DocumentCode :
768405
Title :
Joint Tx-Rx beamforming design for multicarrier MIMO channels: a unified framework for convex optimization
Author :
Palomar, Daniel Pérez ; Cioffi, John M. ; Lagunas, Miguel Angel
Author_Institution :
Dept. of Signal Theor. & Commun., Univ. Politecnica de Catalunya, Barcelona, Spain
Volume :
51
Issue :
9
fYear :
2003
Firstpage :
2381
Lastpage :
2401
Abstract :
This paper addresses the joint design of transmit and receive beamforming or linear processing (commonly termed linear precoding at the transmitter and equalization at the receiver) for multicarrier multiple-input multiple-output (MIMO) channels under a variety of design criteria. Instead of considering each design criterion in a separate way, we generalize the existing results by developing a unified framework based on considering two families of objective functions that embrace most reasonable criteria to design a communication system: Schur-concave and Schur-convex functions. Once the optimal structure of the transmit-receive processing is known, the design problem simplifies and can be formulated within the powerful framework of convex optimization theory, in which a great number of interesting design criteria can be easily accommodated and efficiently solved, even though closed-form expressions may not exist. From this perspective, we analyze a variety of design criteria, and in particular, we derive optimal beamvectors in the sense of having minimum average bit error rate (BER). Additional constraints on the peak-to-average ratio (PAR) or on the signal dynamic range are easily included in the design. We propose two multilevel water-filling practical solutions that perform very close to the optimal in terms of average BER with a low implementation complexity. If cooperation among the processing operating at different carriers is allowed, the performance improves significantly. Interestingly, with carrier cooperation, it turns out that the exact optimal solution in terms of average BER can be obtained in closed form.
Keywords :
MIMO systems; array signal processing; convex programming; encoding; equalisers; error statistics; optimisation; receiving antennas; transmitting antennas; BER; MIMO channels; PAR; Schur-concave functions; Schur-convex functions; array signal processing; average BER; average bit error rate; carrier cooperation; closed-form expressions; communication system design; convex optimization; convex optimization theory; convex programming; design criteria; equalization; exact optimal solution; implementation complexity; joint Tx-Rx beamforming design; linear precoding; linear processing; multicarrier MIMO channels; multicarrier multiple-input multiple-output channels; multilevel water-filling practical solutions; objective functions; optimal beamvectors; optimal structure; peak-to-average ratio; receive beamforming; receiver; signal dynamic range; transmit beamforming; transmit-receive processing; transmitter; Array signal processing; Bit error rate; Closed-form solution; Communication systems; Design optimization; Dynamic range; MIMO; Peak to average power ratio; Signal design; Transmitters;
fLanguage :
English
Journal_Title :
Signal Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1053-587X
Type :
jour
DOI :
10.1109/TSP.2003.815393
Filename :
1223549
Link To Document :
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