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

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Abstract

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.

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Correspondence to Dragan Samardzija.

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Keywords

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