Adaptive Transmitter Optimization in Multiuser Multiantenna Systems: Theoretical Limits, Effect of Delays, and Performan
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Adaptive Transmitter Optimization in Multiuser Multiantenna Systems: Theoretical Limits, Effect of Delays, and Performance Enhancements Dragan Samardzija Wireless Research Laboratory, Bell Labs, Lucent Technologies, 791 Holmdel-Keyport Road, Holmdel, NJ 07733, USA Email: [email protected]
Narayan Mandayam Wireless Information Network Laboratory (WINLAB), Rutgers University, 73 Brett Road, Piscataway, NJ 08854-8060, USA Email: [email protected]
Dmitry Chizhik Wireless Research Laboratory, Bell Labs, Lucent Technologies, 791 Holmdel-Keyport Road, Holmdel, NJ 07733, USA Email: [email protected] Received 6 March 2005; Revised 21 April 2005 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 dirtypaper 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. Keywords and phrases: transmitter beamforming, dirty-paper coding, correlated channels, channel state information, MMSE prediction.
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INTRODUCTION
For a wide range of emerging wireless data services, the application of multiple antennas appears to be one of the most promising solutions leading to even higher data rates and/or the ability to support greater number of users. Multiple-transmit multiple-receive antenna systems represent an implementation of the MIMO (multiple-input multiple-output) concept in wireless communications [1] 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.
that can provide high-capacity (i.e., spectral efficiency) wireless communications in rich scattering environments. It has been shown that the theoretical capacity (approximately) increa
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