基于压缩感知的MIMO NC-OFDM系统信道估计算法
首发时间:2014-02-17
摘要:多天线不连续正交频分复用(multiple-input multiple-output non- contiguous orthogonal frequency division multiplexing,MIMO NC-OFDM)系统是认知无线电(Cognitive Radio,CR)系统的常用体制,由于授权户占用而导致的载波不连续情况下的信道估计是影响该系统性能的关键技术问题。本文提出一种基于压缩感知(Compressed Sensing,CS)的MIMO NC-OFDM系统的信道估计方法。该方法利用多天线无线信道的时域稀疏性,采用稀疏自适应匹配追踪(Sparsity Adaptive Matching Pursuit, SAMP)算法对MIMO NC-OFDM系统时域信道脉冲响应进行估计。仿真结果表明,所提出的压缩感知信道估计算法在频谱利用率以及估计性能方面有较大改善。
关键词: 通信与信息系统 多输入多输出-不连续正交频分复用 认知无线电 压缩感知 信道估计 稀疏自适应匹配追踪
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Compressed Sensing Based Sparse Channel Estimation in MIMO NC-OFDM Systems
Abstract:Multiple-input multiple-output non-contiguous orthogonal frequency division multiplexing (MIMO NC-OFDM) is a commonly used system in Cognitive Radio (CR). One of the key technical affecting the MIMO NC-OFDM performance is channel estimation in the condition of non-continuous carrier caused by licensed users' occupation. A new method of channel estimation based on Compressed Sensing (CS) is proposed in MIMO NC-OFDM system. This scheme takes advantage of the time domain channel sparsity in wireless channel, using compressed sensing method of Sparsity Adaptive Matching Pursuit (SAMP) to estimate the time-domain impulse response of MIMO NC-OFDM channels. Theoretical simulations show that the new channel estimation methods in spectrum utilization and performance than existing MIMO NC-OFDM channel estimation methods have improved significantly.
Keywords: Communication and Information System Multiple-input multiple-output non-contiguous orthogonal frequency division multiplexing Cognitive Radio Compressed Sensing channel estimation Sparsity Adaptive Matching Pursuit
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