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Narrow-band interference mitigation using compressive sensing in AF-OFDM systems

机译:AF-OFDM系统中使用压缩感测的窄带干扰缓解

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In this paper, narrow-band interference (NBI) mitigation is addressed in amplify-and-forward orthogonal-frequency-division-multiplexing (AF-OFDM) cooperative communication systems. Based on the channel gains between the interferer, destination and the relay nodes, three copies of the NBI are received at the destination node in addition to the desired signal. Hence, NBI degrades the performance of AF-OFDM systems which motivates the need for mitigation techniques to reduce its effect. NBI is a sparse signal in the frequency-domain, hence, compressive sensing (CS) framework can be used to estimate and cancel the NBI before detecting the transmitted signal. However, frequency-grid-mismatch destroys the sparsity of NBI in the frequency domain at the destination terminal. A structured-dictionary-mismatch formulation is proposed to approximate the received NBI vector by two sparse vectors. An £2,1 norm minimization problem is solved to recover the sparse vectors. The recovered NBI is then canceled from the received signal before detection. Simulation results demonstrate the merits of the proposed approach.
机译:在本文中,在放大转发正交频分复用(AF-OFDM)协作通信系统中解决了窄带干扰(NBI)的缓解问题。根据干扰源,目标节点和中继节点之间的信道增益,除了所需信号之外,在目标节点还接收到NBI的三个副本。因此,NBI降低了AF-OFDM系统的性能,这激发了对减轻技术以降低其影响的需求。 NBI是频域中的稀疏信号,因此,压缩检测(CS)框架可用于在检测到传输信号之前估计和消除NBI。但是,频率网格不匹配会破坏目标终端在频域中NBI的稀疏性。提出了一种结构字典不匹配公式,以通过两个稀疏向量来近似接收到的NBI向量。解决了£2,1范数最小化问题,以恢复稀疏向量。然后在检测之前从接收到的信号中取消恢复的NBI。仿真结果证明了该方法的优点。

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