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Semi-blind joint channel estimation and data detection on sphere manifold for MIMO with high-order QAM signaling

机译:具有高阶QAM信令的MIMO球体歧管的半盲接头通道估计和数据检测

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摘要

A low-complexity semi-blind scheme is proposed for joint channel estimation and data detection on sphere manifold for multiple-input multiple-output (MIMO) systems with high-order quadrature amplitude modulation signaling. Specifically, the optimal channel estimator is expressed in the least squares form in terms of the received signals and unknown transmitted data, and by splitting the channel and transmitted data into their real parts and imaginary parts, the data detection becomes a problem defined on a scaled sphere manifold in the real domain. Our semi-blind algorithm consists of three stages: (i) a few training symbols are employed to provide a rough initial MIMO channel estimate which in turn yields the initial zero-forcing (ZF) estimate of data samples; (ii) the Riemannian conjugate gradient algorithm is used to estimate the data samples in real domain, and the detected data samples are used to estimate the final MIMO channel matrix; and (iii) the final ZF data detection is carried out based on the final MIMO channel estimate. In particular, we present the first order Riemannian geometry of the sphere manifold which is utilized in the Riemannian conjugate gradient algorithm for solving (ii). Simulation results are employed to demonstrate the effectiveness of the proposed approach. (C) 2020 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
机译:提出了一种低复杂性半盲方案,用于在具有高阶正交调制信号传导的多输入多输出(MIMO)系统的球形歧管上的关节通道估计和数据检测。具体地,在接收的信号和未知的发送数据方面,最优信道估计器以最小二乘形式表示,并且通过将信道和发送数据分成其实体部分和虚部,数据检测成为缩放上定义的问题真实域中的球形歧管。我们的半盲算法由三个阶段组成:(i)采用一些训练符号来提供粗略初始MIMO信道估计,这反过来产生数据样本的初始零强制(ZF)估计; (ii)riemannian共轭梯度算法用于估计真实域中的数据样本,并且检测到的数据样本用于估计最终的MIMO信道矩阵; (iii)基于最终的MIMO信道估计来执行最终ZF数据检测。特别地,我们介绍了球形歧管的第一阶riemananian几何形状,其用于求解(ii)的Riemannian共轭梯度算法。采用仿真结果来证明所提出的方法的有效性。 (c)2020富兰克林学院。 elsevier有限公司出版。保留所有权利。

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  • 来源
    《Journal of the Franklin Institute》 |2020年第9期|5680-5697|共18页
  • 作者

    Hong Xia; Gao Junbin; Chen Sheng;

  • 作者单位

    Univ Reading Sch Math & Phys Sci Dept Comp Sci Reading RG6 6AY Berks England;

    Univ Sydney Sch Business Discipline Business Analyt Camperdown NSW 2006 Australia;

    Univ Southampton Sch Elect & Comp Sci Southampton SO17 1BJ Hants England|King Abdulaziz Univ Jeddah 21589 Saudi Arabia;

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  • 正文语种 eng
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