Presented by: Zakhia Abichar Computer Systems Lab Group Meeting Jan. 28, 2010

1. White Space Networking with Wi-Fi like Connectivity Paramvir Bahl*, Ranveer Chandra*, Thomas Moscibroda*, Rohan Murty**, Matt Welsh***Microsoft Research, Redmond, WA**Harvard University, Cambridge, MA In proceedings of SIGCOMM 2009 Presented by: Zakhia Abichar Computer Systems Lab Group Meeting Jan. 28, 2010

2. TV Transition from Analog to Digital • TV transition from analog to digital • The switch to all-digital broadcasting freed up parts of the broadcast spectrum for public safety communications • city council workers, utility workers, fire department, police, etc. • Digital TV allows transmitting a High-Definition (HD) program, or multiple Standard Definition (SD) programs simultaneously; multicasting • Some of the spectrum can be leased to companies to provide wireless broadband More can be found on:www.dtv.org

3. White Space Networking • The unused portions of the UHF spectrum are called “White Spaces” • Earlier research focused on detecting the presence of RF signals • More recently, the focus is on establishing a wireless link between white space devices • This paper researches how to build Wi-Fi-like network (multiple links) in white spaces

4. 3 kHz 300 kHz 300 kHz 3 MHz 3 MHz 30 MHz 30 MHz 300 MHz 300 MHz 3 GHz Broadcast TV 3 GHz 30 GHz Wi-Fi (ISM) 30 GHz 300 GHz

5. Measurements -60 “White spaces” dbm 700 MHz 470 MHz -100 Frequency

6. The Challenges • FCC ruling on Nov 4, 2008 allowed using unlicensed devices in white spaces • Condition: non-interference with primary users • The aim is to set up one wi-fi like AP with multiple connected stations • Spatial variation • Primary users change from a location to another • Spectrum fragmentation • Primary users can operate on parts of the white space • Temporal variation • A microphone of primary users has on/off traffic • The research in this paper shows that one packet transmitted has an audible effect!

7. TV Stations in America Spatial Variation • The usage of white spaces changes with the location • In large-scale • TV broadcasting • In small-scale • Wireless mircophone (used in classrooms, sporting events, concerts)

8. Spectrum Fragmentation • A fragment consist of one or more contiguous channels that are unused • Rural and suburban areas are more likely to have larger fragments Up to 16 channels in rural areas Data fromwww.tvfool.com

9. Channels Profile for Ames, IA (zip code:50010)from www.tvfool.com We can deduce which channels are not used in this area

10. Temporal Variation • It is especially caused by wireless microphones • Measurements at university premises over several days • Wireless mics are used at different times of the day and for different durations • Per FCC rules, the AP and station should detect the presence of a mic and move to another channel

11. KNOWS Platform • A prototype for white space networking • KNOWS incorporates • Wi-Fi card • UHF band converter • Software-Defined Radio • The proposed system, WhiteFi, was implemented on KNOWS platform

12. KNOWS Architecture • PC • Equipped with a 2.4 GHz Wi-Fi card • Scanner • Separate from data transciever • Used to scan and find primary users • UHF translator • Connected to Wi-Fi card • Converts between 2.4 GHz and 512-698 MHz

13. Functional Block of KNOWS • Scanner samples the UHF spectrum to detect TV broadcasts • Implemented in Software-Defined Radio (SDR) • UHF TV channels 21-51 in 6 MHz increments • Scanner is able to find TV signals as low as -114 dBm and wireless microphones at -110 dBm Scanner

14. Two Key Features • Variable channel width • Support of multiple contiguous channels • Modified Ahteros wi-fi driver to use 5, 10 or 20 MHz • Signal Inspection before Fourier Transform (SIFT) • Determine if there is a packet without decoding • Start of high signal: start of packet • End of high signal: end of packet

15. WhiteFi Architecture • Spectrum assignment • AP discovery • Disconnections

16. AP: {u0, u1,…, uk}Client 1: {u0, u1,…, uk}Client 2: {u0, u1,…, uk}Client 3: {u0, u1,…, uk} bitwise OR Spectrum Assignment • AP and each client maintain info on the channels (30 of them) • {u0, u1,…, uk} channel in use (=1), 0 otherwise • {A0, A1,…, Ak} estimate airtime utilization • New channel selection • Caused by a primary user becoming active • Periodical probing of spectrum to find better channels • Control message sends u and A vector to the AP • Bitwise or eliminates channel that are not available

17. Accounting for Spatial Variation 1 1 1 1 2 2 2 2 3 3 3 3 4 4 4 4 5 5 5 5 1 1 1 2 2 2 3 3 3 4 4 4 5 5 5  = 

18. Spectrum Assignment (cont’d) • Consider each possible channel (F,W) • Select the one with highest aggregate throughput • Expected share of channel c for node n • B^n_c is the number of APs operating on c • Multichannel airtime metric Channel (F,W) has center frequency F and width W

19. Intuition BS 2 1 3 4 5 • Carrier Sense Across All Channels • All channels must be free • ρBS(2 and 3 are free) = ρBS(2 is free) x ρBS(3 is free) Intuition But Use widest possible channel Limited by most busy channel Tradeoff between wider channel widths and opportunity to transmit on each channel

20. AP Discovery • 30 UHF channels x 6 Mhz • Data channels are 5, 10 or 20 MHz • There are 84 combinations to scan • Scan a band • Hardware used can sample 8 MHz at most • Use SDR to find the presence of a signal • AP that overlaps with 8 MHz band is detected • No need to scan all the 84 combinations SDR: Software-Defined Radio

21. Data ACK SIFT, by example SIFS 10 MHz 5 MHz SIFT ADC SIFT Does not decode packets Amplitude Pattern match in time domain Time

22. BS Discovery: Optimizing with SIFT 1 2 3 4 5 1 2 3 4 5 18 MHz Matched against 18 MHz packet signature Amplitude Time SIFT enables faster discovery algorithms

23. BS Discovery: Optimizing with SIFT Linear SIFT (L-SIFT) Jump SIFT (J-SIFT) 1 1 2 2 3 3 4 4 5 5 6 7 8

24. Disconnections • A primary users (e.g. wireless mic) start to use the channel • AP and station vacate the channel (disconnection) • AP and station need a way to tell each other which channel to go next • But they cannot talk again since there is a primary user • AP maintains a 5 MHz backup channel that is advertised in beacons • Upon detection of primary user, they switch to backup • In case backup is also busy, AP switch to another available channel • Then AP periodically scans other channels to re-connect with other users

25. SIFT Accuracy • How reliable can we detect transmissions? • Varying WhiteFi channel width and traffic density (125 kbps to 1 Mbps) • Varying attenuation

26. AP Discovery • There is one fragment of contiguous channels available • J-SIFT is better for a medium size fragment Comparison to non-SIFT approach 10 channels

27. AP Discovery • The fragments are of random size (data:www.tvfool.com) • There is one AP randomly placed • When the fragments are big, J-SIFT has a good chance of finding it quickly Bigger fragments Smaller fragments

28. Throughput metric • When there is a lot of primary traffic, a smaller channel is better Throughput results are by simulation

29. Throughput 33 34 35 36 37 38 39 40 25 26 27 28 29 31 32 30