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Semi-blind adaptive spatial equalisation for MIMO systems with high-order QAM signalling

机译:具有高阶Qam信令的mImO系统的半盲自适应空间均衡

摘要

This contribution investigates semi-blind adaptive spatial filtering or equalisation for multiple-input multiple-output (MIMO) systems that employ high-throughput quadrature amplitude modulation (QAM) signalling. A minimum number of training symbols, equal to the number of receivers (we assume that the number of transmitters is no more than that of receivers), are first utilized to provide a rough least squares channel estimate of the system's MIMO channel matrix for the initialization of the spatial equalizers' weight vectors. A constant modulus algorithm aided soft decision-directed blind algorithm, originally derived for blind equalization of single-input single-output and single-input multiple-output systems employing high-order QAM signalling, is then extended to adapt the spatial equalizers for MIMO systems. This semi-blind scheme has a low computational complexity, and our simulation results demonstrate that it converges fast to the minimum mean-square-error spatial equalization solution.
机译:此文稿研究了采用高吞吐量正交幅度调制(QAM)信令的多输入多输出(MIMO)系统的半盲自适应空间滤波或均衡。最小数量的训练符号等于接收器的数量(我们假设发射器的数量不超过接收器的数量),首先用于提供系统的MIMO信道矩阵的最小二乘近似估计,以进行初始化空间均衡器的权向量。恒定模量算法辅助的软判决定向盲算法,最初是为使用高阶QAM信号的单输入单输出和单输入多输出系统的盲均衡而导出的,然后进行扩展以适应MIMO系统的空间均衡器。该半盲方案具有较低的计算复杂度,我们的仿真结果表明,该方案可快速收敛到最小均方误差空间均衡解决方案。

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