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Design of Sparse FIR Decision Feedback Equalizers in MIMO Systems Using Hybrid l1/l2 Norm Minimization and the OMP Algorithm

机译:基于混合l1 / l2范数最小化和OMP算法的MIMO系统稀疏FIR决策反馈均衡器设计。

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摘要

In this paper, a novel scheme using hybrid l1/l2 norm minimization and the orthogonal matching pursuit (OMP) algorithm is proposed to design the sparse finite impulse response (FIR) decision feedback equalizers (DFE) in multiple input multiple output (MIMO) systems. To reduce the number of nonzero taps for the FIR DFE while ensuring its design accuracy, the problem of designing a sparse FIR DFE is transformed into an l0 norm minimization problem, and then the proposed scheme is used to obtain the sparse solution. In the proposed scheme, a sequence of minimum weighted l2 norm problems is solved using the OMP algorithm. The nonzero taps positions can be corrected with the different weights in the diagonal weighting matrix which is computed through the hybrid l1/l2 norm minimization. The simulation results verify that the sparse FIR MIMO DFEs designed by the proposed scheme get a significant reduction in the number of nonzero taps with a small performance loss compared to the non-sparse optimum DFE under the minimum mean square error (MMSE) criterion. In addition, the proposed scheme provides better design accuracy than the OMP algorithm with the same sparsity level.
机译:提出了一种使用混合l1 / l2范数最小化和正交匹配追踪(OMP)算法的新方案,以设计多输入多输出(MIMO)系统中的稀疏有限脉冲响应(FIR)判决反馈均衡器(DFE)。 。为了在确保FIR DFE设计精度的同时减少非零抽头的数量,将设计稀疏FIR DFE的问题转化为10范数最小化问题,然后将所提出的方案用于获得稀疏解。在提出的方案中,使用OMP算法解决了一系列最小加权l2范数问题。可以使用对角加权矩阵中的不同权重来校正非零抽头位置,该对角加权矩阵是通过混合l1 / l2范数最小化计算的。仿真结果证明,与最小均方误差(MMSE)准则下的非稀疏最佳DFE相比,所提出的方案设计的稀疏FIR MIMO DFE与非稀疏最佳DFE相比,可显着减少非零抽头数量。此外,与具有相同稀疏度的OMP算法相比,所提方案具有更好的设计精度。

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