Adaptive sparse channel estimation for time-variant MIMO-OFDM systems
Adaptive sparse channel estimation for time-variant MIMO-OFDM systems
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DOI：
10.1109/iwcmc.2013.6583673
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发表时间：
2013-02
期刊：
影响因子：
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通讯作者：
Guan Gui;F. Adachi
中科院分区：
文献类型：
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作者：
Guan Gui;F. Adachi
在采用正交频分复用(OFDM)调制的时变多输入多输出(MIMO)通信系统中，相干检测需要准确的信道状态信息(CSI)。基于归一化最小均方(NLMS)的自适应信道估计是一种低复杂度、稳定的自适应信道估计方法。然而，它不能利用MIMO信道固有的稀疏性，这种稀疏性的特点是只有几个主要的信道抽头。本文针对时变MIMO-ofdm系统，提出了两种利用稀疏结构信息的自适应稀疏信道估计方法。与传统的基于NLMS的方法不同，通过在NLMS算法的代价函数中引入稀疏惩罚，实现了两种方法。计算机仿真证实了所提出的ASCE比传统ACE具有明显的性能优势。
Accurate channel state information (CSI) is required for coherent detection in time-variant multiple-input multiple-output (MIMO) communication systems using orthogonal frequency division multiplexing (OFDM) modulation. One of low-complexity and stable adaptive channel estimation (ACE) approaches is the normalized least mean square (NLMS)-based ACE. However, it cannot exploit the inherent sparsity of MIMO channel which is characterized by a few dominant channel taps. In this paper, we propose two adaptive sparse channel estimation (ASCE) methods to take advantage of such sparse structure information for time-variant MIMO-OFDM systems. Unlike traditional NLMS-based method, two proposed methods are implemented by introducing sparse penalties to the cost function of NLMS algorithm. Computer simulations confirm obvious performance advantages of the proposed ASCEs over the traditional ACE.