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Tree-based optimized forward scheme for pilot placement in OFDM sparse channel estimation

机译:OFDM稀疏信道估计中基于树的导频布局优化前向方案

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The problem of channel estimation in Orthogonal Frequency Division Multiplexing (OFDM) systems Is here investigated. In particular, channels exhibiting a temporal response with sparse structure are considered. For fast fading channels, we consider the comb type estimation where we address the pilot allocation optimization by applying the recent Compressed Sensing (CS) theory. This optimization reduces to the choice of the CS decomposition basis, deduced from the Discrete Fourier Transform (DFT) matrix as a selection of rows associated with the pilot subcarriers. It has been demonstrated that the optimal CS basis, respecting the coherence measure minimization, corresponds to that based on Cyclic: Difference Sets (CDS). In this contribution, for unavailable CDS, we propose a forward tree-based near-optimal pilot allocation scheme. This scheme, builds up iteratively the CS decomposition basis and minimizes the coherence measure in each iteration. It is shown that the proposed method attains a slightly enhanced performance compared to existing schemes yet with considerably reduced complexity which can be really beneficial in high mobility scenarios.
机译:本文研究了正交频分复用(OFDM)系统中的信道估计问题。特别地,考虑表现出具有稀疏结构的时间响应的信道。对于快速衰落的信道,我们考虑使用最新的压缩感知(CS)理论解决梳形分配优化问题的梳状类型估计。这种优化减少了对CS分解基础的选择,这是从离散傅里叶变换(DFT)矩阵推导出的,作为与导频子载波相关的行的选择。已经证明,关于相干度量最小化的最佳CS基础对应于基于循环:差异集(CDS)的基础。在此贡献中,对于不可用的CDS,我们提出了一种基于前向树的近最优导频分配方案。该方案迭代地建立了CS分解基础,并在每次迭代中最小化了相干性度量。结果表明,与现有方案相比,所提出的方法性能略有提高,但复杂度却大大降低,这在高移动性场景中确实是有益的。

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