Comparisons of Receive Array Interference Reduction Techniques Under Erroneous Generalized Transmit Beamforming

This paper studies generalized single-stream transmit beamforming employing receive array co-channel interference reduction algorithms under slow and flat fading multiuser wireless systems. The impact of imperfect prediction of channel state information for the desired user spatially uncorrelated transmit channels on the effectiveness of transmit beamforming for different interference reduction techniques is investigated. The case of over-loaded receive array with closely-spaced elements is considered, wherein it can be configured to null specified interfering sources. Both dominant interference reduction and adaptive interference reduction techniques for statistically ordered and unordered interferers powers, respectively, are thoroughly studied. The effect of outdated statistical ordering of the interferers powers on the efficiency of dominant interference reduction is studied and then compared against the adaptive interference reduction. For the system models described above, new analytical formulations for the statistics of combined signal-to-interference-plus-noise ratio are presented, from which results for conventional maximum ratio transmission and single-antenna best transmit selection can be directly deduced as limiting cases. These results are then utilized to obtain quantitative measures for various performance metrics. They are also used to compare the achieved performance of various configuration models under consideration.

I. Introduction

THE use of multiple-antenna arrays in wireless systems have been shown to improve the spatial coverage and communication reliability. Some of the benefits include spatial multiplexing gain and diversity gain [1]. It has been also predicated that the performance of multiple-antenna systems can be improved if the channel state information (CSI) is available to the transmitter [2]. One of the multiple-antennas techniques that has received considerable attention is a closed-loop diversity scheme, which is referred to as single-stream transmit beamforming, maximum-ratio transmission (MRT) [3], or multiple-input multiple-output maximum-ratio combining (MIMO MRC).