In order to achieve blind detection, the classic sub-space tracking method used the received signal sample matrix to get the eigenvalue decomposition (EVD) or ralph lauren polo shirts singular value decomposition (SVD). However, these two algorithms are highly complex. PASTd algorithm because of low complexity have been widely used in multi-user detection. However, discount wedding dresses PASTd algorithm to track the signal subspace is not orthogonal, resulting in very slow cheap wedding gown dresses convergence rate. In response to this question, this the flat iron shop for us paper Proposed an improved algorithm which is based on the prediction orthogonal approximation subspace tracking algorithm (OPAST)——positive definite matrix OPAST algorithm. And this new algorithm is applied to subspace blind MMSE multi-user detection. The simulation results prove that this improved positive definite matrix OPAST sub-space algorithm for multi-user detector has stable global sell discount wedding dresses convergence, and maintain much less computation complexity, so in the anti-MAI respect also has higher performance. This show that the positive definite matrix OPAST sub-space algorithm for multi-user detector is a better feasible solution.
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