1. Enhancing 802.11 Wireless Networks with Directional Antenna and Multiple Receivers Chenxi Zhu, Fujitsu Laboratories of America Tamer Nadeem, Siemens Corporate Research Jonathan Agre, Fujitsu Laboratories of America

2. Introduction IEEE 802.11 WLANs have enjoyed tremendous popularity in recent years. RTS/CTS/DATA/ACK packets assume omni-directionality

3. Introduction (cont’d) Channel reservation is made through carrier sensing All neighbors of source and destination nodes need to be silent. Limited number of channels and unlicensed spectrum usage Interference between transmissions is becoming a serious problem.

4. Spatial Fairness of 802.11 Different nodes have different neighbors  experience different contention environments. Nodes at the overlapping coverage area of the WLANs suffer from lower throughput Extend Bianchi’s discrete time Markov model to understand Spatial Fairness

5. Spatial Fairness of 802.11 Extend Bianchi’s discrete time Markov model to some simple multihop networks. Contention probability  Need to revisit Bianchi’s discrete time model conditional collision probability p c Beyond a single hop  different nodes are attached to different ’spatial channels’  no longer share the same notion of discrete time.

6. Assumptions The carrier sensing range is the same as the communication range; RTS/CTS messages are always used A collision (duration of RTS/CTS) takes the same amount of time as an idle slot. DATA/ACK are free of collisions Duration of the RTS/CTS/DATA/ACK four way handshake is a geometric random variable with average of 1/p t slots, where p t is the probability that a data transmission terminates in a slot; Every node always has a packet to send to one of its neighbors.

7. Markov Model

8. Markov Model The state (SA, SC, SB) represents the status of the nodes in group A,C,B in a slot, where The Markov chain has 5 states: (0; 0; 0), (1; 0; 0), (1; 0; 1), (0; 0; 1), (0; 1; 0).

9. Markov Model Transitional Probabilities: Diagonal terms:

10. Markov Model Stationary State Probabilities: p s (0; 0; 0), p s (1; 0; 1), p s (0; 1; 0), and p s (1; 0; 0) = p s (0; 0; 1) Contention probabilities  1 ;  2 of nodes in areas A/B and C Collision probabilities of the nodes in groups A,B and group C

11. Fairness Analysis (N A =N c =N B =20) Throughput vs. Packet size Stationary Probabilities

12. Fairness Analysis (N A =N c =N B =20) Node Contention/Collision P a A = p * s (0; 0; 0) + p * s (0; 0; 1) P a C = p * s (0; 0; 0)

13. Use of Directional Antenna Fairness relieved through interference reduction Directional antenna is a well known method to reduce the interference and to increase the range and the capacity for wireless networks. S-MAC

14. S-MAC: Sectorized Antenna Dedicated Rx per sector/antenna Tx can switch to different antennas Self-interference cancellation between Tx and Rx in different sectors Consistent channel information at different nodes No hidden nodes or deafness problem Addresses the hidden node problem and the deafness problem by continuously monitoring the channel in all directions (sectors) at all time

15. S-MAC Architecture TX 2 TX 1 RX 3 RX 2 RX 1 switching fabric DUX TX symbol for self-interference cancellation S-MAC: SNAV = [NAV TX1,NAV TX2, NAV RX1, NAV RX2, NAV RX3 ] TX RX Directional Antennas … Separate queues Base Band RX RF TX RF MAC and higher

16. Self-interference Cancellation Scheme Different TX and RX modules are all part of the same PHY –on-chip communication between them is possible. When TX i transmits signal S t i, RX j receives S r i. ; –RX j cancels the interference caused by own TX i –RX j can then decode signal from another node k –This requires self-channel estimation from own i to j: G ij : S r i  k. = S r i - G ij * S t i.

17. Sectorized NAV and Carrier Sensing SNAV=[NAV TX1, NAV TX2, NAV 1, NAV 2, …, NAV M ]. –NAV TXi : status of TX i (busy period). Updated when S-MAC node is involved in a transmission using TX i –NAVj: status of medium in sector j. Updated when S-MAC node senses a change of medium status in sector j (sending or receiving RTS/CTS/DATA). Fully interoperable with regular omni 802.11 nodes.

