DocumentCode :
3070652
Title :
A Minimax Regret Approach to Robust Beamforming
Author :
Byun, Jungsub ; Mutapcic, Almir ; Kim, Seung-Jean ; Cioffi, John M.
Author_Institution :
Dept. of Electr. Eng., Stanford Univ., Stanford, CA, USA
fYear :
2009
fDate :
20-23 Sept. 2009
Firstpage :
1
Lastpage :
6
Abstract :
Abstract-This article describes a minimax regret approach to robust beamforming with an ellipsoidal uncertainty model for a steering vector, in which the objective is to minimize the worstcase regret over the uncertainty set, where ´worst´ means largest. This problem can be solved efficiently by using an iterative method which uses an alternating sequence of optimization and worst-case analysis steps. Each of the two steps amounts to solving a convex optimization problem. The method typically converges to a solution within 5 iterations. The minimax regret beamforming is illustrated with numerical examples in planar random array antennas. The numerical results show that the minimax regret approach is less pessimistic (less conservative) and provides more robust performance than the worst-case SINR maximization (maximin) approach, where ´worst´ means smallest.
Keywords :
iterative methods; planar antenna arrays; convex optimization problem; ellipsoidal uncertainty model; iterative method; minimax regret beamforming; planar random array antennas; robust beamforming; steering vector; Antenna arrays; Array signal processing; Decision making; Minimax techniques; Optimization methods; Performance loss; Robustness; Sensor arrays; Signal to noise ratio; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Vehicular Technology Conference Fall (VTC 2009-Fall), 2009 IEEE 70th
Conference_Location :
Anchorage, AK
ISSN :
1090-3038
Print_ISBN :
978-1-4244-2514-3
Electronic_ISBN :
1090-3038
Type :
conf
DOI :
10.1109/VETECF.2009.5378979
Filename :
5378979
Link To Document :
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