采用最小角回归的稀疏MIMO均衡器设计方法

doi:10.19665/j.issn1001-2400.2019.01.012

Abstract

Abstract:

A new scheme for designing sparse finite impulse response (FIR) decision feedback equalizers(DFE) in multiple input multiple output(MIMO) systems based on the Least Angle Regression(LARS) algorithm is proposed. To decrease the number of nonzero taps for FIR DFE and reduce computational complexity, the problem of designing sparse FIR DFE is transformed into an l₁-norm minimization approach, and the proposed design scheme is applied to compute the locations and weights of the nonzero taps for sparse FIR DFE iteratively. Simulation results show that when compared with the optimum Minimum Mean Square Error(MMSE) non-sparse solution for a small given performance loss, the number of nonzero taps for the proposed sparse equalizer design is reduced by more than 70%, while the maximum SNR loss for the proposed sparse equalizer is just about 0.3dB in the Vehicular A channel, which results in an effective trade-off between performance and computational complexity.

Key words: multiple input multiple output, decision feedback equalization, sparse representation, least angle regression

CLC Number:

TN92

YU Lihong,ZHAO Jiaxiang. Design of sparse MIMO equalizers using least angle regression[J].Journal of Xidian University, 2019, 46(1): 73-78.

Figures/Tables 3

References 13

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Design of sparse MIMO equalizers using least angle regression

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