DYNAMIC SPECTRUM ACCESS IN DTV WHITESPACES: DESIGN RULES, ARCHITECTURE AND ALGORITHMS

Supratim Deb, Vikram Srinivasan, (Bell Labs India)

Ritesh Maheshwari (State University of NY)

MobiCOM 2009

Presenter: Han-Tien Chang

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Outline2

Introduction Related Work Background Design Rules System Architecture and Spectrum

Allocation Problem Algorithms (for spectrum allocation) Simulations Conclusion and Comments

Introduction3

The newly freed up spectrum (from analog to digital) along with other slices of unused spectrum in the 50-700 MHz

(channels 2-51) television band is known as DTV white-space (DTV-WS).

In November 2008, in FCC’s second report and order [4], The FCC ruled that the digital TV whitespaces be used for

unlicensed access by fixed and portable devices Fixed devices (e.g., IEEE 802.22 base stations) are used for providing last

mile internet access in underserved areas Portable devices can be used to provide short range wireless connectivity

for Internet access (e.g., Wi-Fi like access points) Indeed, unlicensed access in DTV-WS can not only decrease

congestion on the 2.4 GHz ISM band, but also provide much better data rates and coverage due to superior propagation properties of the spectrum.

[4] FCC 08-260. Second Rep. and Order and Memorandum Opinion and Order. 2008.

Introduction (cont’d)4

In this paper, Perform a comprehensive design exercise of a

system for Wi-Fi like unlicensed access in the DTV whitespaces.

Design a system and architecture where a central controller can be responsible for

performing efficient spectrum allocation based on access point demands

The Goal develop a thorough understanding of the effect of

frequency dependent radio propagation and out of and emissions on system design

derive an FCC compliant multi-radio based architecture based on this understanding

design algorithms to efficiently allocate variable spectrum to access points based on their demand

Related Work5

The KNOWS [29] project at Microsoft has developed a hardware prototype, a carrier sense MAC and algorithms for dynamic spectrum access. doesn’t consider the propagation characteristics, co-

channel interference and out-of-band emissions In [21], the authors consider a problem very similar

in nature to ours issues of out-of-band emissions and frequency

dependent interference graphs do not come into play In [7], the authors design and implement a Wi-Fi-

like system with Wi-Fi components that operates over UHF whitespaces also demonstrates how spectrum fragmentation and

spatial variation of spectrum have implication on network design.

[29] Y. Yuan, P. Bahl, R. Chandra, P. A. Chou, J. I. Ferrell, T. Moscibroda, S. Narlanka, and Y. Wu. KNOWS: Kognitiv Networking Over White Spaces. In IEEE DySPAN 2007.[21] T. Moscibroda, R. Chandra, Y. Wu, S. Sengupta, P. Bahl, and Y. Yuan. Load-Aware Spectrum Distribution in Wireless LANs. In IEEE ICNP 2008.[7] P. Bahl, R. Chandra, , T. Moscibroda, R. Murty, and M. Welsh. White Space Networking with Wi-Fi like Connectivity. In ACM SIGCOMM 2009.

Background6

Radio Propagation Path loss is directly proportional to the square of the carrier

frequency Specifically lower frequencies propagate much farther than

high frequencies Out of Band Emission

Radio transmissions are never entirely confined to their operating bandwidth

Some power leaks into the adjacent parts of the spectrum causing adjacent channel interference

Adjacent Channel Interference (ACI): The spectrum mask allows us to compute the adjacent channel interference precisely.

FCC Regulations Channel Occupancy Database Fixed Device, Portable Devices Interference to DTV Receivers

Design Rules7

Determining Transmit Power Design Rule 1

Consider a white space W, which is to be shared between several APs. Ensure that each AP gets at least 6MHz and set the transmit power for each AP to 40 mW (16 dBm).

Design Rules (cont’d)8

Guard Band Design Rule 2

The guard band depends on the frequency of operation.

For channels 21-51, the guard band between frequency allocations on two different radios on the same AP should be separated by at least 20MHz.

Thus for the choice of spectrum mask parameters L = -50 dB and α = -2.28 dB/MHz, adjacent channels with no guard band can be allocated to adjacent access points

Design Rules (cont’d)9

Interference Graph Design Rule 3

The interference map of an AP in a higher frequency band can be inferred from the interference measurements in a lower frequency band using Equation 11 along with appropriate ambient interference measurements.

Consider two APs AP1 and AP2, and suppose AP1 is transmitting using power P.

Suppose Pr(f1) is the received power at AP2 when the transmission happens using carrier frequency f1, and similarly Pr(f2) is defined.

