Channel Assignment for WLAN by Considering Overlapping Channels

Channel Assignment for WLAN by Considering Overlapping Channels in SINR Model Kunxiao Zhou and Xiaohua Jia City University of Hong Kong

Outlines Introduction n Related work n Problem formulation n Proposed solution n Simulation results n Conclusion n 2

Introduction n Channel assignment q q n Partially overlapping channels (802. 11 b) q q n Wireless Local Area Networks (WLANs) Access points (APs), clients Basic service set (BSS) Assign channels to BSSs 11 partially overlapping channels 3 non-overlapping (orthogonal) channels SINR model q q Accumulative nature of interference Most of combinatorial optimization techniques based on protocol model are not applicable 3

Related work n A. Mishra, V. Shrivastava, S. Banerjee, and W. Arbaugh, “Partially overlapped channels not considered harmful, ” SIGMetrics/Performance, 2006, pp. 63– 74. q q n Y. Cui, W. Li, and X. Cheng, “Partially overlapping channel assignment based on “node orthogonality” for 802. 11 wireless networks, ” Mini-Conference at IEEE INFOCOM, 2011. q n Interference of overlapping channels Communication btwn two nodes by using overlapping channels interference model: two nodes interfering or not depends on channel distance and physical distance bwtn two nodes (i. e. “node orthogonality”) A. Mishra, S. Banerjee, and W. Arbaugh, “Weighted coloring based channel assignment for wlans”, in ACM Sigmobile MC 2 R, 2005 q ADJ-minmax and ADJ-sum 4

Problem Formulation n Infrastructure-based IEEE 802. 11 WLAN, 5

Problem Formulation (cont’d) n W= {w 1, …, wm}: set of APs; U= {u 1, …, un}: set of clients; F= {f 1, f 2, … , fk}: set of overlapping channels; BSS: AP and its associated clients G(U ∪ W, E) , (u, w) ∈ E: client u connects to AP w; γ(v, u): overlapping degree btwn channels of node v and u. n Channel overlapping degree: n n 6

Problem Formulation (cont’d) n Data rate: n The throughput of a BSS : n Throughput of the system: 7

Problem Formulation (cont’d) n Total interference of u received from all APs: n Total interference of all clients in the system: n Maximize the system throughput is equivalent to minimizing system total interference 8

Algorithm Design Interference analysis: n Interference caused by AP v to client u (u S(v)) n Interference by AP v to all clients in a BSS Bw, n We only consider downlink case, 9

Algorithm Design (cont’d) n Fig. 2, weighted interference graph GI(VI, EI) 10

Algorithm Design (cont’d) n Total weights of all edges in GI(VI, EI) , n The total weight of all edges in GI is equal to the total interference of the system. Our problem is converted to minimizing the total weight of all edges in GI(VI, EI) n 11

Algorithm Design (cont’d) n Heuristic method 12

Simulation Results (throughput) 13

Simulation Results (service ratio) 14

Simulation Results (per-user throughput) 15

Simulation Results (channel utilization) 16

Conclusions n n Studied channel assignment by considering partially overlapping channels in SINR model; Converted the maximal throughput problem to minimizing total edge weight of the interference graph; Proposed a heuristic method; Channel overlapping attenuation coefficient is a major factor to affect the channel utilization. 17

Thanks! Q&A 18