摘要

In this article, a detection strategy based on variable neighborhood search (VNS) and semidefinite relaxation of the multiuser model maximum likelihood (ML) is investigated. The VNS method provides a good method for solving the ML problem while keeping the integer constraints. A SDP relaxation is used as an efficient way to generate an initial solution in a limited amount of time, in particular using early termination. The SDP resolution tool used is the spectral bundle method developed by Helmberg. We show that using VNS can result in a better error rate, but at a cost of calculation time.

  • 出版日期2010-5

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