Weighted Sum Rate Maximization for MIMO Broadcast Channels Using Dirty Paper Coding and Zero-forcing Methods

We consider precoder design for maximizing the weighted sum rate (WSR) of successive zero-forcing dirty paper coding (SZF-DPC). For this problem, the existing precoder designs often assume a sum power constraint (SPC) and rely on the singular value decomposition (SVD). The SVD-based designs are know...

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Veröffentlicht in:	IEEE transactions on communications Jg. 61; H. 6; S. 2362 - 2373
Hauptverfasser:	Tran, Le-Nam, Juntti, Markku, Bengtsson, Mats, Ottersten, Bjorn
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York, NY IEEE 01.06.2013 Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithm design and analysis Algorithms Antennas Applied sciences broadcast channels Broadcasting. Videocommunications. Audiovisual Coding Coding, codes Complexity theory Convergence Decomposition dirty paper coding Encoding Exact sciences and technology Information, signal and communications theory Maximization MIMO MIMO systems Miscellaneous multiuser multi-antenna communication Numerical analysis Optimization Radiocommunications Receivers Signal and communications theory Statistical process control Studies Systems, networks and services of telecommunications Telecommunications Telecommunications and information theory Transmission and modulation (techniques and equipments) Transmitting antennas Vectors zero-forcing MIMO system Multiple access Diagonalization dirty paper coding Coding circuit Interior point method Numerical method Optimization Optimal design MIMO systems zero-forcing Relaxation multiuser multi-antenna communication Covariance Algorithm performance Coding QR factorization Broadcast channels Convergence rate Numerical algorithm Antenna Singular value decomposition
ISSN:	0090-6778, 1558-0857, 1558-0857
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Zusammenfassung:	We consider precoder design for maximizing the weighted sum rate (WSR) of successive zero-forcing dirty paper coding (SZF-DPC). For this problem, the existing precoder designs often assume a sum power constraint (SPC) and rely on the singular value decomposition (SVD). The SVD-based designs are known to be optimal but require high complexity. We first propose a low-complexity optimal precoder design for SZF-DPC under SPC, using the QR decomposition. Then, we propose an efficient numerical algorithm to find the optimal precoders subject to per-antenna power constraints (PAPCs). To this end, the precoder design for PAPCs is formulated as an optimization problem with a rank constraint on the covariance matrices. A well-known approach to solve this problem is to relax the rank constraints and solve the relaxed problem. Interestingly, for SZF-DPC, we are able to prove that the rank relaxation is tight. Consequently, the optimal precoder design for PAPCs is computed by solving the relaxed problem, for which we propose a customized interior-point method that exhibits a superlinear convergence rate. Two suboptimal precoder designs are also presented and compared to the optimal ones. We also show that the proposed numerical method is applicable for finding the optimal precoders for block diagonalization scheme.
Bibliographie:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23
ISSN:	0090-6778 1558-0857 1558-0857
DOI:	10.1109/TCOMM.2013.043013.130100