The Application of Successive Quadratic Programming Algorithm to Multiuser Detection in CDMA

In this paper, based on the semidefinite programming relaxation of the CDMA maximum likelihood (ML) multiuser detection problem, a detection strategy by the successive quadratic programming algorithm is presented. Coupled with the randomized cut generation scheme, we obtain the suboptimal solution of multiuser detection problem. Comparing with the reported interior point methods based on semidefinite programming, simulations demonstrate that the successive quadratic programming algorithm often yields the similar BER performances of the multiuser detection problem. But the average CPU time of this approach is significantly reduced. Xuewen Mu received the MS degree in applied mathematics from the Xidian University in 2004 and the PhD degree in applied mathematics in 2006. His current research interests include the applications of the semidefinite programming and the combinatorial programming.