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Sparsity-based Channel Estimation in Visible Light Communication

机译:可见光通信中基于稀疏性的信道估计

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This paper considers a multi-user multiple-input multiple-output (MU-MIMO) visible light communication (VLC) interference channel system with massive light emitting diode (LED) arrays. Compared with the perfect channel state information (CSI), the sparse loss of channel is more realistic in VLC applications due to obstruction of the light, which may significantly degrade the performance of transmission. Hence, the robustness is a crucial issue. We estimate the transmitted signal and take the sparse loss into account for an indoor VLC system with imperfect CSI. The standard CVX method is used to minimize the ℓ1-norm that subjects to the constraints on the channel uncertainty and signal estimation. Moreover, considered the sparsity of channel imperfection, an iterative algorithm based on alternating direction method of multipliers (ADMM) is proposed to further solve the underlying estimation problem. Simulation results indicate that the iteration method offers higher robustness against channel uncertainty in different scenarios than the standard CVX method.
机译:本文考虑了具有大规模发光二极管(LED)阵列的多用户多输入多输出(MU-MIMO)可见光通信(VLC)干扰信道系统。与完美的信道状态信息(CSI)相比,由于光的阻塞,在VLC应用中信道的稀疏损失更为现实,这可能会大大降低传输性能。因此,鲁棒性是至关重要的问题。对于带有不完善CSI的室内VLC系统,我们估计传输信号并考虑稀疏损耗。标准CVX方法用于最小化 1 -规范受信道不确定性和信号估计的约束。此外,考虑到信道缺陷的稀疏性,提出了一种基于乘法器交替方向法(ADMM)的迭代算法,以进一步解决潜在的估计问题。仿真结果表明,与标准CVX方法相比,该迭代方法在不同场景下具有更高的鲁棒性以应对信道不确定性。

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