Xiaojun Feng , Jin Zhang, and Qian Zhang Hong Kong University of Science and Technology

1. Database-Assisted Multi-AP Network on TV White Spaces: Architecture, Spectrum Allocation and AP Discovery Xiaojun Feng, Jin Zhang, and Qian Zhang Hong Kong University of Science and Technology DySPAN 2011

2. How far away are we from mass deployment of cognitive radio networks? Real and Mass deployment of cognitive radio network. How can a multi-AP system really works on TV white spaces? 2008, 2010 FCC releases TV white space for secondary access 10 years of study of Cognitive Radio 1999, Cognitive Radio was proposed by Joseph Mitola and Gerald Q. Maguire, JR

3. Some backgrounds • TV White Spaces • Free TV channels after Analog to Digital Transition • FCC rules • Sep. 2010 • Available TV channels: channel 2-51 (except 37), 54MHz~698MHz • Geo-location Database architecture

4. Existing Systems • WhiteFi, SIGCOMM 09 • Single AP, multiple users • Adaptive channel width • Sensing based architecture • Jello, NSDI 10 • Several link pairs • Non-continuous spectrum for each link • Coordination through common backup channel • SenseLess, DySPAN 11 • Database architecture • Mainly focus on the database design and implementation

5. Our Aim • Our system should be compatible with the database architecture • Multiple APs, each AP supports multiple users • Non-continuous spectrum allocation for each AP in a distributed manner • Challenges • Detailed database specification • How to allocate spectrum for each AP distributedly while ensuring fairness and performance? • How can users discover APs operating on non-continuous band?

6. Our System: WhiteNet AP Discovery and Connection: a novel beacon scheme Spectrum Sharing among APs: rule regulated spectrum allocation Incumbent Protection: propose a local database compatible with FCC’s final rule

7. Outline • WhiteNet Design • WhiteNet Local Database • Distributed Spectrum Allocation • AP Discovery • System Implementation • Evaluation • Conclusion

8. WhiteNet: the Local Database • Why a local database? • Act as an proxy between global database and local APs, provide information of available channels • Facilitate spectrum among APs • What’s in the local database? • Available TV channel list • Information about APs in the system • Location • Power • Channel occupation • Anything be more?

9. WhiteNet Local Database • Proposed Local Database Architecture:

10. WhiteNet Local Database • Vacant TV Database (TDB) • Store information about available TV channels obtained from the central database • Local AP Database (ADB) • Store information about APs in the local area network, such as location, power, occupied channel • Contention Database (CDB) • Define rules to resolve contention between APs during spectrum allocation • One simple example: • CDB generate random primes periodically • Two contending APs generate their own numbers and compared the residuals through CDB

11. WhiteNet: Distributed Spectrum Allocation • Why distributed? • There may not be any central controller, there are only central database. • The controller may become a bottleneck in the centralized scheme • Our assumptions • All APs are good people • They can follow some rules • The problem is: How to define such “rules”?

12. Existing Rule-based Spectrum Allocation Schemes • Assign each AP with spectrum around its “fair” share, so everyone will be happy • But, what’s a “fair” share? • Poverty Line: a lower bound on spectrum allocation to one AP, when the system converges

13. Unique challenges in TVWS • Frequency Heterogeneity of TV band • Higher frequency  higher path loss • Non-uniform path loss non-uniform interference graphs in different bands • Fragmented Spectrum in a very wide range (54MHz-698MHz), but limited capability for each AP A limited number of contiguous spectrum width, especially in urban areas Figure from WhiteFi, SIGCOMM09

14. WhiteNet’s Way: B-SAFE: DistriButed Spectrum Allocation For whitespacE • For Frequency Heterogeneity: • Use different interference graphs in different bands • Define an “aggregated poverty line” to jointly value the fair share of each AP in all available bands • For Frequency Fragmentation: • Enable NC-OFDM to utilize fragmented spectrum • Consider the spectrum span constraint of each AP

15. B-SAFE: Key Ideas • Aggregated Poverty Line : Number of spectrum chunks in white space i : Number of neighbors of AP j in white space i : Number of white spaces Now the problem becomes: How to assigned each AP with spectrum of width APL

