No abstract

No abstract

-This paper studies optimum signal combining for space diversity reception in cellular mobile radio systems. With optimum combining, the signals received by the antennas are weighted and combined to maximize the output signal-to-interference-plus-noise ratio. Thus, with cochanne1 interference, space diversity is used not only to combat Rayleigh fading of the desired signal (as with maximal ratio combining) but also to reduce the power of interfering signals at the receiver. We use analytical and computer simulation techniques to determine the performance of optimum combining when the received desired and interfering signals are subject to Rayleigh fading. Results show that optimum combining is significantly better than maximal ratio combining even when the number of interferers is greater than the number of antennas. Results for typical .cellular mobile radio systems show that optimum combining increases the output signalto-interference ratio at the receiver by several decibels. Thus, systems can require fewer base slation antennas and/or achieve increased channel capacity through greater frequency reuse. We also describe techniques for implementing optimum combining with least mean square (LMS) adaptive arrays.

No abstract

We consider the capacity of multiple-input multiple-output systems with reduced complexity. One link-end uses all available antennas, while the other chooses the L out of N antennas that maximize capacity. We derive an upper bound on the capacity that can be expressed sa sthe sum of the logarithms of ordered chi-square-distributed variables. This bound is then evaluated analytically and compared to the results obtained by Monte Carlo simulations. Our results show that the achieved capacity is close to the capacity of a full-complexity system provided that L is at least as large as the number of antennas at the other link-end. For example, for L=3, N=8 antennas at the receiver and three antennas at the transmitter, the capacity of the reduced-complexity scheme is 20 bits/s/Hz compared to 23 bits/s/Hz of a full-complexity scheme. We also present a suboptimum antenna subset selection algorithm that has a complexity of N2 compared to eht optimum algorithm with a complexity of (N L). IEEE Transactions on Wireless CommunicationsThis 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-We consider the capacity of multiple-input multipleoutput systems with reduced complexity. One link-end uses all available antennas, while the other chooses the L out of N antennas that maximize capacity. We derive an upper bound on the capacity that can be expressed as the sum of the logarithms of ordered chi-square-distributed variables. This bound is then evaluated analytically and compared to the results obtained by Monte Carlo simulations. Our results show that the achieved capacity is close to the capacity of a full-complexity system provided that L is at least as large as the number of antennas at the other linkend. For example, for L = 3, N = 8 antennas at the receiver and three antennas at the transmitter, the capacity of the reducedcomplexity scheme is 20 bits/s/Hz compared to 23 bits/s/Hz of a full-complexity scheme. We also present a suboptimum antenna subset selection algorithm that has a complexity of N 2 compared to the optimum algorithm with a complexity of N L .