An improved pilot routing algorithm for compressed sensing-based channel estimation in underwater acoustic OFDM system

L. Tang, Haixia Wu, Rongkun Jiang, Chang Lu
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引用次数: 3

Abstract

Compressed sensing (CS) is used to estimate channel information in underwater acoustic OFDM system recently. However, there are no recognition criteria to specify the pilot patterns in channel estimation. In order to improve the accuracy of the estimation, this paper proposes a pilot routing algorithm based on minimizing the adjusted mutual coherence of the measurement matrix in the recovery algorithm of compressed sensing theory. Each pilot symbol location is determined by calculating the adjusted mutual coherence of the corresponding measurement matrix. The matrix is produced by fixing other pilot location indexes and replacing the index of the current pilot location with all optional indexes. The simulation results show that the BER is 2dB and 8dB lower when SNR is 5dB and 30dB respectively, and the MSE is 2dB lower compared with the results of algorithm 1. Comparing with the results of algorithm 2, the BER is 2dB better, and the MSE is 3dB lower when SNR is 30dB. The data confirms the efficiency of this pilot routing algorithm.
一种改进的基于压缩感知的水声OFDM信道估计导频路由算法
近年来,压缩感知技术被用于水声OFDM系统的信道信息估计。然而,在信道估计中,没有识别标准来指定导频模式。为了提高估计的精度,本文在压缩感知理论的恢复算法中提出了一种基于最小化测量矩阵调整后相互相干性的导频路由算法。每个导频符号的位置是通过计算相应测量矩阵调整后的相互相干性来确定的。通过固定其他导频位置索引并将当前导频位置的索引替换为所有可选索引来生成矩阵。仿真结果表明,与算法1的结果相比,信噪比分别为5dB和30dB时,误码率分别降低了2dB和8dB, MSE降低了2dB。当信噪比为30dB时,与算法2相比,误码率提高了2dB, MSE降低了3dB。实验数据验证了该导频路由算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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