Research Article
Sparse Algorithm for OFDM Underwater Acoustic Channel Estimation
@INPROCEEDINGS{10.1007/978-3-031-04409-0_18, author={Tieliang Guo and Wenxiang Zhang and Zhijun Li and Xue Sun}, title={Sparse Algorithm for OFDM Underwater Acoustic Channel Estimation}, proceedings={Machine Learning and Intelligent Communications. 6th EAI International Conference, MLICOM 2021, Virtual Event, November 2021, Proceedings}, proceedings_a={MLICOM}, year={2022}, month={5}, keywords={Underwater acoustic communications OFDM Channel estimation OMP algorithm}, doi={10.1007/978-3-031-04409-0_18} }- Tieliang Guo
Wenxiang Zhang
Zhijun Li
Xue Sun
Year: 2022
Sparse Algorithm for OFDM Underwater Acoustic Channel Estimation
MLICOM
Springer
DOI: 10.1007/978-3-031-04409-0_18
Abstract
Channel estimation is very important and challenging for underwater acoustic (UWA) systems that use orthogonal frequency division multiplexing (OFDM) technique. The conventional methods are not appropriate to the severe frequency selective fading channel; also current channel estimation algorithms do not use the sparse characteristics of the UWA channel efficiently. In this paper, a novel algorithm about channel estimation is addressed that applies channel sparse features. First, Least Square (LS) algorithm is used to get the pilot channel valuation. Secondly, the sparse degree of channel is estimated through DFT for noise reduction processing. Then the autocorrelation matrix of the channel is obtained approximately. Finally a preliminary calculation of the error threshold is acquired, and the high quality data subcarrier channel impulse can be estimated by the pilot symbols through using the orthogonal matching pursuit (OMP) algorithm. In terms of simulating, we study the performance of the system through bit error rate (BER) and the constellation diagram, and it is indicated that the new method has excellent performance at less computation. So it is very important that the method can be implemented in OFDM systems.
