DocumentCode :
1420781
Title :
Convex Approximation Algorithms for Back-Pressure Power Control
Author :
Matskani, Evaggelia ; Sidiropoulos, Nicholas D. ; Tassiulas, Leandros
Author_Institution :
Dept. of Electron. & Comput. Eng., Tech. Univ. of Crete, Chania, Greece
Volume :
60
Issue :
4
fYear :
2012
fDate :
4/1/2012 12:00:00 AM
Firstpage :
1957
Lastpage :
1970
Abstract :
Throughput-optimal multihop wireless network operation entails a key physical-layer optimization problem: maximizing a weighted sum of link rates, with weights given by the differential queue backlogs. This emerges in joint back-pressure routing and power control, which is central in cross-layer wireless networking. We begin by showing that the core problem is not only nonconvex, but also NP-hard. This is a negative result, which however comes with a positive flip side: drawing from related developments in the digital subscriber line (DSL) literature, we propose effective ways to approximate it. Exploiting quasi-periodicity of the power allocation in stable setups due to the push-pull nature of the solution, we derive two custom algorithms that offer excellent throughput performance at reasonable, worst-case polynomial complexity. Judicious simulations illustrate the merits of the proposed algorithms.
Keywords :
approximation theory; convex programming; digital subscriber lines; polynomials; power control; pressure control; radio networks; telecommunication control; telecommunication network routing; DSL literature; NP-hard; back-pressure power control; convex approximation algorithms; differential queue backlogs; digital subscriber line literature; joint back-pressure routing; positive flip side; power allocation; throughput-optimal multihop wireless network operation; worst-case polynomial complexity; Approximation algorithms; Approximation methods; Complexity theory; Interference; Optimization; Power control; Throughput; Back-pressure routing; NP-hard problems; convex approximation; cross-layer design; digital subscriber line (DSL); dynamic spectrum management; network optimization; power control; utility maximization;
fLanguage :
English
Journal_Title :
Signal Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1053-587X
Type :
jour
DOI :
10.1109/TSP.2012.2184097
Filename :
6129545
Link To Document :
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