Adaptive multiuser receiver using a support vector machine technique
Sheng Chen, Ahmad Kamsani Samingan, L. Hanzo · 2002
The paper investigates the application of an emerging learning technique, called support vector machines (SVMs), to construct an adaptive nonlinear multiuser detector (MUD) for direct sequence code-division multiple-access (DS-CDMA) signals transmitted through multipath channels. Computer simulation is used to study this adaptive SVM MUD, and the results show that it can closely match the performance of the optimal Bayesian one-shot detector, using a relatively small training data block.