Low complexity linear equalization of doubly selective channel

S. Ghauri, Hasan Humayun, Mobeen Iqbal
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Abstract

A communication system is always prone to impairments, impairments such as noise, inter symbol interference (ISI) etc. are a major threat in channels but they are always compensated by the receiver in communication system. The compensation is usually done by introducing equalization and its different techniques. Submitted paper starts with equalization methods for doubly selective channel. To recognize the technique like Maximum Likelihood (ML), similarly another technique called Zero Forcing (ZF) and finally this paper will focus on Minimum Mean Square Error (MMSE) techniques and its complexity reduction by using Conjugate Gradient method. In MMSE Serial Linear Equalizer (SLE), different windows from channel are taken and recover the original out of it, whereas MMSE Block Linear Equalizer (BLE) recovers the signal from the whole block. MMSE-BLE gives better performance than MMSE-SLE considering values of Bit Error Rate (BER). The channel model considered for MMSE was SISO and MIMO. The performance of MMSE-BLE is enhanced by reducing its complexity by using the iterative methods. We use Conjugate Gradient algorithm, which is one of the best among all the iterative methods.
双选择通道的低复杂度线性均衡
在通信系统中,噪声、码间干扰(ISI)等损伤是信道中的主要威胁,但在通信系统中,这些损伤总是由接收机进行补偿。补偿通常通过引入均衡及其不同的技术来实现。提交的论文从双选择通道的均衡方法开始。为了识别像最大似然(ML)这样的技术,类似的另一种技术称为零强迫(ZF),最后本文将重点介绍最小均方误差(MMSE)技术及其使用共轭梯度方法降低复杂性。在MMSE串行线性均衡器(SLE)中,从信道中提取不同的窗口并从中恢复原始信号,而MMSE块线性均衡器(BLE)从整个块中恢复信号。考虑误码率,MMSE-BLE比MMSE-SLE具有更好的性能。MMSE考虑的信道模型是SISO和MIMO。采用迭代方法降低了MMSE-BLE算法的复杂度,提高了算法的性能。我们使用了共轭梯度算法,它是所有迭代方法中最好的一种。
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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