Design Rules (cont’d)10

Aggregate Spectral Efficiency (ASE) Design Rule 4

For any frequency band, the RSSI measurements from the clients can be used to compute the ASE.

The ASE in one frequency band can be computed from the ASE in another frequency band

Consider a carrier frequency f1 for an AP. Assume the kth client perceives SINRk(f1)(dB). Then the spectral efficiency for the kth client is k(f1) = a + bSINRk(f1).

Assume there are N clients and each client has equal opportunity to communicate with the AP. Then the ASE is given by

System Architecture and Spectrum Allocation Problem

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Architecture Access Point

Each access point comprises multiple transceivers One transceiver is dedicated for communications

over a common control channel Clients Central Controller

periodically computes the interference graphs in the different whitespaces.

computes the ASE in the different whitespaces based on control channel aggregate RSSI measurements provided by the AP

an efficient allocation of the available whitespaces based on interference maps, ASEs, ACI constraints, transmit power constraint

System Architecture and Spectrum Allocation Problem (cont’d)12

System Architecture and Spectrum Allocation Problem (cont’d)13

Spectrum Allocation Problem in DTV-band Our goal is to assign spectrum to all/some of the

radios of each AP in the different WS’s. There are NWS distinct white spaces (WS), where the jth

white space has center frequency fj and total available bandwidth Wj .

We wish to distribute the white space bandwidth among NAP distinct AP’s.

Each AP has Nrad different radios.

For the jth white space, associated with APi is a set of other AP’s Nij (called neighbors of APi in white space j) that cannot transmit simultaneously with APi over the same spectrum on any of the Nrad radios.

System Architecture and Spectrum Allocation Problem (cont’d)14

System Architecture and Spectrum Allocation Problem (cont’d)15

Associated with APi are two parameters Demand in terms of data rate, denoted by di

ASE over whitespace WSj, denoted by ηij we can set ηij = 0 if WSj is not available to APi

System Constraints and Objective Operating Spectrum Width Minimum Spectrum Width

bm= 6MHz Co-channel Reuse Constraint

From the interference graph Adjacent-channel Reuse Constraint

System Architecture and Spectrum Allocation Problem (cont’d)16

Objective Function In proportional fairness based schemes, the goal is

to maximize overall system utility where the logarithm of the data rates are taken as a measure of utility

In such a scheme, the objective is to find data rate r i to APi

The problem of maximizing system capacity our objective will be to maximize the total data rate

across all AP’s, subject to the constraint that no AP gets more than the requested demand

System Architecture and Spectrum Allocation Problem (cont’d)17

Problem Statement Proportionally Fair White-Space Spectrum

Allocation Problem (PF-WSA) To find: an allocation of spectrum to the Nrad

radios of the AP’s subject to the system constraints OSW, MSW, CCI, and ACI such that, if ri is the data rate achieved by APi,

then Σi dilog(1 + ri) is maximized.

Algorithm18

Spectrum allocation for single WS and single radio per AP The problem can be solved easily for a clique

Greedily assign spectrum to AP’s that give higher increase in the utility per unit of spectrum

Identify cliques formed by neighbors of a node for all nodes u, and then greedily assign spectrum by giving higher priority to those cliques that give the best improvement in the objective function.

Our goal is to maximize Σi Ui(ri) mi: a minimum threshold

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Sum the used bandwidth and update

20-22: Request = Demand, remove ym

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28. If the last iteration alone contributes to the utility more than the other iterations combined, we allocate bandwidth only to the greedy choice in the last iteration

Algorithm (cont’d)22

Solving PF-WSA for a general interference graph 1. Computing the total utility in the

neighborhoods 2. Allocating spectrum to the best

neighborhood 3. Repetition of the steps

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Algorithm (cont’d)25

Multiple White Space and Multiple Radio the idea of local search where we

iteratively improve upon the solution by improving the solution for individual WS’s

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Simulations28

Two objectives Evaluate the performance of our algorithms

versus an upper bound for the PF-WSA problem

Evaluate the performance benefit from doing dynamic spectrum allocation in the DTV whitespaces as opposed to doing dynamic spectrum allocation in the 2.4GHz ISM band

Simulations (cont’d)29

Conclusion and Comments30

Designing system for short range unlicensed access is a complex and challenging task

four design rules that allow us to manage this complexity, and based on these rules, we proposed an architecture and algorithms for

efficient demand-based spectrum allocation Comments

Thorough system design procedure From the issue analysis to different case solution

The future of DTV whitespace