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  • Research Article
  • Open Access

Adaptive Transmitter Optimization in Multiuser Multiantenna Systems: Theoretical Limits, Effect of Delays, and Performance Enhancements

EURASIP Journal on Wireless Communications and Networking20052005:929730

  • Received: 6 March 2005
  • Published:


The advances in programmable and reconfigurable radios have rendered feasible transmitter optimization schemes that can greatly improve the performance of multiple-antenna multiuser systems. Reconfigurable radio platforms are particularly suitable for implementation of transmitter optimization at the base station. We consider the downlink of a wireless system with multiple transmit antennas at the base station and a number of mobile terminals (i.e., users) each with a single receive antenna. Under an average transmit power constraint, we consider the maximum achievable sum data rates in the case of (1) zero-forcing (ZF) spatial prefilter, (2) modified zero-forcing (MZF) spatial prefilter, and (3) triangularization spatial prefilter coupled with dirty-paper coding (DPC) transmission scheme. We show that the triangularization with DPC approaches the closed-loop MIMO rates (upper bound) for higher SNRs. Further, the MZF solution performs very well for lower SNRs, while for higher SNRs, the rates for the ZF solution converge to the MZF rates. An important impediment that degrades the performance of such transmitter optimization schemes is the delay in channel state information (CSI). We characterize the fundamental limits of performance in the presence of delayed CSI and then propose performance enhancements using a linear MMSE predictor of the CSI that can be used in conjunction with transmitter optimization in multiple-antenna multiuser systems.


  • transmitter beamforming
  • dirty-paper coding
  • correlated channels
  • channel state information
  • MMSE prediction

Authors’ Affiliations

Wireless Research Laboratory, Bell Labs, Lucent Technologies, 791 Holmdel-Keyport Road, Holmdel, NJ 07733, USA
Wireless Information Network Laboratory (WINLAB), Rutgers University, 73 Brett Road, Piscataway, NJ 08854-8060, USA


© Dragan Samardzija et al. 2005

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.