Channel Estimation Performance Analysis of FBMC/OQAM Systems with Bayesian Approach for 5G-Enabled IoT Applications
Channel Estimation Performance Analysis of FBMC/OQAM Systems with Bayesian Approach for 5G-Enabled IoT Applications
复制标题
针对支持 5G 的物联网应用，采用贝叶斯方法对 FBMC/OQAM 系统进行信道估计性能分析
DOI：
10.1155/2020/2389673
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发表时间：
2020
影响因子：
--
通讯作者：
Xu Lingwei
中科院分区：
文献类型：
--
作者：
Wang Han;Du Wencai;Wang Xianpeng;Yu Guicai;Xu Lingwei
具有偏移正交幅度调制（OQAM）的滤波器组多载波（FBMC）（FBMC/OQAM）被认为是未来通信系统中的物理层技术之一，并且它也是支持物联网（IoT）应用的无线传输技术。然而，有效的信道参数估计是实现高可用FBMC系统的难点之一。本文研究了FBMC/OQAM系统中的贝叶斯压缩感知（BCS）信道估计方法，并分析了其在多输入多输出（MIMO）情况下的性能。提出了一种迭代快速贝叶斯匹配追踪算法，用于高速信道估计。贝叶斯信道估计首先提出了通过探索稀疏信道模型的先验统计信息。结果表明，BCS信道估计方案可以有效地估计信道冲激响应。通过优化迭代终止条件，提出了一种改进的FBMP算法。仿真结果表明，与传统的压缩感知方法相比，该方法具有更好的均方误差（MSE）和误比特率（BER）性能。
A filter bank multicarrier (FBMC) with offset quadrature amplitude modulation (OQAM) (FBMC/OQAM) is considered to be one of the physical layer technologies in future communication systems, and it is also a wireless transmission technology that supports the applications of Internet of Things (IoT). However, efficient channel parameter estimation is one of the difficulties in realization of highly available FBMC systems. In this paper, the Bayesian compressive sensing (BCS) channel estimation approach for FBMC/OQAM systems is investigated and the performance in a multiple-input multiple-output (MIMO) scenario is also analyzed. An iterative fast Bayesian matching pursuit algorithm is proposed for high channel estimation. Bayesian channel estimation is first presented by exploring the prior statistical information of a sparse channel model. It is indicated that the BCS channel estimation scheme can effectively estimate the channel impulse response. Then, a modified FBMP algorithm is proposed by optimizing the iterative termination conditions. The simulation results indicate that the proposed method provides better mean square error (MSE) and bit error rate (BER) performance than conventional compressive sensing methods.