Hu Hao, Zhao Xu, Chen Shiyong, Huang Tiancong
School of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, China.
Beijing Smart-Chip Microelectronics Technology Co., Ltd., Beijing 100192, China.
Sensors (Basel). 2023 Jul 25;23(15):6668. doi: 10.3390/s23156668.
Channel estimation of an orthogonal frequency division multiplexing (OFDM) system based on compressed sensing can effectively reduce the pilot overhead and improve the utilization rate of spectrum resources. The traditional SAMP algorithm with a fixed step size for sparse channel estimation has the disadvantages of a low estimation efficiency and limited estimation accuracy. An Improved SAMP (ImpSAMP) algorithm is proposed to estimate the channel state information of the OFDM system. In the proposed ImpSAMP algorithm, the received signal is firstly denoised based on the energy-detection method, which can reduce the interferences on channel estimation. Furthermore, the step size is adjusted dynamically according to the norm of difference between two estimated sparse channel coefficients of adjacent phases to estimate the sparse channel coefficients quickly and accurately. In addition, the double threshold judgment is adopted to enhance the estimation efficiency. The simulation results show that the ImpSAMP algorithm outperforms the traditional SAMP algorithm in estimation efficiency and accuracy.
基于压缩感知的正交频分复用（OFDM）系统信道估计能够有效降低导频开销并提高频谱资源利用率。传统的用于稀疏信道估计的固定步长SAMP算法存在估计效率低和估计精度有限的缺点。提出了一种改进的SAMP（ImpSAMP）算法来估计OFDM系统的信道状态信息。在所提出的ImpSAMP算法中，首先基于能量检测方法对接收到的信号进行去噪，这可以减少对信道估计的干扰。此外，根据相邻相位的两个估计稀疏信道系数之间的差的范数动态调整步长，以快速准确地估计稀疏信道系数。另外，采用双阈值判断来提高估计效率。仿真结果表明，ImpSAMP算法在估计效率和精度方面优于传统SAMP算法。
