基于IOC-CSMP的OFDM系统稀疏信道快速重构算法

doi:10.11959/j.issn.1000-436x.2023034

通信学报 ›› 2023, Vol. 44 ›› Issue (2): 52-58.doi: 10.11959/j.issn.1000-436x.2023034

基于IOC-CSMP的OFDM系统稀疏信道快速重构算法

崔伟, 于颖, 于海霞, 陈超, 李云鹏

空军航空大学航空作战勤务学院，吉林长春 130022

修回日期:2022-10-08 出版日期:2023-02-25 发布日期:2023-02-01
作者简介:崔伟（1982− ），男，山东青岛人，博士，空军航空大学副教授，主要研究方向为盲源分离与稀疏信号重构、阵列信号处理等
于颖（1978− ），女，吉林靖宇人，空军航空大学讲师，主要研究方向为盲源分离、稀疏信号重构和信道估计等
于海霞（1979− ），女，吉林长春人，空军航空大学副教授，主要研究方向为信道估计、自适应通信等
陈超（1983− ），男，辽宁辽源人，空军航空大学讲师，主要研究方向为电子对抗雷电一体化、雷电信号处理等
李云鹏（1979− ），男，辽宁开原人，空军航空大学副教授、硕士生导师，主要研究方向为电子对抗仿真与运用、信号盲处理等
基金资助:
国家自然科学基金资助项目(61571462);空军航空大学中青年骨干支持计划基金资助项目(HDZQN2020-012)

Sparse channel fast reconstruction algorithm for OFDM system based on IOC-CSMP

Wei CUI, Ying YU, Haixia YU, Chao CHEN, Yunpeng LI

College of Avaiation, Avaiation University of Air Force, Changchun 130022, China

Revised:2022-10-08 Online:2023-02-25 Published:2023-02-01
Supported by:
The National Natural Science Foundation of China(61571462);Young and Middle-Aged Backbone Support Program of Aviation University of Air Force(HDZQN2020-012)

摘要/Abstract

摘要：

针对信道路径数量未知时正交频分复用（OFDM）系统信道估计问题，提出了一种基于内积运算优化与稀疏度更新约束的压缩采样匹配追踪快速重构算法。通过构建与更新选择向量，利用与选择向量中非零值索引对应的原子向量参与内积运算来降低运算量；基于压缩采样与回溯策略来优化原子，利用匹配追踪完成信道估计，通过相邻两次信道估计值的能量差来更新稀疏度并约束算法停止，保证算法快速收敛。仿真结果表明，所提算法具有比最小二乘、最小均方差、稀疏度自适应匹配追踪和自适应正则化压缩采样匹配追踪算法更好的信道估计性能，且比2种自适应方法消耗更少的信道估计时间。

关键词: 压缩采样, 内积运算, 回溯策略, 稀疏度自适应, 信道估计

Abstract:

A fast reconstruction algorithm based on inner product optimization and sparsity updating constraint was proposed for OFDM system channel estimation when the number of channel paths was unknown.By constructing and updating the selection vector, the inner product operation was reduced by using the atoms corresponding to the non-zero index of the selection vector.The atoms were optimized based on compressed sampling and backtracking strategies, and the channel estimation was completed by matching pursuit.The sparsity update and the stop condition for the algorithm was achieved by the energy difference between the two adjacent channel estimation so as to ensure fast convergence of the algorithm.The simulation results show that the proposed algorithm has better channel estimation performance than the least square algorithm, minimum mean square error algorithm, sparsity adaptive matching pursuit algorithm and adaptive regularized compressed sampling matching pursuit algorithm, and consumes less channel estimation time than the two adaptive methods.

Key words: compressed sampling, inner product, backtracking strategy, sparsity adaptive, channel estimation

中图分类号:

TN92

崔伟, 于颖, 于海霞, 陈超, 李云鹏. 基于IOC-CSMP的OFDM系统稀疏信道快速重构算法[J]. 通信学报, 2023, 44(2): 52-58.

Wei CUI, Ying YU, Haixia YU, Chao CHEN, Yunpeng LI. Sparse channel fast reconstruction algorithm for OFDM system based on IOC-CSMP[J]. Journal on Communications, 2023, 44(2): 52-58.

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基于IOC-CSMP的OFDM系统稀疏信道快速重构算法

Sparse channel fast reconstruction algorithm for OFDM system based on IOC-CSMP

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基于IOC-CSMP的OFDM系统稀疏信道快速重构算法

Sparse channel fast reconstruction algorithm for OFDM system based on IOC-CSMP

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