Paper Info
Title
Radio Channel Allocations With Global Optimality and Bounded Computational Scale.
Abstract
The radio channel assignment (RCA) in wireless networks is an optimization problem that is often found NP-complete. For networks of practical sizes, various heuristic algorithms are used to solve it. However, there are two major issues: finding a globally optimized solution without relying on specific interference models and estimating the computational complexity of general heuristic algorithms. In this paper, we propose a new simulated annealing (SA)-based RCA (SRCA) algorithm to find the globally optimized channel assignment in a distributed way but with bounded computational complexity. We propose using effective channel utilization (ECU) as the evaluation vector, whereas the objective function is to maximize the total ECU in a neighborhood. The ECU can be easily calculated by an access point (AP). The impact of interference is included in the ECU. We propose a hybrid method for estimating the algorithm's computational scale (CS), i.e., the number of channel reallocations until the network reaches a convergence state, by combining analytical and experimental methods. The resulting algorithm is a dynamic and distributed algorithm. Our extensive simulation results have demonstrated that it quickly achieves 99% of the global maximum with a chance over 95%, whereas its complexity is linear with the number of routers in the network.
Year
DOI
Venue
2014
10.1109/TVT.2014.2311922
IEEE T. Vehicular Technology
Keywords
DocType
Volume
Interference,Channel allocation,Optimization,Vectors,Linear programming,Channel estimation,Convergence
Journal
63
Issue
ISSN
Citations 
9
0018-9545
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Ming Yu111310.43
Xiaoguang Ma200.68
MengChu Zhou38989534.94