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Bringing Life to Dead Spots

Bringing Life to Dead Spots. Grace Woo Pouya Kheradpour, Dawei Shen, and Dina Katabi. Many APs But Still Poor Coverage. mit1. mit4. mit5. Problem increases with mobility and low power devices. Poor Coverage Is Not No Coverage!. X. X. 010101011111. 011101011011. Loss. Loss.

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Bringing Life to Dead Spots

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  1. Bringing Life to Dead Spots Grace Woo Pouya Kheradpour, Dawei Shen, and Dina Katabi

  2. Many APs But Still Poor Coverage mit1 mit4 mit5 Problem increases with mobility and low power devices

  3. Poor Coverage Is Not No Coverage! X X 010101011111 011101011011 Loss Loss Currently High Bit Error  Persistent Loss  Dead Spot Spatial Diversity  APs are unlikely to have same bit error Can recover a correct packet if we combine the correct bits from these receptions

  4. But Which AP Got the Right Bit? First bit is “1” First bit is “0” • Clearly can’t have per bit checksum • Prior work (MRD) tries all block combinations to satisfy checksum • Exponential Complexity • Works for a few bit errors But not dead spots

  5. SOFT • Recovers a correct packet from its faulty receptions at APs • Leverages physical layer hints to identify correct bits • SOFT’s delivery rate is up to10x higher than current WLANs and MRD

  6. SOFT Architecture X X 010001001111 010101001011 010001001011 SOFT Combiner Internet APs leverage high-speed Ethernet to combine their receptions Wired Ethernet AP2 APn AP1 But which bits are correct?

  7. 01011001 PHY Physical Layer Knows More! PHYalready estimates a confidence in its 0-1 decision  Soft Value PDF of per bit soft values Soft Value < 0  “0” Soft Value > 0  “1” Larger absolute soft values  More confidence in bit Measured Soft Values

  8. We Use the Soft Values • SOFT changes the PHY interface to expose the soft values to higher layers • SOFT combines the soft values of a bit to decode it correctly • The combiner forwards the decoded packet if it satisfies the 802.11 checksum 010110111 SOFT Combiner AP2 AP1 Soft packet Soft packet

  9. How Do We Combine Soft Values? Say for a particular bit, we got - 0.1 - 0.2 0.4 • How do we decode the bit? • Maximum soft value  Bit is “1” • Majority vote  Bit is “0” • Average  Bit is “1” Different Combining Methods  Different Answers!

  10. SOFT Combining Algorithm Intuitively, we want to favor less noisy channels • Let be the noise variance on the channel to APi • Let Sij be the soft value of bit j reported by APi • SOFT decision rule: • For AWGN and dead spots rule is proven optimal.

  11. But, How Does SOFT Get the Noise Variance? • Randomness in soft values is caused by channel noise PDF of per bit soft values Measured Soft Values • Estimate from the PDF of the soft values in packet

  12. How About Overhead? • PHY soft values can be 32-bit float •  Excessive Ethernet traffic • Solution • Invoke SOFT only when associated AP can’t decode • Quantize soft values (we used 3 bits)

  13. What About the Downlink? X X 010001001011 010101000011 Use Time Diversity Combine a packet with its retransmission

  14. Performance

  15. SOFT Implementation • Software – GNURadio codebase • Hardware – USRP frontend • GMSK and DBPSK modulations • Soft values are inputs to the slicer • Poor Coverage: • SNR 5 – 12 dB • BER about 10-3

  16. Experimental Setup • 13 GNURadio nodes • Compared • Current 802.11 WLAN (user associates with best AP) • MRD • SOFT • Each Experiment • 3 random APs • Random source • Transmit 500 packets

  17. Does SOFT Help? CDF of 100 experiments Packet Delivery Rate

  18. Does SOFT Help? CDF of 100 experiments Packet Delivery Rate

  19. Does SOFT Help? CDF of 100 experiments Packet Delivery Rate

  20. Does SOFT Help? CDF of 100 experiments 10x Packet Delivery Rate SOFT’s delivery rate can be 10x higher

  21. Performance with Increasingly Poor Coverage Packet Delivery Rate Bit Error Rate

  22. Performance with Increasingly Poor Coverage Packet Delivery Rate Current Approach Bit Error Rate

  23. Current Approach Performance with Increasingly Poor Coverage MRD Packet Delivery Rate Bit Error Rate

  24. Current Approach Performance with Increasingly Poor Coverage MRD SOFT Packet Delivery Rate Bit Error Rate SOFT Addresses Dead Spots

  25. SOFT on Downlink CDF over 50,000 packets Current Approach Number of Retransmissions Until Correct Packet

  26. SOFT on Downlink CDF over 50,000 packets 17 ReTx SOFT Current Approach Much Higher Throughput! Number of Retransmissions Until Correct Packet

  27. MAX Combining Method Is Important Majority SOFT CDF of 100 experiments Packet Delivery Rate SOFT Outperforms MAX and MAJORITY

  28. Effect of Quantization SOFT Average Delivery Rate 32 Bits 3 Bits 2 Bits All presented results are for 3-bit quantization! Overhead on Wired Ethernet is Acceptable

  29. Related Work • Soft and softer handoff in cellular networks • Theoretical Maximum Ratio Combining (MRC) [Brennan55,Yang99] • H-ARQ & Chase Combining [ASX03] • Partial Packet Recovery [Jam07]

  30. Conclusion • WLAN can have better coverage if the interface to the PHY exposes soft values • Delivery rate can be up to 10x higher • Ethernet overhead is acceptable • The new architecture, SOFT, can co-exist with unmodified 802.11 cards and APs

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