Research On Underwater Acoustic Channel Estimation Of MIMO-OFDM Based On Compressed Sensing

The ocean not only contains abundant resources,but also has great strategic value.As an effective way of ocean communication,high-speed and reliable underwater acoustic communication has received extensive attenti on from various countries.Due to the complex and ever-changing marine environment,channel fading seriously affects the quality of communication.Accurate channel estimation algorithms help correct signal recovery at the receiving end.Channel estimation algorithms based on compressed sensing can quickly and effectively estimate the state information of underwater acoustic channels and become a research hotspot.This paper uses MIMO-OFDM technology to build a system simulation model,and conducts simulation research on the compressed sensing channel estimation algorithm.The main work of the thesis includes the following aspects:First,the main characteristics of the underwater acoustic channel are studied,and the impact of these features on underwater acoustic communication is analyzed.Based on the large-scale effect and the small-scale effect,the underwater acoustic channel model is established to pave the way for subsequent simulation experiments.Secondly,the advantages and disadvantages of MIMO technology and OFDM technology in underwater acoustic environment are analyzed,and an underwater acoustic MIMO-OFDM simulation system is built.The influence of space-time block code,modulation technology and channel coding technology on MIMO-OFDM system is studied.The performance of the bit error rate is given through simulation comparison.Then,the theory of compressed sensing and its application in channel estimation are introduced.The channel estimation research is based on the tracking algorithm in the greedy algorithm.In the MIMO-OFDM system,common matching tracking algorithms are analyzed and simulated to verify their channel estimation effect.Finally,for both the known and unknown sparseness,an improved algorithm based on ROMP and SAMP is proposed.Simulation experiments show that the improved algorithm can improve the signal processing efficiency and increase the system performance,which has certain reference and practical value.