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Joint tx-rx beamforming design for multicarrier mimo channels: a unified framework for convex optimization

IEEE Transactions on Signal Processing · 2003 · Vol. 51(9) · pp. 2381–2401
Daniel P. PalomarJ.M. CioffiM.A. Lagunas

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.

Advanced MIMO Systems OptimizationAdvanced Wireless Communication TechniquesWireless Communication Networks ResearchBeamformingPrecodingMIMOTransmitterMathematical optimizationComputer scienceConvex optimizationOptimization problemControl theory (sociology)Mathematics

Funding

  • European Commission
Citations
1,215
FWCI
44.84
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References
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IEEE Transactions on Signal Processing · 2002 · 828 citations
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IEEE Transactions on Communications · 1998 · 1,467 citations
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