| 摘要: |
| 为了提高G3-PLC系统可靠性，引入压缩感知(Compressed Sensing，CS)的信道估计方法，提出了一种基于最小二乘(Least Squares,LS)的稀疏度预测自适应匹配追踪(LS Based Prediction-Sparsity Adaptive Matching Pursuit，LS-SAMP)算法。该算法在稀疏度自适应匹配追踪(Sparsity Adaptive Matching Pursuit，SAMP)算法的基础上，采用了基于LS的稀疏度预测方法对信道稀疏度进行预估计，使算法可以快速逼近信道的真实稀疏度，提高算法运行效率；其次利用主成分分析方法对观测矩阵进行线性优化，降低观测矩阵相干度，提高算法的重构性能。实验结果表明，在误码率为10-3时，所提算法相对于LS算法的信道估计性能有1 dB的提升，且其运行效率比SAMP算法提升了31.23%，以更有效的方式提高了G3-PLC系统的可靠性。 |
| 关键词: G3-PLC系统 信道估计 压缩感知 稀疏度自适应匹配追踪(SAMP) |
| DOI：10.20079/j.issn.1001-893x.220328003 |
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| 基金项目:国家自然科学基金资助项目（12004292）；陕西省科技厅一般项目-工业领域（2020GY-054）；西安市科技计划项目（2020KJRC0040） |
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| LS-SAMP Algorithm for Compressed Sensing Channel Estimation in G3-PLC System |
| LING Jinwei,ZHANG Feng,SHEN Bo,ZHAO Li |
| (1.School of Electronic Information Engineering,Xi揳n University of Technology,Xi揳n 710021,China;2.Xi揳n Institute of Mechanical and Information Technology,Xi揳n 710065,China) |
| Abstract: |
| In order to improve the reliability of G3-PLC system,the channel estimation method of compressed sensing(CS) is introduced,and a Least Squares(LS) based prediction-Sparsity Adaptive Matching Pursuit(LS-SAMP) algorithm is proposed.Based on the Sparsity Adaptive Matching Pursuit(SAMP) algorithm,the LS-SAMP algorithm uses the sparsity prediction method based on LS to predict the channel sparsity,so that it can quickly approach the real sparsity of the channel and improve the operation efficiency of the algorithm.Secondly,the principal component analysis method is used to linearly optimize the observation matrix,reduce the coherence of the observation matrix and improve the reconstruction performance of the algorithm.The experimental results show that when the bit error rate is 10-3,the channel estimation performance of the proposed algorithm is 1 dB higher than that of LS algorithm,and the operation efficiency is 31.23 |
| Key words: G3-PLC system channel estimation compressed sensing sparsity adaptive matching pursuit(SAMP) |
