ZigZag Decoding: Combating Hidden Terminals in Wireless Networks

1. ZigZag Decoding: Combating Hidden Terminals in WirelessNetworks Shyamnath Gollakota and Dina Katabi MIT CSAIL SIGCOMM 2008 Presented by Paul Wang

2. Hidden Terminal Problem Alice • Leads to low utilization of bandwidth and unfairness in channel access • RTS/CTS induced too much overhead – disabled by default • Collided packets may still be decodable! Bob AP X

3. 2 Characteristics of 802.11 Exploited • An 802.11 sender retransmits a packet until it is acked or timed out, and hence when two senders collide they tend to collide again on the same packets • 802.11 senders jitter every transmission by a short random interval, and hence collisions start with a random stretch of interference free bits

4. Basic idea of ZigZag Decoding • Chunk 1 from user A from 1st copy of collided packet can be decoded successfully • Subtract from 2nd copy to decoded the Chunk 1 of user B • Subtract from 1st copy of collided packet to decode Chunk 2 from user A • Subtract from 2nd copy of collided packet to decode Chunk 2 from user B

5. Wait! What about Shannon Capacity? R1 • Requires retransmissions if collision occurs • No overhead if no collision TDMA R2

6. Other alternatives • CDMA • Incompatible with WLAN • Low efficiency in high SNR • Successive interference cancellation (SIC) • Chunk == packet • Decode the strong signal first, subtract from the sum and then decode the weak signal • No need for retransmissions • Both transmitters need to transmit at a lower rate

7. Patterns that ZigZag Applicable • Both backward and forward decoding can be used Sudoku? 

8. Preliminary on communication • BPSK: 0 -> -1 1 -> 1 http://en.wikipedia.org/wiki/QPSK

9. Technical Barriers • How do I know packets collide • Matching collision happened? (P1, P2) and (P1’, P2’) • Frequency offset between transmitter and receiver • Sampling offset • Inter-symbol interference • What if errors occur in chunks • Acknowledgement? } subtraction is non-trivial

10. Collision Detection • Preamble • Pseudo random number, independent of shifted versions of itself as well as the data • Correlation with moving window • thresholding

11. Matching collision • Given (P1, P2()) and (P1’, P2’(’)), how to determine that P1 = P1’ and P2 = P2’ • Determine offset first – you know this from the collision detection scheme in the prior slide • Align P2(Δ) and P2’(Δ’) accordingly • Calculate correlation of P2() and P2’(’) • If high correlation, then packet matched!

12. Decode matching collision • Decode iteratively • Re-encoding • Computing channel parameters • Channel gain estimated from • Frequency offset and sampling error 1) coarse estimation from previously successful reception 2) iterative estimation • Inter-symbol interference: take the inverse of linear filter (for removal of ISI)

13. Decode matching collision (cont’d) • Re-encoding • Account for sampling offset error (μ) – based off of Nyquist criteria

14. What about errors? • Will errors in decoding have a cascading effect? • Error propagation dies out exponentially • Error correction capability of modulation • Forward and backward decoding

15. Acknowledgement • Use as much synchronous acknowledgement as possible for backward compatibility

16. Evaluation • 14-node GNURadiotestbed • USRP with RFX2400 radio (2.4 GHz) • BPSK • Bit rate 500kbs • 32-bit preamble • 1500-byte payload, 32-bit CRC • Deficiency in GNURadio • Cannot coordinate transmission and reception very closely • CSMA, ACK Software Transmitter Receiver

17. Micro-benchmark

18. Alice & Bob • Bob’s location is fixed, Alice moves closer to the base-station

19. Impact of SNR on BER • Alice & Bob at fixed and equal location • Vary transmission power level

20. Testbed Results • Pick two senders randomly • 10% hidden terminals, 10% partial, 80% perfect

21. Three hidden terminals

22. Secret to Success • Work on something novel! • Write effectively and clearly… the paper must be understandable by the readers • Don’t assume your reader knows as much as you about the specific topic • Made numbers sound good… but BER/Packet loss numbers don’t mean there isn’t any error… bit errors are just very low!