复杂性降低了大规模MIMO系统中的零强迫波束形成

Chan-Sic Park, Yong-Suk Byun, A. Bokiye, Yong-Hwan Lee
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引用次数: 29

摘要

数据采集是多跳无线传感器网络中最受欢迎的应用之一。大规模多输入多输出(m-MIMO)系统可以提供高度的信号传输自由度,能够以高传输容量同时为多个用户服务。传统的零强迫波束形成技术可以在传输多用户信号的同时完全消除波束间干扰。然而,在m-MIMO系统中应用时,由于处理复杂性大,可能存在实现困难。在本文中,我们设计了一种通过顺序干扰抵消来降低复杂度的ZFBF方案。我们首先根据传统的最大比传输(MRT)方案确定光束权重,并计算相应的光束间干扰。我们通过按最强干扰的顺序依次消除预定数量的干扰源来计算所谓的干扰抵消矢量。最后,我们通过将干涉抵消矢量加入到MRT波束权重中来确定波束权重。考虑到处理的复杂性和所需的性能,可以预先确定要消除的光束间干扰的数量。随着需要消除的梁间干扰数量的增加,所提方案的性能逐渐接近ZFBF。数值和仿真结果表明,在使用32128发射天线的各种工作环境下,该方案可达到ZFBF容量的90%左右,而处理复杂度仅为ZFBF的2~7%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Complexity reduced zero-forcing beamforming in massive MIMO systems
Data gathering is one of the most popular applications in multi-hop wireless sensor networks. Since resources are limited, it is important to efficiently allocate the resource Massive multi-input multi-output (m-MIMO) systems can provide a high degree of freedom in signal transmission, enabling to simultaneously serve a number of users with high transmission capacity. Conventional zero-forcing beamforming (ZFBF) techniques can transmit multi-user signal while completely canceling out interbeam interference. However, they may have implementation difficulty when applied to m-MIMO systems mainly due to hugh processing complexity. In this paper, we design a complexity reduced ZFBF scheme by means of sequential interference cancellation. We first determine the beam weight according to the use of conventional maximum ratio transmission (MRT) scheme and calculate the corresponding interbeam interference. We calculate so-called an interference cancellation vector by sequentially cancelling out a predetermined number of interference sources in an order of the strongest interference. Finally, we determine the beam weight by adding the interference cancellation vector to the MRT beam weight. The number of interbeam interferences to be cancelled out can be pre-determined taking into consideration of the processing complexity and required performance. As the number of interbeam interferences to be cancelled out increases, the performance of the proposed scheme approaches to that of ZFBF. The numerical and simulation results show that the proposed scheme can achieve about 90 % capacity of ZFBF while requiring 2~7% processing complexity of ZFBF in various operating environments with the use of 32 128 transmit antennas.
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