Pre-LNA smart soft antenna selection for MIMO spatial multiplexing/diversity system when amplifier/sky noise dominates

J. Ahmadi-shokouh, S. H. Jamali, S. Safavi-Naeini
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引用次数: 6

Abstract

Due to a beamforming capability, Soft Antenna Selection (SAS) techniques have shown great performance improvements over the traditional antenna sub-set selection schemes for Multi-Input and Multi-Output (MIMO) communication systems. A SAS method is basically defined by a pre-processing matrix which is located in RF domain, either before or after the Low Noise Amplifier (LNA). In this paper, we propose a pre-LNA SAS module which is adaptively tuned to maximise the mutual information or the Signal to Noise Ratio (SNR) gain for spatial multiplexing or diversity transmissions, respectively. The SAS optimality is discussed for the two practical cases where either the sky noise or the amplifier noise dominates. We analytically show that the pre-LNA SAS method even outperforms the full-complexity MIMO system for when the number of receive Radio Frequency (RF) chains is greater than or equal to the number of the transmit RF chains. The simulation results verify this claim and also superiority of the proposed scheme to the post-LNA SAS. Copyright © 2010 John Wiley & Sons, Ltd.
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放大器/天空噪声占主导的MIMO空间复用/分集系统的预lna智能软天线选择
由于具有波束形成能力,软天线选择(SAS)技术在多输入多输出(MIMO)通信系统中比传统的天线子集选择方案表现出了很大的性能改进。SAS方法基本上是由位于RF域的预处理矩阵定义的,该预处理矩阵位于低噪声放大器(LNA)之前或之后。在本文中,我们提出了一种预lna SAS模块,该模块可自适应调谐,分别用于空间复用或分集传输,以最大化互信息或信噪比(SNR)增益。针对天空噪声或放大器噪声占主导地位的两种实际情况,讨论了SAS的最优性。分析表明,当接收射频链的数量大于或等于发射射频链的数量时,pre-LNA SAS方法甚至优于全复杂度MIMO系统。仿真结果验证了这一说法,也证明了该方案相对于后lna SAS的优越性。版权所有©2010 John Wiley & Sons, Ltd
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