Multi-Rate Adaptation with Interference and Congestion Awareness

1. Multi-Rate Adaptation with Interference and Congestion Awareness IPCCC 2011 University of California, Santa Cruz* Huawei Innovation Center^ 11/17/2011 Duy Nguyen*, J.J. Garcia-Luna-Aceves* and Cedric Westphal*^

2. Rate/Link Adaptation

3. Challenges S R Limited Feedback Interference N1 N2

4. Challenges Path Attenuation Multi-path Fading S R Limited Feedback Interference N1 N2

5. Rate Adaptation:Explicit vs Implicit Approach • Explicit: • Receiver-driven: dictates what rate that should be used • CSI S/N measurements & BER estimate • Implicit: • Sender-driven: Inferring the channel condition on the receiver • Based on RSSI measurements and ACK Packets

6. Rate Adaptation:Explicit vs Implicit Approach • Explicit: • Pros: measurements estimate from PHY • Cons: Incurs additional overhead, possible stale feedback due to short channel coherence time. • Implicit: • Pros: simplicity • Cons: must infer the channel condition on the receiver side

7. Multi-rate Adaptation with Interference Congestion Awareness (MAICA) • Implicit Approach can be very effective • Inspired by AIMD Scheme • Credit-based systems, using both packet window and time window • Allows progressive rate increase and immediate rate decrease • Reactive to changes in the environment • Compatible with current WiFi Systems

8. Multi-rate Adaptation with Interference Congestion Awareness (MAICA)

9. Multi-rate Adaptation with Interference Congestion Awareness (MAICA) Packets Bucket & Time Window Credit Bucket

10. Multi-rate Adaptation with Interference Congestion Awareness (MAICA) Acceptable Threshold Packets Bucket & Time Window Credit Bucket Awarding a credit

11. Multi-rate Adaptation with Interference Congestion Awareness (MAICA) Acceptable Threshold Packets Bucket & Time Window Credit Bucket Awarding a credit

12. Multi-rate Adaptation with Interference Congestion Awareness (MAICA) Acceptable Threshold Increase Rate Packets Bucket & Time Window Credit Bucket Credit has been reached

13. Multi-rate Adaptation with Interference Congestion Awareness (MAICA) Acceptable Threshold Decrease Rate Packets Bucket & Time Window Credit Bucket

14. Multi-rate Adaptation with Interference Congestion Awareness (MAICA) Acceptable Threshold Decrease Rate Packets Bucket & Time Window Credit Bucket

15. Multi-rate Adaptation with Interference Congestion Awareness (MAICA) More errors than success packets Decrease Rate Multiplicatively Packets Bucket & Time Window Credit Bucket

16. Multi-rate Adaptation with Interference Congestion Awareness (MAICA) Transmitting at a lower rate Packets Bucket & Time Window Credit Bucket

17. MAICA MARKOV MODEL

18. ARF and MAICA’s Markov Models

19. NS 3 Simulation Setup • Implicit rate adaptation evaluations • Compare against other current well-known rate adaptations such as AMRR, CARA, RRAA • Ported the popular Linux Minstrel rate adaptation to ns-3 simulations • MAICA consistently performs well in all scenarios

20. Fading with Movement S R

21. Scenario Setup Exponential distributed flows with mean of 3s 20m distance between each node

22. Propagation Loss Models

23. 50 Flows in 500mx500m Topology with Random Node Placement

24. 30 Flows and 2D Mobility in 500mx500m Topology with Random Node Placement

25. Fairness Evaluation Jain’s Fairness • Evaluate Jain’s Fairness Index and Aggregate Throughput • MAICA achieved fairness not at the expense of performance

26. Fairness with 16 Flows Static Grid Aggregate Throughput 8% gain over CARA

27. Fairness with 100 Flows Static Grid Aggregate Throughput 25% gain over CARA in dense networks

28. Linux Implementation of MAICA

29. Real World Experiments

30. Conclusion • Simple and practical • Inspired by TCP and AIMD • Consistently performs well in various fading scenarios, especially in multi-user environment • Fairness achieved not at the expense of performance • Seamless integration with current Wi-Fi with Linux Kernel implementation