WCSE 2016
ISBN: 978-981-11-0008-6 DOI: 10.18178/wcse.2016.06.123

OFDM System Channel Estimation Based on Compressive Sensing Technology

Tang Jia-lin, Deng Dong-fang, Jiang Cai-gao, Li Xi-ying

Abstract— Compressive Sensing is applicable to the sparse signals or sampling signals, and can compress the signal data properly in course of sampling, therefore, it can carry out sampling at a rate much lower than that specified as per Nyquist Sampling Theorem, and reconstruct the original signals accurately. This paper mainly studies the channel estimation algorithm of OFDM system, including the traditional channel estimation algorithm and that based on compressive sensing theory, and makes a relevant analysis on their respective theories, thoughts and characteristics. Furthermore, an experiment simulation is conducted here to compare their performance in an all-round manner, and the conclusion indicates that the signal acquisition technology based on compressive sensing technology performs better. The compressive sensing can effectively solve the problems encountered by the traditional signal sampling and coding technology in the aspect of processing speed, memory space and anti-interference function, showing a promising application background.

Index Terms— compressive sensing, signal sampling, signal reconstruction, channel estimation.

Tang Jia-lin, Deng Dong-fang, Jiang Cai-gao
School of Information Technology, ZHBIT, CHINA
Li Xi-ying
Guangdong Provincial Key Laboratory of Intelligent Transportation System, CHINA


Cite: Tang Jia-lin, Deng Dong-fang, Jiang Cai-gao, Li Xi-ying, "OFDM System Channel Estimation Based on Compressive Sensing Technology," Proceedings of 2016 6th International Workshop on Computer Science and Engineering, pp. 695-700, Tokyo, 17-19 June, 2016.