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arXiv 1005.2269cs.ITcs.NImath.IT
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宽带通信系统中基于DS算法的稀疏多径信道估计

Sparse Multipath Channel Estimation using DS Algorithm in Wideband Communication Systems

Guan Gui, An-min Huang, Qun Wan

摘要:

宽带无线信道是一种时间色散信道,具有很强的频率选择性。然而,在大多数情况下,信道由少数主导抽头组成,并且大部分抽头近似为零或零。它们通常被称为稀疏多径信道(MPC)。传统的线性MPC方法,如最小二乘(LS),不利用MPC的稀疏性。通常,即使在存在噪声的情况下,也可以通过求解LASSO问题来获得精确的稀疏MPC估计器。本文提出了一种新的基于CS的稀疏MPC方法,该方法使用Dantzig选择器(DS)[1]。这种方法利用信道的稀疏性来减少训练序列的数量,因此,与现有的方法相比,利用计算机模拟,提高频谱效率。

英文摘要:

Wideband wireless channel is a time dispersive channel and becomes strongly frequency-selective. However, in most cases, the channel is composed of a few dominant taps and a large part of taps is approximately zero or zero. They are often called sparse multi-path channels (MPC). Conventional linear MPC methods, such as the least squares (LS), do not exploit the sparsity of MPC. In general, accurate sparse MPC estimator can be obtained by solving a LASSO problem even in the presence of noise. In this paper, a novel CS-based sparse MPC method by using Dantzig selector (DS) [1] is introduced. This method exploits a channel's sparsity to reduce the number of training sequence and, hence, increase spectral efficiency when compared to existed methods with computer simulations.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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