基于ISL0算法的码间干扰稀疏多径信道估计

发布时间：2018-01-14 19:39

本文关键词：基于ISL0算法的码间干扰稀疏多径信道估计　出处：《通信学报》2014年05期 　论文类型：期刊论文

【摘要】：针对存在码间干扰ISI的稀疏多径信道,已提出基于压缩感知理论的平滑SL0算法来研究其稀疏特性,然而SL0算法的迭代方向为负梯度方向,存在"锯齿效应",且其代价函数"陡峭性"性能欠佳,使得信道估计和收敛效果均未达到最优。因此提出利用拉格朗日算子,结合牛顿法来改进和优化SL0算法,获得了快速和高效的信号重构ISL0算法,对稀疏多径信道状态信息进行了相关估计,分析了信噪比SNR和迭代次数等参数对重构信号均方误差MSE的影响。比较了ISL0算法与其他相关算法的迭代时间以及对稀疏信道中ISI均衡效果的差异。算法的优越性通过仿真得到验证,实时仿真结果显示ISL0算法能很好地对稀疏信道进行估计。在同样信道环境条件下,相比CoSaMP、SL0及其他算法,ISL0算法的性能有了较大提高。
[Abstract]:For sparse multipath channels with inter-symbol interference (ISI), a smoothing SL0 algorithm based on compression sensing theory is proposed to study its sparse properties. However, the iterative direction of SL0 algorithm is negative gradient direction. There is "sawtooth effect", and its cost function "steepness" performance is poor, so channel estimation and convergence effect are not optimal. Therefore, Lagrangian operator is proposed. Combining Newton method to improve and optimize the SL0 algorithm, a fast and efficient signal reconstruction ISL0 algorithm is obtained, and the correlation estimation of sparse multipath channel state information is carried out. The effects of SNR, SNR and iteration times on the mean square error (MSE) of reconstructed signals are analyzed. The iterative time of ISL0 algorithm and other related algorithms and the effect of ISI equalization on sparse channel are compared. The superiority of the algorithm is verified by simulation. The real time simulation results show that the ISL0 algorithm can estimate the sparse channel very well. In the same channel environment, compared with the CoSMP ISL0 SL0 and other algorithms. The performance of ISL0 algorithm has been greatly improved.
【作者单位】：南京信息工程大学电子与信息工程学院;日本国立新泻大学工学部电气电子工学科;
【基金】：国家自然科学基金资助项目(61372128) 科技部公益性行业专项基金资助项目(GYHY200906053) 江苏省科技支撑计划(工业)基金资助项目(BE2011195)~~
【分类号】：TN911.23
【正文快照】： 1引言无线多径衰落信道和水声信道通常都是稀疏信道,在数字通信理论的架构下,稀疏信道都可以建模成有限冲激响应(FIR,finite impulse response)稀疏滤波向量[1,2]。由于多径效应,在数字通信系统中不可避免地会存在码间干扰(ISI,inter symbolinterference),所以对存在ISI的稀疏

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