of implications.

Soft Handover Gain

� The macro-diversity provided by soft handover results in link budget gains.

� This leads to lower transmitted powers� higher network capacity� better network coverage

� These gains are no longer available between layers if hard handovers are used.

Compressed Mode

� In CDMA systems, the UE will normally transmit and receive continuously during a call.

� In a single receiver UE, this provides no time to make measurements on other carrier frequencies.

� In UTRA, compressed mode is used to allow inter-frequency measurements to be made.

Compressed ModeTr

ansm

itted

Pow

er

One Frame(10ms) Transmission

Gap

User Data Rate Increased

Compressed Mode

� The use of compressed mode results in a performance degradation for the following reasons� fast power control loop cannot be updated

during compressed mode� interleaving gain is decreased.

� If all UEs are in compressed mode, capacity loss could be around 20%*.

*Holma H and A Toskala, �WCDMA for UMTS� Wiley, 2000

Compressed Mode

� Compressed mode can also decrease the coverage of a Node B.

� This shows that careful planning is required to minimise the use of compressed mode in multi-carrier networks.

� This is particularly difficult in multi-layer networks.

Adjacent Channel Interference

� Multi-frequency networks can lead to UEs in the same area communicating with different Node Bs.

� This results in different transmitted powers at UEs, which can cause adjacent channel interference problems.

Adjacent Channel Interference

High Pathloss

High Tx Power

Low Tx Power

Low Pathloss

Adjacent Channel

Interference

Call Admission Control

� Call admission control is a challenging area, particularly in multi-layer networks.

� Several call admission control schemes are available, each with its own characteristics.

� Different schemes will have different effects on the network quality.

Call Admission Control

� Some schemes aim to maximise Node B throughput.

� Other schemes aim to maintain a minimum level of coverage.

� The call admission control scheme must be considered in the planning process.

Planning Example

� Urban network with rooftop macrocells and street microcells.

� Call admission control scheme limits noise rise at Node B.

� The admission control scheme also includes a predictive component (ie, it predicts what will happen if the call is admitted).

Planning Example

Planning Example

Planning Example

Potential Solutions

� Preserve a minimum coupling loss between UEs and Microcellular Node Bs.

� In multi-frequency network, use macrocell when UE is close to microcellular Node B � potential adjacent channel interference problems.

Conclusions

� There are many design choices associated with planning 3G networks in urban areas.

� The equipment performance (eg, call admission control) must be considered in the planning process.

� Operators and vendors must work closely to ensure that the networks are modelled correctly.

Documents

3g Radio Planning