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WiFi Models

WiFi Models. EE 228A Lecture 5. Teresa Tung and Jean Walrand Department of EECS University of California at Berkeley. Overview: Contents. WiFi models via an example of QoS over 802.11 Overview 802.11 DCF Extension for 802.11e EDCF. Overview: Scenario. 802.11 Network

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WiFi Models

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  1. WiFi Models EE 228A Lecture 5 Teresa Tung and Jean Walrand Department of EECS University of California at Berkeley

  2. Overview: Contents WiFi models via an example of QoS over 802.11 • Overview • 802.11 DCF • Extension for 802.11e EDCF

  3. Overview: Scenario 802.11 Network • What is the throughput? • Can we provide QoS? D1 S1 A1 5.5 Mbps … Am Sm Dm 2 Mbps AP V1 H1 H1 11 Mbps … Vn Hn Hn 5.5 Mbps

  4. Overview: 802.11 MAC • Point Coordination Function (PCF) • Not implemented • Simple to analyze TDMA • Distributed Coordination Function (DCF) • Implemented • More difficult to analyze CSMA/CA • Ex: 802.11b (11 Mbps) • Data only: 6 Mbps • VoIP: 12 connections  64 kbps/direction  1.5 Mbps

  5. Overview: DCF review V1 V1 V’n A1 D1 S1 A1 5.5 Mbps … Am Sm Dm 2 Mbps AP V1 H1 H1 11 Mbps … Vn Hn Hn 5.5 Mbps Dm Dm

  6. VoIP only V1 V1 V’2 V’1 • Hope to send V1,V2,…,Vn in 20 ms • Time depends on n and rates • Given rates, there is a maximum n feasible V1 H1 H1 11 Mbps AP … Vn Hn Hn 5.5 Mbps … Vn

  7. VoIP only: approach Observation: Bottleneck at the AP # voice connections Bianchi’s model M/G/1 model at the AP QoS criterion: ave delay < 20 ms Pr(AP senses channel busy) E[transmission delay] Call capacity

  8. Bianchi model • Discrete model with variable slot size • Idle slot • Success = VoIP + SIFS + ACK + DIFS • Collision = VoIP + EIFS • VoIP = (RTP + UDP + IP + MAC + payload)/rate

  9. Bianchi: 802.11b Markov chain 16 32

  10. Bianchi: simplification Simplification: Assume independence p1 1 p2 … pn c1 = 1 –  i 1(1 – pi) Markov chains coupled Ex: 2 stations state (CW1,m1,CW2,m2) 2 1

  11. Bianchi: background A N1 N2 B C • Circuit switched networks [Erlang fixed point] • Pr(A blocked) depends on (#A,#B,#C) • Simplification: Assume each call blocked independently by different links • Ex: Arrival rate at 1: 1 = A (1 – b2) + B Pr(blocked at 1): b1 = (N1) M/M/1/N1 • Packet switched network [Kleinrock independence approximation]: M/M/1 queuing model • Interacting particle systems [Gibbs]

  12. Bianchi: fixed point Node n Find fixed point solution (e.g. voice only) Markov chain

  13. M/G/1 review

  14. 802.11: Comparison with ns-2 • 802.11b network, G.711 codec (160 byte/D)

  15. 802.11: results Maximize throughput by • Limiting the number of contending stations • Using large packet payload Not suitable for VoIP

  16. 802.11e: EDCF review • Voice has edge over data (waits less) • Chooses random back-off from smaller interval • Waits less time after busy period to operate AIFS V = DIFS AIFS D = AIFS V + 2 IDLE • However, may still be pre-empted by data AIFS V Backoff V V1 D1 Backoff D Backoff D AIFS D AIFS D

  17. 802.11e: approach Type A • AIFS D = AIFS V + 2 IDLE Type B 0 1 • Classify slots by two types • A reserved for VoIP transmissions • B for all types of transmissions • Changes fixed point equations e.g. AP

  18. 802.11e results • Cannot guarantee service Ex.

  19. Why 802.11e is not enough • Not enough transmission attempts for VoIP • AP admits too many data packets

  20. Enabling QoS over WiFi Ideal solution: PCF • Requires changes of AP and wireless clients DCF solution using existing WiFi clients • Requires changes at the AP • Estimate capacity • Admission control for VoIP and video • Traffic shaping for TCP • PCF on downlink via NAV vector

  21. References • G. Bianchi, “Performance analysis of the IEEE 802.11 distributed coordination function,” IEEE J. Select Areas Communications, vol. 18, no. 3, pp. 535-547, 2000. • N. Hedge, A. Proutiere, and J. Roberts, “Evaluating the voice capacity of 802.11 WLAN under distributed control,” Proc. LANMAN, 2005.

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