Title :
Adaptive multiuser receiver using a support vector machine technique
Author :
Chen, S. ; Samingan, A.K. ; Hanzo, L.
Author_Institution :
Dept. of Electron. & Comput. Sci., Southampton Univ., UK
Abstract :
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
Keywords :
adaptive signal detection; code division multiple access; learning automata; multiuser channels; radio receivers; spread spectrum communication; DS-CDMA signals; adaptive SVM MUD; adaptive multiuser receiver; adaptive nonlinear multiuser detector; computer simulation; direct-sequence code-division multiple-access; learning technique; multipath channels; optimal Bayesian one-shot detector; small training data block; support vector machine; Adaptive signal detection; Application software; Bayesian methods; Computer simulation; Detectors; Machine learning; Multiaccess communication; Multipath channels; Multiuser detection; Support vector machines;
Conference_Titel :
Vehicular Technology Conference, 2001. VTC 2001 Spring. IEEE VTS 53rd
Conference_Location :
Rhodes
Print_ISBN :
0-7803-6728-6
DOI :
10.1109/VETECS.2001.944914
