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Load-Aware Spectrum Distributionin Wireless LANs
Thomas Moscibroda, Ranveer Chandra, Yunnan Wu, Sudipta Sengupta, Paramvir Bahl, Yuan Yuan
Microsoft Research
ICNP 2008
IntroductionIn IEEE 802.11, the entire available
spectrum is divided into smaller channels of equal channel-width (bandwidth)
Previous Approaches – III Coloring: Assign best (least-congested) channel
to most-loaded Aps, Reuse some of the channels, weighted coloring
Previous Approaches – III Coloring: Assign best (least-congested) channel
to most-loaded Aps, Reuse some of the channels, weighted coloring
Spectrum assignmentThe 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:
IntroductionIn 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
Load-Aware Spectrum Allocation
Problem definition:
1) Assignment withoptimal spectrum utilization:All spectrum to leafs!
Load-Aware Spectrum Allocation
Problem definition:
2) Assignment with Optimal per-load fairness:Every AP gets halfthe spectrum
Problem DefinitionAP1, … , APnConflict graph G=(V,E) describes which
APs interfereEvery 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
Non-Overlapping ChannelNon-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
Why is this problem interestingTraditional channel assignment /
frequency assignment problems map to graph coloring problems
We must assign contiguous bands to each node
Solution 1: ILPProblem is clearly NP-hard in general
conflict graphsThe problem can be formulated as an
ILP
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 )
Evaluations Extensive trace-driven simulations using two-
data sets: 1) Small WLAN, monitoring information of 6 APs
on floor at MSR2) Large WLAN, 177 APs in 3 buildings
[Balazinska, Castro, Mobisys 2003]
ConclusionsAdaptive Channel Width
Simple technology (deployable today!)
Provides new knob for optimization
Huge potential for performance improvement!
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