DocumentCode :
1471177
Title :
Achieving Global Optimality for Weighted Sum-Rate Maximization in the K-User Gaussian Interference Channel with Multiple Antennas
Author :
Liu, Liang ; Zhang, Rui ; Chua, Kee-Chaing
Author_Institution :
Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore, Singapore
Volume :
11
Issue :
5
fYear :
2012
fDate :
5/1/2012 12:00:00 AM
Firstpage :
1933
Lastpage :
1945
Abstract :
Characterizing the global maximum of weighted sum-rate (WSR) for the K-user Gaussian interference channel (GIC), with the interference treated as Gaussian noise, is a key problem in wireless communication. However, due to the users\´ mutual interference, this problem is in general non-convex and thus cannot be solved directly by conventional convex optimization techniques. In this paper, by jointly utilizing the monotonic optimization and rate profile techniques, we develop a new framework to obtain the globally optimal power control and/or beamforming solutions to WSR maximization problems for the GICs with single-antenna transmitters and single-antenna receivers (SISO), single-antenna transmitters and multi-antenna receivers (SIMO), or multi-antenna transmitters and single-antenna receivers (MISO). Different from prior work, this paper proposes to maximize the WSR in the achievable rate region of the GIC directly by exploiting the facts that the achievable rate region is a "normal" set and the users\´ WSR is a strictly increasing function over the rate region. Consequently, the WSR maximization is shown to be in the form of monotonic optimization over a normal set and thus can be solved globally optimally by the existing outer polyblock approximation algorithm. However, an essential step in the algorithm hinges on how to efficiently characterize the intersection point on the Pareto boundary of the achievable rate region with any prescribed "rate profile" vector. This paper shows that such a problem can be transformed into a sequence of signal-to-interference-plus-noise ratio (SINR) feasibility problems, which can be solved efficiently by applying existing techniques. Numerical results validate that the proposed algorithms can achieve the global WSR maximum for the SISO, SIMO or MISO GIC, which serves as a performance benchmark for other heuristic algorithms.
Keywords :
Gaussian channels; Pareto optimisation; antenna arrays; approximation theory; concave programming; convex programming; radio receivers; radio transmitters; receiving antennas; transmitting antennas; K-user GIC; K-user Gaussian interference channel; MISO GIC; Pareto boundary; SIMO; SINR; SISO; WSR maximization problems; beamforming solutions; convex optimization techniques; globally optimal power control; heuristic algorithms; monotonic optimization techniques; multiantenna receivers; multiantenna transmitters; multiple antennas; nonconvex problem; outer polyblock approximation algorithm; rate profile techniques; signal-to-interference-plus-noise ratio; single-antenna receivers; single-antenna transmitters; weighted sum-rate maximization; wireless communication; Approximation algorithms; Approximation methods; Array signal processing; Interference; Receivers; Transmitters; Vectors; Beamforming; interference channel; multi-antenna system; non-linear optimization; power control; weighted sum-rate maximization;
fLanguage :
English
Journal_Title :
Wireless Communications, IEEE Transactions on
Publisher :
ieee
ISSN :
1536-1276
Type :
jour
DOI :
10.1109/TWC.2012.031212.111585
Filename :
6170850
Link To Document :
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