16. B-SAFE: Key Ideas • Aggregated Poverty Line

17. B-SAFE: Key Ideas • Consideration of spectrum span constraint • One radio can access limited spectrum span • Partition all white spaces according to the maximum spectrum span • Calculate APL for each partition • AP chooses one partition to do spectrum allocation

18. B-SAFE: Algorithm Outline • APs contend through database to assign spectrum one by one • AP calculates its APL in each partition • AP select one partition and use Best Fit to do spectrum allocation • Other APs update available spectrum Until all APs are assigned spectrum

19. WhiteNet: AP Discovery • In WiFi • AP is operating on one of the pre-defined WiFi channels • AP periodically broadcast beacon messages • A Client scans APs of each WiFi channels and records their corresponding signal strengths • Challenges in WhiteNet • AP may be assigned with non-continuous spectrum • Both the bandwidth and center frequency of each AP can be variable

20. AP Discovery • Our Key Ideas • Each AP uses its left most frequency for beacon message Beacon for AP1 Beacon for AP1

21. AP Discovery • Our Key Ideas • Each AP uses its left most frequency for beacon message • All APs can be discovered one by one Cancel out the spectrum of AP1, AP2’s beacon can be found

22. Outline • WhiteNet System Architecture • WhiteNet Database Design • Spectrum Allocation Algorithm • AP Discovery • System Implementation • Evaluation • Conclusion

23. System Implementation • Platform • 7 USRP nodes • Hardware limitations • USRP cannot support a very wide bandwidth • No proper antenna for TV band • WhiteNet’s solution • Define 40 channels, each of width 125KHz, in 2.4GHz band • Set different power on different bands to obtain different interference relationships

24. System Implementation • Proof of concept implementation of the WhiteNet Local Database • Run on one linux machine as an user level process, data stored in memory. • APs use socket to connect this machine through wired backhaul • Define communication protocol between AP and database process

25. System Implementation • NC-OFDMA • Support multiple users • Currently, only downlink is supported, since it is hard to synchronize multiple users • Uplink implementation will be left as our future work • AP discovery • MAC protocols for both AP and the user to set up connection

26. Outline • WhiteNet System Architecture • WhiteNet Database Design • Spectrum Allocation Algorithm • AP Discovery • System Implementation • Evaluation • Conclusion

27. System Evaluation • Three topologies • Two metrics • System goodput • Proportional fairness of the spectrum allocation • Four spectrum algorithms • B-SAFE • Uni-Conservative: use the interference graph on the lowest frequency for all white spaces • Uni-Aggressive: use the interference graph on the highest frequency for all white spaces • Continuous allocation

28. Efficiency of B-SAFE(vs. uniform interference graph) System goodput in topology 1, similar results in other topologies Proportionally fairness of the system in topology 1

29. Efficiency of B-SAFE(vs. continuous allocation) Results of system goodput in topology 1 Results of proportionally fairness of the system in topology 1

30. System Evaluation • Efficiency of the AP discovery scheme • Topology • Two APs: 1 & 3 • Clients: 2, 4, 5, 7 • Clients try to connect one AP one by one • The baseline scheme • Check all the combinations of different center frequencies and different spectrum width • Metric • Time to discover all neighboring APs

31. Time in AP Discovery Results are an average of 8 round tests

32. Simulation Evaluation • To evaluate B-SAFE in a larger scale network • Scenario • 20-120 APs randomly distributed in a 1km × 1km area. • Randomly generated 6−30 vacant TV channels • Interference graph generated according to the path loss model • Metrics • Average goodput of each AP • Average utility of each AP

33. Simulation Results vs. uniform interference graph vs. continuous allocation

34. Conclusion • WhiteNet architecture coherent with the FCC’s rule • Distributed spectrum allocation algorithm – B-SAFE • AP discovery and connection based on a novel beacon scheme • Both system and simulation evaluation show the efficiency of the proposed algorithm

35. Thanks!Questions? Database-Assisted Multi-AP Network on TV White Spaces: Architecture, Spectrum Allocation and AP Discovery Xiaojun Feng xfeng@cse.ust.hk