Study of multiuser detection: the support vector machine approach

Authors:
Tao Yang;Bo Hu
Affiliations:
Department of Electronics Engineering, Fudan University, Shanghai, China;Department of Electronics Engineering, Fudan University, Shanghai, China
Venue:
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part II
Year:
2005

Citing 4
Cited 1

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Support Vector Machines: Theory and Applications (Studies in Fuzziness and Soft Computing)
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Abstract

In this paper, a support vector machine (SVM) multi-user receiver based on competition learning (CL) strategy is proposed. The new algorithm adopts a heuristic approach to extend standard SVM algorithm for multiuser classification problem, and also a clustering analysis is applied to reduce the total amount of computation. In implementation of multi-user receiver, an asymptotical iterative algorithm is used to guide the learning of the input sample pattern. The digital result shows that the new multi-user detector scheme has a relatively good performance comparing with the conventional MMSE detector especially under the heavy interference environment.