18. Operation of S-MAC (example I) C Example adopted from R. Choudhury, X. Yang, R. Ramanathan, and NH Vaidy, MobiCom 2002. DMAC “Hidden Node due to asymmetric gain” DH A E BF G RTS CTS RTS Collision

19. Operation of S-MAC (example I) Example adopted from R. Choudhury, X. Yang, R. Ramanathan, and NH Vaidy, MobiCom 2002. SMAC: “Hidden Node due to asymmetric gain” avoidance DH A C E BF G RTS CTS CTS from F rcvd RTS not sent by A

20. Operation of S-MAC (example II) Example adopted from R. Choudhury, X. Yang, R. Ramanathan, and NH Vaidy, MobiCom 2002. “Hidden Node due to unheard RTS/CTS” avoidance DH A C E BF G RTS CTS E waits for B-F to finish

21. Operation of S-MAC (example II) Example adopted from R. Choudhury, X. Yang, R. Ramanathan, and NH Vaidy, MobiCom 2002. Deafness Prevention DH A C E BF G E is aware C is Transmitting

22. Markov Model for S-MAC The state (SA, SC1, SC2, SB) represents the status of the nodes in group A,C,B in a slot, where SA + SC1 <= 1, SB + SC2 <= 1, SC1 + SC2 <= 1 The Markov chain has 8 states: (0,0,0,0), (0,0,0,1), (0,0,1,0), (0,1,0,0), (0,1,0,1), (1,0,0,0), (1,0,0,1), (1,0,1,0).

23. Fairness Analysis ( N A =N B =20, N c1 =N c2 =10 ) Throughput vs. Packet size Stationary Probabilities

24. Fairness Analysis ( N A =N B =20, N c1 =N c2 =10 ) Node Contention/Collision P a Ad = p s (0,0,0,0) + p s (0,0,0,1) +p s (0,0,1,0) P a Cd = p s (0,0,0,0) + p s (0,0,0,1)

25. Performance Evaluation NS-2 simulator is used. 802.11b with transmission rate 11 Mbps. Transmission range of 250m and carrier sensing range is 550m. All nodes are stationary. UDP traffics packets with average packet size 1000 bytes. Four way handshake (RTS/CTS/DATA/ACK) is used. Simulated duration of 50 seconds and each point is averaged from 5 independent runs.

26. Simulation Scenarios Network of 2x2 grid of overlapping Each AP has and 40 clients that are distributed uniformly in its coverage area. Infrastructure mode is used. APs are upgraded with S-MAC of 4 sectors (1 Tx & 4 Rx). All STAs still use omni directional antenna (regular 802.11 MAC).

27. Simulation Results Improvement arises from reduced interference with sector antennas and reduced collision from the S-MAC protocol. Total throughput does not change significantly as the number of sectors increases from 2 to 4. No significant change was found with different antenna orientations.

28. Conclusion S-MAC takes full advantage of directional antenna: –Avoids hidden node problem and deafness. –Multiple sectors can be used simultaneously. Fully compatible with regular omni-antenna client nodes. –Easy to upgrade existing 802.11 networks with enhanced access. –Increase the network capacity with minimal cost. –Extendable to utilize smart antenna systems

29. Ideas For ad hoc networks: –Study effect of x% of nodes are S-MAC. –Study the effect of location of S-MAC node  find the optimum set of S-MAC nodes for best performance For Infrastructure: –Best Carrier Sense Threshold for optimal performance Mobility?

30. BACKUP SLIDES

31. Directional Antenna and DMAC (I) Conflict between increased spatial reuse (higher capacity) and increased collision (higher MAC overhead) Collision caused by directional antenna –Hidden nodes due to asymmetry omni/directional gain –Hidden nodes due to unheard RTS or CTS packets –Deafness N1N1 N2N2 N3N3

32. Directional Antenna and DMAC (II) Conflict between increased spatial reuse (higher capacity) and increased collisions (higher MAC overhead) Collisions caused by directional antenna –Hidden nodes due to asymmetry omni/directional gain –Hidden nodes due to unheard RTS or CTS packets –Deafness N1N1 N2N2 N3N3 N4N4

33. MAC Assisted Self-calibration Self-calibration: –Estimate the channel from antenna i to antenna k, both of the same S-MAC node. –Applicable to all PHY (a/b/g). Procedures –Step 1: send RTS in every sector to silence all neighbor nodes, so the SYNC sent next will not collide with other packets. –Step 2: send regular training symbols (SYNC) in every sector. As SYNC is sent from antenna i, antenna k estimate the channel G ik. G ik and G ki can be averaged: G ki = G ik :=(G ki + G ik )/2.