Spatial multiplexing and channel statistics-based RF pre-processing for antenna selection

Abstract

For a multiple input multiple output system, antenna selection reduces complexity at the expense of performance. In this paper, we propose two novel RF pre-processing architectures that significantly improve the performance of antenna selection, which marginally increasing the complexity. These architectures introduce a RF pre-processing matrix, M, that multiplies the vector of incoming signals prior to down-conversion. The elements of M use only the knowledge of the channel statistics. In the first architecture, M outputs a reduced number of streamsan explicit selection algorithm is therefore not required. In the second architecture, the number of output streams equals the number of input streams, and a selection switch that uses instantaneous channel state information achieves the reduction of the number of streams. We show that the optimal pre-processing receiver projects the received signal along the eigenvectors of the correlation matrix. In a correlated channel, both these architectures significantly outperform conventional antenna selection. We also develop a beam-pattern based intuition and compare the performance of our scheme to other RF pre-processing schemes previously proposed in the literature. Globecom 2004This work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of Mitsubishi Electric Research Laboratories, Inc.; an acknowledgment of the authors and individual contributions to the work; and all applicable portions of the copyright notice. Copying, reproduction, or republishing for any other purpose shall require a license with payment of fee to Mitsubishi Electric Research Laboratories, Inc. All rights reserved. Abstract-For a multiple input multiple output system, antenna selection reduces complexity at the expense of performance. In this paper, we propose two novel RF pre-processing architectures that significantly improve the performance of antenna selection, which marginally increasing the complexity. These architectures introduce a RF pre-processing matrix, M, that multiplies the vector of incoming signals prior to downconversion. The elements of M use only the knowledge of the channel statistics. In the first architecture, M outputs a reduced number of streams -an explicit selection algorithm is therefore not required. In the second architecture, the number of output streams equals the number of input streams, and the reduction of the number of streams is achieved by a selection switch that uses instantaneous channel state information. We show that the optimal pre-processing receiver projects the received signal along the eigenvectors of the correlation matrix. In a correlated channel, both these architectures significantly outperform conventional antenna selection. We also develop a beam-pattern based intuition and comp...

A Partial MRT Algorithm for Closed-Loop Spatial Multiplexing Systems with Transmit Antenna Selection

“…Ref [9] considers the case when beamforming matrix can tune to the instantaneous channel state information (CSI). For slowly varying wireless channels, a novel RF pre-rocessing architecture was propose in [10] that uses the knowledge of only the channel statistics.…”

“…These decoding algorithms consist of maximum likelihood receiver, linear receivers and ordered Successive Interference Cancellation receiver. Recently for the use of CSI at the transmitter, transmit beamforming methods [9,10] were added in the systems to recover the beamforming gain loss by conventional antenna selection. Ref [9] considers the case when beamforming matrix can tune to the instantaneous channel state information (CSI).…”