摘要
为合理利用电力线信道的稀疏特性,提高G3-PLC系统通信的可靠性,基于压缩感知(compressed sensing,CS)理论,提出一种稀疏度自适应的变步长前向后向匹配追踪(sparsity adaptive variable step size forward-backward pursuit,SA-VSSFBP)算法。该算法在前向后向匹配追踪算法(forward-backward pursuit,FBP)的基础上引入变步长自适应的思想,于迭代初期选择大步长以减小迭代次数,迭代后期使用小步长获得精确估计。同时利用原子匹配度测试进行稀疏度预估计,确保逼近真实稀疏度的前提下,加快迭代速度,减少算法运行的时间。仿真实验结果表明,对比传统的信道估计方式,压缩感知信道估计方式具有更优越的性能,且相较于正交匹配追踪算法(orthogonal matching pursuit,OMP)与FBP的压缩感知信道估计算法,文章提出的算法能够在保证精度与步长为1的FBP相当的情况下算法效率分别能够提升24.14%和47.2%。
In order to leverage the sparse characteristics of power line communication channel and improve the reliability of G3-PLC system communication,this paper proposes a sparsity adaptive variable step size forward-backward pursuit(SA-VSSFBP)algorithm based on the theory of compressed sensing(CS).This algorithm builds upon the forward-backward pursuit(FBP)algorithm and introduces the concept of variable step size with adaptivity.It employs a large step size in the initial iterations to reduce the number of iterations,and a small step size in the later iterations to obtain accurate estimates.Additionally,the atomic matching test is utilized for sparsity pre-estimation to ensure the approximation of the real sparsity,speed up the iteration speed and reduce the running time of the algorithm.The simulation results show that:compared with the traditional channel estimation method,the compressed sensing channel estimation method has superior performance;and compared with the orthogonal matching pursuit(OMP)and FBP compressed sensing channel estimation algorithms,the algorithm proposed in this paper is able to improve 24.14%and 47.2%of the efficiency of the algorithm in the case of guaranteeing that the accuracy is comparable to that of the FBP with the step size of 1.
作者
吴铭
沈瑞强
袁三男
WU Ming;SHEN Ruiqiang;YUAN Sannan(School of Electronic and Information Engineering,Shanghai Electric Power University,Yangpu District,Shanghai 201306,China;Jiangsu Linyang Energy Co.,Ltd.,Nantong 226200,Jiangsu Province,China)
出处
《电力信息与通信技术》
2024年第7期82-87,共6页
Electric Power Information and Communication Technology
