基于子空间跟踪的修正MMSE多用户检测算法

A Modified MMSE Multi-user Detection Algorithm Based on Subspace Tracking

在研究基于子空间跟踪的最小均方误差(MMSE)多用户检测器(MUD)的基础上,为解决原算法因引入特征值估计误差而导致检测性能下降的问题,设计了一种改进的算法———修正的MMSE多用户检测器.采用正交性能优良的OPAST算法跟踪子空间,提出一种基于OPAST的修正MMSE多用户检测算法.仿真结果显示,与基于OPAST的MMSE MUD相比,基于OPAST的修正MMSE MUD算法收敛速度快,输出信干比和误码率性能逼近SVD MUD算法,并且计算复杂度较低.

Abstract： The minimum mean square error （MMSE） muhiuser detectors （MUDs） based on subspace tracking are deeply investigated, and an improved algorithm, i.e. , a modified MMSE muhiuser detector is designed to solve the problems of detecting performance degradation on traditional algorithm caused by eigenvalue estimation errors. The orthogonal projection approximation subspace tracking （OPAST） algorithm with good orthogonality is used to track the subspace, and a modified MMSE muhiuser detection algorithm based on OPAST is proposed. The simulation results show that, compared with the OPAST-based MMSE MUDs, the proposed modified MMSE algorithm based on OPAST offers faster convergence rate, its output SIR（ signal to interference ratio） and bit error rate （BER） are close to those of the SVD（singular value decomposition） MUD method, and it reduces the computational complexity.