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Overcoming the Antennas-Per-AP Throughput Limit in MIMO

Overcoming the Antennas-Per-AP Throughput Limit in MIMO. Shyamnath Gollakota Samuel David Perli and Dina Katabi. MIMO LANs. Today, MIMO delivers as many concurrent packets as the antennas on the AP. Talk presents a practical technique to double the concurrent packets in MIMO LANs.

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Overcoming the Antennas-Per-AP Throughput Limit in MIMO

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  1. Overcoming the Antennas-Per-AP Throughput Limit in MIMO Shyamnath Gollakota Samuel David Perli and Dina Katabi

  2. MIMO LANs Today, MIMO delivers as many concurrent packets as the antennas on the AP Talk presents a practical technique to double the concurrent packets in MIMO LANs

  3. MIMO Primer Bob AP Antenna 2 Antenna 1 hijis the channel from antenna i to antenna j

  4. MIMO Primer Bob AP AP receives the sum of these vectors

  5. MIMO Primer Bob AP p1 p2 How does the AP decode each packet? Current MIMO decodes as many concurrent packets as there are antennas per AP AP projects on a direction orthogonal to interference

  6. Can We Get More Concurrent Packets? Bob AP p3 p3 Alice All current MIMO LANs are limited by number of antennas-per-AP No direction is orthogonal to all interference  AP can’t decode

  7. Let the APs Coordinate Over the Ethernet Naive solution: Emulate 4-antenna AP by sending every signal sample over Ethernet

  8. Let the APs Coordinate Over the Ethernet Naive solution: Emulate 4-antenna AP by sending every signal sample over Ethernet Impractical Overhead, Raw samples p3 Ethernet Can we leverage the Ethernet with minimal overhead? E.g., a 3 or 4-antenna system needs 10’s of Gb/s

  9. Interference Alignment and Cancellation (IAC) p1 p3 Bob AP1 Ethernet p3 p1 AP2 Alice • IAC overcomes the antennas-per-AP throughput limit • In IAC, a packet is decoded, then broadcasted once on the Ethernet  minimal overhead • Align P3 with P2 at AP1  AP1 decodes P1 to its bits • AP1 broadcasts P1 on Ethernet p2 p3 • AP2 subtracts/cancels P1 decodes P2, P3

  10. Contributions • First MIMO LAN to overcome the antennas-per-AP limit • IAC synthesizes interference alignment and cancellation • Proved that IAC almost doubles MIMO throughput • Implemented IAC in software radios showing practical throughput gains

  11. How to Change Packet Direction?

  12. How to Change Packet Direction? Client AP

  13. How to Change Packet Direction? Client AP Sender controls packet direction by multiplying with a vector

  14. How Do We Align? AP1 Bob AP2 Alice

  15. How Does Alignment Work in Presence of Modulation? Modulated samples are complex numberswith different phases Imaginary Imaginary Sample in P2 Antenna 2 Sample in P3 Real Real Antenna 1 Alignment works independent of modulation phases Alignment is in the antenna domain not the modulation domain

  16. How Does AP2 Subtract Interference from P1? • Can’t subtract the bits in packet • Need to subtract interference signal as received by AP2 Solution • AP2 Re-modulate P1’s bits • AP2 estimate and apply the channel P1 traversed to itself on modulated signal • Channel estimation in the presence of interference as in [ZigZag, SIGCOMM’08] • Subtract!

  17. How Does IAC Generalize to M-Antenna MIMO?

  18. How Does IAC Generalize to M-Antenna MIMO? • Theorem In a M- antenna MIMO system, IAC delivers • 2M concurrent packets on uplink • max{2M-2, 3M/2} concurrent packets on downlink 4 packets on uplink 3 packets on downlink E.g., M=2 antennas

  19. How Does IAC Generalize to M-Antenna MIMO? • Theorem In a M- antenna MIMO system, IAC delivers • 2M concurrent packets on uplink • max{2M-2, 3M/2} concurrent packets on downlink For a large M, IAC doubles MIMO throughput 20 packets on uplink 18 packets on downlink E.g., M=10 antennas

  20. What if There is a Single Client? Client AP1 Can’t have more than 2 concurrent packets, but … AP2 • IAC provides higher diversity than Current MIMO • Diversity gain applies to one or more clients Current MIMO exploits diversity and pick best of two APs IAC can pick the best antenna pair across APs

  21. IAC MAC Leverages 802.11 PCF mode Contention Contention-free Uplink P1 Grant . . . . . • Clients are simple: APs compute v vectors and send them to clients in the Grant message • IAC adapts to changing channels because APs get a new channel estimate from each ACK packet P2 CF- End P3 Time P4 . . . . . P5 ACKs P6 Downlink

  22. Performance

  23. Implementation • GNURadio software • 2-antenna MIMO USRP nodes • Carrier Freq: 2.4GHz

  24. Testbed • 20-node testbed • All nodes within radio range of each other • Each run randomly picks APs and clients

  25. Metric Gain = Client throughput in IAC Client throughput in current MIMO

  26. Uplink Gain CDF of Runs Per-Client Throughput Gain

  27. Uplink Gain CDF of Runs Per-Client Throughput Gain • On uplink, IAC’s median gain is 2.1x • Gain is partially due to diversity but more to concurrency

  28. Downlink Gain CDF of Runs Per-Client Throughput Gain On downlink, IAC’s median gain is 1.5x

  29. Gains as a Function of SNR

  30. Gains as a Function of SNR Uplink Throughput Gain SNR in dB IAC is beneficial across the operational range of SNRs

  31. Related Work • Interference Alignment [AMK’08,JS’08] • Interference Cancellation [GC’80,HWA’08] • MU-MIMO [NJ’06] IAC provably provides more throughput, and doubles the number of concurrent packets

  32. Conclusion • First MIMO LAN to overcome the antennas-per-AP limit • IAC synthesizes interference alignment and cancellation • Proved that IAC almost doubles MIMO throughput • Implemented IAC in software radios showing that it works in practice

  33. IAC MAC Leverages 802.11 PCF mode Contention Contention-free Uplink P1 Grant . . . . . • APs compute and send v vectors in Grant  Clients are oblivious to each other • APs can track channels, i.e., H, from using ACKs P2 CF- End P3 Time P4 . . . . . P5 ACKs P6 Downlink

  34. Uplink: for M=2 antennas, IAC delivers 2M=4 packets APs Clients p1 Ethernet p2 p4 p3

  35. Downlink: - Clients can’t coordinate over Ethernet - For M=2 antennas, IAC delivers 3M/2 = 3 packets Clients APs p1 p2 p3

  36. IAC’s concurrency increases capacity bound C = d log(SNR) + o(log(SNR)) d is degrees of freedom IAC increases degrees of freedom Interference cancellation does not increase degrees of freedom but provides a better use of them

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