1. Load-Aware Spectrum Distribution in Wireless LANs Thomas Moscibroda, Ranveer Chandra, Yunnan Wu, Sudipta Sengupta, Paramvir Bahl, Yuan Yuan Microsoft Research ICNP 2008

2. Outline Introduction Motivation Design Approach Problem Formulation Algorithms Evaluation Conclusions

3. Introduction In IEEE 802.11, the entire available spectrum is divided into smaller channels of equal channel- width (bandwidth)

4. Introduction

5. Previous Approaches - 1 Change associations between clients and access points (APs)

6. Previous Approaches - 1 Change associations between clients and access points (APs)

7. Previous Approaches – 1I Use transmission powers for load balancing

8. Previous Approaches – 1I Use transmission powers for load balancing

9. Previous Approaches – III Coloring: Assign best (least-congested) channel to most- loaded Aps, Reuse some of the channels, weighted coloring

10. Previous Approaches – III Coloring: Assign best (least-congested) channel to most- loaded Aps, Reuse some of the channels, weighted coloring

11. Spectrum assignment The problem with existing approaches is fundamental - Demand at APs very different - But, every AP assigned the same amount of spectrum! (one 20 MHz channel) Our approach:

12. Introduction In this paper, we argue that by moving beyond this fixed channelization structure, the network capacity, spectrum utilization and fairness can be greatly increased ◦ Wider channels for heavily-loaded APs ◦ Narrower channels for lightly-loaded APs

13. Load-Aware Spectrum Allocation Problem definition: 1) Assignment with optimal spectrum utilization: All spectrum to leafs!

14. Load-Aware Spectrum Allocation Problem definition: 2) Assignment with Optimal per-load fairness: Every AP gets half the spectrum

15. Problem Definition AP1, …, APn Conflict graph G=(V,E) describes which APs interfere Every APi has a load Li (e.g. #assigned clients) Spectrum Assignment Problem: Input: 1) AP1,…,APn 2) L1,…,Ln 3) Conflict graph G Output: Assign a channel Ii=[Si, Si+Bi] to every AP

16. Problem Definition

17. Non-Overlapping Channel Non-interfering assignment: An assignment is non-interfering if the channels of no two neighboring APs overlap. Why Non-Overlapping? ◦ Lesser contention overhead, no rate anomaly

18. Why is this problem interesting Traditional channel assignment / frequency assignment problems map to graph coloring problems We must assign contiguous bands to each node

19. Solution 1: ILP Problem is clearly NP-hard in general conflict graphs The problem can be formulated as an ILP

20. Solution 2: Heuristics 1) Determine an ordering O = (AP1,…,APn) over all APs 2) For a given R, … a) … assign each node a channel width b) … check whether these (B1,…,Bn) can be feasibly allocated when greedily packed in the order of O 3) Find largest R, for which greedy packing is feasible (binary search). We looked at several possible orderings O (most-congested first, smallest-last )

21. Evaluations Extensive trace-driven simulations using two-data sets: 1) Small WLAN, monitoring information of 6 APs on floor at MSR 2) Large WLAN, 177 APs in 3 buildings [Balazinska, Castro, Mobisys 2003]

22. Evaluations

23. Conclusions Adaptive Channel Width Simple technology (deployable today!) Provides new knob for optimization Huge potential for performance improvement!