北京邮电大学学报

  • EI核心期刊

北京邮电大学学报 ›› 2019, Vol. 42 ›› Issue (3): 7-13.doi: 10.13190/j.jbupt.2018-157

• 论文 • 上一篇    下一篇

GFDM系统低复杂度最小均方误差接收机解调算法

黄翔东, 王惠杰, 黎鸣诗, 曹月彬   

  1. 天津大学 电气自动化与信息工程学院, 天津 300072
  • 收稿日期:2018-07-17 出版日期:2019-06-28 发布日期:2019-06-20
  • 作者简介:黄翔东(1979-),男,副教授,E-mail:xdhuang@tju.dedu.cn.
  • 基金资助:
    青岛海洋科学与技术试点国家实验室开放基金项目(QNLM2016OPR041)

Low-Complexity MMSE Demodulation Algorithm for GFDM

HUANG Xiang-dong, WANG Hui-jie, LI Ming-shi, CAO Yue-bin   

  1. School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China
  • Received:2018-07-17 Online:2019-06-28 Published:2019-06-20

摘要: 针对广义频分复用(GFDM)在频率选择性信道下的最小均方误差(MMSE)接收机计算复杂度过高的问题,提出了一种基于矩阵解构的低复杂度GFDM系统的MMSE接收机解调算法.该方法对涉及的大尺寸矩阵做分块处理,发掘了矩阵的特殊性质(稀疏性、准三对角性和块对称性等),进而将一系列大矩阵的相乘和求逆运算转化为相应子块间的相乘和求逆,从而使得其耗费的复数乘法次数比原始的MMSE接收机解调算法低2~3个数量级.仿真结果表明,所提出的接收机不会导致误比特率性能下降,因而在未来移动通信的解调系统中具有较高的应用价值.

关键词: 广义频分复用, 最小均方误差, 频率选择性信道, 低复杂度

Abstract: Aiming at the problem that the computation complexity of the existing minimum mean square error (MMSE) demodulator with generalized frequency division multiplexing (GFDM) over frequency selective channel is relatively high, a matrix deconstruction based low-complexity MMSE GFDM receiver is proposed. By utilization of the particular structures (sparse, quasi-tridiagonal, block-symmetric, etc.) in a series of large-sized matrices involved in the receiver, either of large-sized matrix manipulations (including matrix multiplication and matrix inversion) is partitioned into small-sized matrix manipulations, thereby considerably reducing the computational complexity. Quantitively speaking, the times of complex multiplications consumed by the proposed MMSE receiver is 2-3 amount levels lower than the original MMSE receiver. Moreover, simulation shows that the proposed receiver does not suffer from any bit-error-rate degradation. Therefore, the proposed MMSE GFDM receiver possesses vast potentials for future 5G demodulation applications.

Key words: generalized frequency division multiplexing, minimum mean square error, frequency selective channel, low-complexity

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