NDLI: Convex primal decomposition for multicarrier linear MIMO transceivers

Content Provider	IEEE Xplore Digital Library
Author	Palomar, D.P.
Copyright Year	1991
Abstract	The design of linear transceivers for multiple-input-multiple-output (MIMO) communication systems with channel state information is particularly challenging for two main reasons. First, since several substreams are established through the MIMO channel, it is not even clear how the quality of the system should be measured. Second, once a cost function has been chosen to measure the quality, the optimization of the system according to such criterion is generally difficult due to the nonconvexity of the problem. Recent results have solved the problem for the wide family of Schur-concave/convex functions, resulting in simple closed-form solutions when the system is modeled as a single MIMO channel. However, with several MIMO channels (such as in multi-antenna multicarrier systems), the solution is generally more involved, leading in some cases to the need to employ general-purpose interior-point methods. This problem is specifically addressed in this paper by combining the closed-form solutions for single MIMO channels with a primal decomposition approach, resulting in a simple and efficient method for multiple MIMO channels. The extension to functions that are not Schur-concave/convex is also briefly considered, relating the present work with a recently proposed method to minimize the average bit error rate (BER) of the system.
Sponsorship	IEEE Signal Processing Society
Starting Page	4661
Ending Page	4674
Page Count	14
File Size	488430
File Format	PDF
ISSN	1053587X
Volume Number	53
Issue Number	12
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-12-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	MIMO Transceivers Bit error rate Channel state information Closed-form solution DSL Transmitters Employment Communication systems Cost function waterfilling Convex optimization theory linear precoder majorization theory multicarrier transceiver multiple-input–multiple-output (MIMO) channel primal decomposition technique Schur convexity
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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