基于压缩感知技术的双向中继信道估计

Two-way Relay Channel Estimation Based on Compressive Sensing

  • 摘要: 设计了一种基于压缩感知(compressive sensing, CS)技术的双向中继信道(two-way relay channels, TWRC)估计方法,并具体采用正交匹配追踪算法(orthogonal matching pursuit, OMP)对OFDM系统下的信道脉冲响应进行估计。双向中继信道往往呈现出稀疏多径结构,这种结构会随着信号空间维数的增大而越加明显。传统的线性估计方法没有考虑到TWRC的潜在稀疏性,因而导致了对关键通信资源的过度使用。而基于CS的TWRC估计方法能够很好地利用这种传输信道的稀疏多径结构,与传统线性估计方法相比,在获得同样估计性能的前提下,需要的训练序列长度大大减少,有效地提高了频谱、能量等资源利用率。同时,所采用的OMP算法的时间复杂度主要依赖于信道稀疏度,因此计算效率往往比传统的方法高。仿真也证实了基于CS的TWRC估计算法的优越性。

     

    Abstract: A method of two-way relay channel (TWRC) estimation based on compressive sensing (CS) is designed in this paper. We specifically introduce the orthogonal matching pursuit (OMP) algorithm to reconstruct the channel impulse response under the OFDM system. Two-way relay channels tend to exhibit sparse multipath structure, and this structure will be more conspicuous when the dimension of signal space is increasing. Traditional linear estimation methods are incapable of exploiting the potential sparsity of two-way relay channels, thus leading to excessive use of critical communication resources. On the contrary, the method of two-way relay channel estimation based on compressive sensing can fully exploit the sparse multipath structure of this kind transmission channel. By contrast to traditional linear estimation methods, the method of TWRC based on CS needs much less training sequence under the same estimation performance. As a result, the introduced method effectively improves the utilization of communication resources such as spectrum and energy. At the same time, the computational efficiency of the introduced OMP algorithm is always higher than traditional methods as its computational complexity mainly relies on the sparse degree of multipath channels. Simulation results confirm the method of TWRC estimation based on CS.

     

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