文章摘要
李文艳,朱婷婷,王琪.稀疏多径信道自适应均衡算法研究[J].声学技术,2019,38(6):698~704
稀疏多径信道自适应均衡算法研究
Research on adaptive equalization algorithm for sparse multipath channel
投稿时间:2019-07-08  修订日期:2019-10-10
DOI:10.16300/j.cnki.1000-3630.2019.06.017
中文关键词: 稀疏多径信道  自适应均衡  l2-范数  压缩感知
英文关键词: sparse multipath channel  adaptive equalization  l2-norm  compressed sensing
基金项目:Shaanxi province science and technology key research and development program general projects (2019GY-084)
作者单位E-mail
李文艳 西安工业大学电子信息工程学院, 陕西西安 710021 2963454019@qq.com 
朱婷婷 西安工业大学电子信息工程学院, 陕西西安 710021  
王琪 西安工业大学电子信息工程学院, 陕西西安 710021  
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中文摘要:
      针对传统自适应均衡算法在稀疏多径信道中性能较差的问题,提出了一种基于l2-范数的自适应均衡算法。该算法利用稀疏多径信道下均衡器权值的稀疏性,将自适应均衡器的训练过程看作压缩感知理论中稀疏信号对字典的加权求和,以解决迭代参数的设置及收敛速度慢的问题。该算法将l2-范数和压缩感知相结合,不仅提高了权值的精度,而且降低了计算复杂度。仿真结果表明,该算法计算量小,训练序列少,具有较好的性能,对提高系统的通信性能具有参考价值。
英文摘要:
      In order to solve the problem of poor performance of traditional adaptive equalization algorithm in sparse multipath channels, a new adaptive equalization algorithm based on l2 -norm is proposed. This algorithm takes advantage of the sparsity of equalizer weights in sparse multipath channel, and regards the training process of adaptive equalizer as the weighted sum of sparse signal to dictionary in compressed sensing theory, so as to solve the problems of iterative parameter setting and slow convergence. This new algorithm, which combines l2 -norm with compressed sensing, not only improves the weight accuracy, but also reduces the computational complexity. Simulation results show that the proposed algorithm can achieve better performance with less computation amount and fewer training sequences, and has a reference value for improving the communication performance of the system.
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