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Fading performance evaluation of a semi-blind space-time equaliser for frequency selective MIMO systems

机译:用于频率选择性mImO系统的半盲时空均衡器的衰落性能评估

摘要

A semi-blind adaptive space–time equaliser (STE) has recently been proposed based on a concurrent gradient-Newton(GN) constant modulus algorithm (CMA) and soft decision-directed (SDD) scheme for dispersive multiple-input multiple-output (MIMO) systems that employ high-throughput quadrature amplitude modulation signalling. A minimum number of training symbols, approximately equal to the dimension of the STE, is used to provide a rough initial estimate of the STE’s weight vector. The concurrent GN based CMA and SDD blind adaptive scheme is then adopted to adapt the STE. This semi-blind STE has a complexity similar to that of the training-based recursive least squares (RLS) algorithm. For stationary MIMO channels, it has been demonstrated that this semi-blind adaptive STE is capable of converging fast to the optimal minimum mean square error STE solution. In this contribution, we investigate the performance of this semi-blind adaptive STE operating in Rayleigh fading MIMO systems. Our results obtained show that the tracking performance of this semi-blind adaptive algorithm is close to that of the training-based RLS algorithm. Thus, this semi-blind adaptive STE offers an effective and practical means to successfully operate under the highly dispersive and fading MIMO environment.
机译:最近,基于并发梯度牛顿(GN)恒定模量算法(CMA)和软决策定向(SDD)方案,针对色散多输入多输出(STEP)提出了半盲自适应空时均衡器(STE) MIMO)系统采用高吞吐量正交幅度调制信令。训练符号的最小数量(大约等于STE的尺寸)用于对STE的权重向量进行初步估算。然后采用基于并发GN的CMA和SDD盲自适应方案来自适应STE。此半盲STE的复杂度类似于基于训练的递归最小二乘(RLS)算法。对于固定的MIMO信道,已证明该半盲自适应STE能够快速收敛到最佳最小均方误差STE解。在这项贡献中,我们研究了在瑞利衰落MIMO系统中运行的这种半盲自适应STE的性能。我们获得的结果表明,该半盲自适应算法的跟踪性能接近于基于训练的RLS算法的跟踪性能。因此,这种半盲自适应STE提供了一种有效且实用的方法,可以在高度分散和衰落的MIMO环境下成功运行。

著录项

  • 作者

    Cheng Huiting; Chen Sheng;

  • 作者单位
  • 年度 2011
  • 总页数
  • 原文格式 PDF
  • 正文语种 {"code":"en","name":"English","id":9}
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