Multi user detection based on independent component analysis and compressed sensing
In the process of wireless communication, the improved wireless communication technology is optimized by exploiting the sparsity of the signal transmission to improve the system communication efficiency and the communication performance. In the case of insufficient system resources and few active users, in order to save system resources, the pilot signal is not sent. Recover the source signal from the received data when the channel parameters are unknown., we combine the advantages of independent component analysis and compressed sensing to obtain the multiuser detection. Based on the multi-user detection model, the independent component analysis algorithm is introduced into the compressed sensing data processing. Two different data processing processes are analyzed and compared. The experimental results show that the compressive sensing algorithm combined with the independent component analysis can be applied to multi-user detection without prior information and has good performance.