1. 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 1

2. Outline 2  Introduction  Related Work  Background  Design Rules  System Architecture and Spectrum Allocation Problem  Algorithms (for spectrum allocation)  Simulations  Conclusion and Comments

3. Introduction 3  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.

4. 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

5. Related Work 5  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.

6. Background 6  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

7. Design Rules 7  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).

8. 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

9. 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 AP 1 and AP 2, and suppose AP 1 is transmitting using power P. Suppose P r (f 1 ) is the received power at AP 2 when the transmission happens using carrier frequency f 1, and similarly P r (f 2 ) is defined.

10. 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 f 1 for an AP. Assume the k th client perceives SINR k (f 1 )(dB). Then the spectral efficiency for the k th client is k(f 1 ) = a + bSINR k (f 1 ). Assume there are N clients and each client has equal opportunity to communicate with the AP. Then the ASE is given by

11. System Architecture and Spectrum Allocation Problem 11  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

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

13. 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 N WS distinct white spaces (WS), where the j th white space has center frequency f j and total available bandwidth W j. We wish to distribute the white space bandwidth among N AP distinct AP’s. Each AP has N rad different radios. For the j th white space, associated with AP i is a set of other AP’s N ij (called neighbors of AP i in white space j) that cannot transmit simultaneously with AP i over the same spectrum on any of the N rad radios.

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

15. System Architecture and Spectrum Allocation Problem (cont’d) 15  Associated with AP i are two parameters Demand in terms of data rate, denoted by d i ASE over whitespace WS j, denoted by η ij we can set η ij = 0 if WS j is not available to AP i  System Constraints and Objective Operating Spectrum Width Minimum Spectrum Width b m = 6MHz Co-channel Reuse Constraint From the interference graph Adjacent-channel Reuse Constraint

16. 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 AP i 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

17. 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 N rad radios of the AP’s subject to the system constraints OSW, MSW, CCI, and ACI such that, if r i is the data rate achieved by AP i,  then Σ i d i log(1 + r i ) is maximized.

18. Algorithm 18  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 Σ i U i (r i ) m i : a minimum threshold

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20. 20 Sum the used bandwidth and update 20-22: Request = Demand, remove y m

21. 21 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

22. 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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25. 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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28. Simulations 28  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

29. Simulations (cont’d) 29

30. Conclusion and Comments 30  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