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Fast Converging Semi-Blind Space-Time Equalisation for Dispersive QAM MIMO Systems

机译:离散QAM MIMO系统的快速收敛半盲空时均衡

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摘要

A novel semi-blind space-time equaliser (STE) is proposed for dispersive multiple-input multiple-output systems that employ high-throughput quadrature amplitude modulation signalling. A minimum number of training symbols, approximately equal to the dimension of the STE, are first utilised to provide a rough initial least squares estimate of the STE¿s weight vector. A concurrent gradient-Newton constant modulus algorithm and soft decision-directed scheme is then applied to adapt the STE. The proposed semi-blind adaptive STE is capable of converging fast to the minimum mean square error STE solution. Simulation results confirms that the convergence speed of this semi-blind adaptive algorithm is very close to that of the training-based recursive least squares algorithm.
机译:针对采用高通量正交幅度调制信号的色散多输入多输出系统,提出了一种新颖的半盲空时均衡器(STE)。最小数量的训练符号(大约等于STE的尺寸)首先用于提供STE权重向量的粗略初始最小二乘估计。然后,采用并发梯度牛顿常数模算法和软决策指导方案来适应STE。所提出的半盲自适应STE能够快速收敛到最小均方误差STE解。仿真结果表明,该半盲自适应算法的收敛速度与基于训练的递归最小二乘算法的收敛速度非常接近。

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