基于联合稀疏模型的OFDM线性时变信道估计
发布时间：2019-02-19 22:03
【摘要】：为了进一步提高OFDM线性时变信道估计性能,利用信道抽头的时域稀疏特性和相关性,提出一种基于联合稀疏模型的信道估计方法.首先,将线性时变信道模型下对连续多个符号周期的信道估计转换成一个联合稀疏重构模型;其次,采用基于测量矩阵互相关性最小化的分组导频设计准则,在应对子载波干扰的同时,保证了稀疏重构算法的性能;最后,设计一种基于循环并行树的分组导频优化算法.仿真结果表明:与传统线性时变信道估计方法和联合稀疏模型下的信道估计方法相比,所提方法所需导频数量少,信道估计性能更好,同时便于工程应用.
[Abstract]:In order to further improve the performance of OFDM linear time-varying channel estimation, a channel estimation method based on joint sparse model is proposed based on time-domain sparsity and correlation of channel tap. Firstly, the channel estimation for continuous multiple symbol periods under the linear time-varying channel model is transformed into a joint sparse reconstruction model. Secondly, a packet pilot design criterion based on minimization of cross-correlation between measurement matrices is adopted to deal with subcarrier interference while ensuring the performance of sparse reconstruction algorithm. Finally, a packet pilot optimization algorithm based on cyclic parallel tree is designed. The simulation results show that compared with the traditional linear time-varying channel estimation method and the channel estimation method based on the joint sparse model, the proposed method requires less pilot frequency, has better channel estimation performance, and is easy to be applied in engineering.
【作者单位】： 西北工业大学电子信息学院;武警工程大学信息工程系;
【基金】：国家自然科学基金资助项目(61571368) 军队装备预研项目(9140A25030511HK0340,9410C39051120C39149)
【分类号】：TN929.53
本文编号：2426924
[Abstract]:In order to further improve the performance of OFDM linear time-varying channel estimation, a channel estimation method based on joint sparse model is proposed based on time-domain sparsity and correlation of channel tap. Firstly, the channel estimation for continuous multiple symbol periods under the linear time-varying channel model is transformed into a joint sparse reconstruction model. Secondly, a packet pilot design criterion based on minimization of cross-correlation between measurement matrices is adopted to deal with subcarrier interference while ensuring the performance of sparse reconstruction algorithm. Finally, a packet pilot optimization algorithm based on cyclic parallel tree is designed. The simulation results show that compared with the traditional linear time-varying channel estimation method and the channel estimation method based on the joint sparse model, the proposed method requires less pilot frequency, has better channel estimation performance, and is easy to be applied in engineering.
【作者单位】： 西北工业大学电子信息学院;武警工程大学信息工程系;
【基金】：国家自然科学基金资助项目(61571368) 军队装备预研项目(9140A25030511HK0340,9410C39051120C39149)
【分类号】：TN929.53
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