NDLI: Efficient Beamforming in Cognitive Radio Multicast Transmission

Content Provider	IEEE Xplore Digital Library
Author	Beko, M.
Copyright Year	2002
Abstract	The optimal beamforming problems for cognitive multicast transmission are quadratic nonconvex optimization problems. The standard approach is to convert the problems into the form of semi-definite programming (SDP) with the aid of rank relaxation and later employ randomization techniques for solution search. However, in many cases, this approach brings solutions that are far from the optimal ones. We consider the problem of minimizing the total power transmitted by the antenna array subject to quality-of-service (QoS) at the secondary receivers and interference constraints at the primary receivers. It is shown that this problem, which is known to be nonconvex NP-hard, can be approximated by a convex second-order cone programming (SOCP) problem. Then, an iterative algorithm in which the SOCP approximation is successively improved is presented. Simulation results demonstrate the superior performance of the proposed approach in terms of total transmitted power and feasibility, together with a reduced computational complexity, as compared to the existing ones, for both the perfect and imperfect channel state information (CSI) cases. It is further shown that the proposed approach can be used to address the max-min fairness (MMF) based beamforming problem.
Starting Page	4108
Ending Page	4117
Page Count	10
File Size	240268
File Format	PDF
ISSN	15361276
Volume Number	11
Issue Number	11
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-11-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Array signal processing Optimization Receivers Signal to noise ratio Interference Robustness Vectors convex-concave procedure Cognitive radio beamforming second-order cone programming problem MIMO
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Electrical and Electronic Engineering Computer Science Applications

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