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结合修正常数模算法、决策导向方案与巴齐莱-博温方法

Concurrent Modified Constant Modulus Algorithm and Decision Directed Scheme With Barzilai-Borwein Method.

作者信息

Xu Tongtong, Xiang Zheng, Yang Hua, Chen Yun, Luo Jun, Zhang Yutao

机构信息

Department of Telecommunication Engineering, Xidian University, Xi'an, China.

Guangdong Shenglu Telecommunication Tech. Co., Ltd, Foshan, China.

出版信息

Front Neurorobot. 2021 Jun 10;15:699221. doi: 10.3389/fnbot.2021.699221. eCollection 2021.

Abstract

At present, in robot technology, remote control of robot is realized by wireless communication technology, and data anti-interference in wireless channel becomes a very important part. Any wireless communication system has an inherent multi-path propagation problem, which leads to the expansion of generated symbols on a time scale, resulting in symbol overlap and Inter-symbol Interference (ISI). ISI in the signal must be removed and the signal restores to its original state at the time of transmission or becomes as close to it as possible. Blind equalization is a popular equalization method for recovering transmitted symbols of superimposed noise without any pilot signal. In this work, we propose a concurrent modified constant modulus algorithm (MCMA) and the decision-directed scheme (DDS) with the Barzilai-Borwein (BB) method for the purpose of blind equalization of wireless communications systems (WCS). The BB method, which is two-step gradient method, has been widely employed to solve multidimensional unconstrained optimization problems. Considering the similarity of equalization process and optimization process, the proposed algorithm combines existing blind equalization algorithm and Barzilai-Borwein method, and concurrently operates a MCMA equalizer and a DD equalizer. After that, it modifies the DD equalizer's step size (SS) by the BB method. Theoretical investigation was involved and it demonstrated rapid convergence and improved equalization performance of the proposed algorithm compared with the original one. Additionally, the simulation results were consistent with the proposed technique.

摘要

目前,在机器人技术中,机器人的远程控制是通过无线通信技术实现的,无线信道中的数据抗干扰成为非常重要的一部分。任何无线通信系统都存在固有的多径传播问题,这会导致生成的符号在时间尺度上扩展,从而产生符号重叠和符号间干扰(ISI)。必须消除信号中的ISI,并使信号在传输时恢复到原始状态或尽可能接近原始状态。盲均衡是一种流行的均衡方法,用于在没有任何导频信号的情况下恢复叠加噪声的传输符号。在这项工作中,我们提出了一种并发的改进恒模算法(MCMA)和带有Barzilai-Borwein(BB)方法的判决导向方案(DDS),用于无线通信系统(WCS)的盲均衡。BB方法是一种两步梯度法,已被广泛用于解决多维无约束优化问题。考虑到均衡过程和优化过程的相似性,所提出的算法将现有的盲均衡算法与Barzilai-Borwein方法相结合,并同时运行一个MCMA均衡器和一个DD均衡器。之后,它通过BB方法修改DD均衡器的步长(SS)。进行了理论研究,结果表明与原始算法相比,所提出的算法具有快速收敛性和改进的均衡性能。此外,仿真结果与所提出的技术一致。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf73/8222806/c6bdcb285276/fnbot-15-699221-g0001.jpg

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