Multi User Detection Based on Independent Component Analysis and Compressed Sensing

Abstract

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.