MIMO systems equalization in Flat fading

A. Grover, B. Sangar, Rohit Gupta, Neeti Grover
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引用次数: 1

Abstract

The main challenges in the design of wireless communication systems are the limited resources, such as constrained transmission power, scarce frequency bandwidth, and limited implementation complexity-and the impairments of the wireless channels, including noise, interference, and fading effects. Multiple-Input-Multiple-Output (MIMO) communication has been shown to be one of the most promising emerging wireless technologies that can efficiently boost the data transmission rate, improve system coverage, and enhance link reliability. Equalization is a well known technique for combating inter-symbol interference. In this paper, we are considering the equalization; a filtering approach that minimizes the error between actual output and desired output by continuous updating its filter coefficients. Moreover, this article compares the performance of MIMO Systems in Rayleigh and Rician Flat fading channels. We observed that the successive interference methods provide better performance as compare to others, but their complexity is high. Simulation results shows that ML equalizer with BPSK gives better performance as compare to QPSK. Finally we concluded that Sphere decoder provides the best performance.
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MIMO系统的平坦衰落均衡
无线通信系统设计面临的主要挑战是有限的资源,如受限的传输功率、稀缺的频率带宽和有限的实现复杂性,以及无线信道的缺陷,包括噪声、干扰和衰落效应。多输入多输出(MIMO)通信已被证明是最有前途的新兴无线技术之一,它可以有效地提高数据传输速率,提高系统覆盖范围,提高链路可靠性。均衡是一种众所周知的对抗符号间干扰的技术。在本文中,我们考虑均衡化;一种过滤方法,通过不断更新其过滤系数,使实际输出和期望输出之间的误差最小化。此外,本文还比较了MIMO系统在瑞利和瑞利平坦衰落信道下的性能。我们发现,逐次干扰方法的性能优于其他方法,但其复杂度较高。仿真结果表明,与QPSK相比,BPSK的ML均衡器具有更好的性能。最后得出球体解码器提供了最好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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