Multiuser detection with sparse spectrum Gaussian process regression

Abstract

Multiuser detection in direct-sequence code-division multiple access (DS-CDMA) systems can be implemented by using Gaussian process (GP) for regression in the sense of minimum mean square error criterion. In this Letter we investigate the application of sparse spectrum Gaussian process (SSGP) to the multiuser detection problem. The key point of the SSGP is that the sparsity of spectral representation of Gaussian process leads to an algorithm with much lower complexity than the full GP, while keeping almost the same bit error rate (BER) for DS-CDMA systems. Experimental results validate our proposed SSGP based multiuser detection method. It achieves greater efficiency and good BER performance.