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Greedy approach to sparse multi-path channel estimation using sensing dictionary

机译:利用感知字典的稀疏多径信道估计的贪婪方法

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As most components of sparse multi-path channel (SMPC) are zero, impulse response of SMPC can be recovered from a short training sequence. Although the ordinary orthogonal matching pursuit (OMP) algorithm provides a very fast implementation of SMPC estimation, it suffers from inter-atom interference (IAI), especially in the case of SMPC with a large delay spread and a short training sequence. In this paper, an adaptive IAI mitigation method is proposed to improve the performance of SMPC estimation based on a general OMP algorithm. Unlike the ordinary OMP algorithm, a sensing dictionary is designed adaptively and posterior information is utilized efficiently to prevent false atoms from being selected due to serious IAI. Numeral experiments illustrate that the proposed general OMP algorithm based on adaptive IAI mitigation outperforms both the ordinary OMP algorithm and the general OMP algorithm based on non-adaptive IAI mitigation. Copyright © 2011 John Wiley & Sons, Ltd.
机译:由于稀疏多径信道(SMPC)的大多数分量为零,因此可以从较短的训练序列中恢复SMPC的冲激响应。尽管普通的正交匹配追踪(OMP)算法提供了SMPC估计的非常快速的实现,但是它受到原子间干扰(IAI)的困扰,特别是在SMPC的情况下,该方法具有较大的时延扩展和较短的训练序列。本文提出了一种自适应的IAI缓解方法,以提高基于通用OMP算法的SMPC估计的性能。与普通的OMP算法不同,自适应设计感测字典,并有效利用后验信息,以防止由于严重的IAI而选择虚假原子。大量实验表明,提出的基于自适应IAI缓解的通用OMP算法优于常规OMP算法和基于非自适应IAI缓解的通用OMP算法。版权所有©2011 John Wiley&Sons,Ltd.

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