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Sparsity based adaptive thresholding for DFE in SC-FDMA

机译:SC-FDMA中基于稀疏性的DFE自适应阈值

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For single-carrier systems with frequency domain equalization, such as SC-FDMA, decision feedback equalization (DFE) performs better than linear equalization and has much lower computational complexity than sequence maximum likelihood detection. The main challenge in DFE is the feedback symbol selection rule. In this paper, we give a theoretical framework for a simple, sparsity based thresholding algorithm. We feed back multiple symbols in each iteration, so the algorithm converges fast and has a low computational cost. We show how the initial solution can be obtained via convex relaxation instead of linear equalization. Numerical results illustrate significant performance improvement in terms of bit error rate compared to the MMSE solution.
机译:对于具有频域均衡的单载波系统(例如SC-FDMA),判决反馈均衡(DFE)的性能优于线性均衡,并且计算复杂度比序列最大似然检测低得多。 DFE中的主要挑战是反馈符号选择规则。在本文中,我们给出了一种基于稀疏性的简单阈值算法的理论框架。我们在每次迭代中反馈多个符号,因此该算法收敛速度快且计算成本低。我们展示了如何通过凸松弛而不是线性均衡来获得初始解。数值结果表明,与MMSE解决方案相比,就误码率而言,性能得到了显着改善。

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