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Performance evaluation of combined methods for the estimation of fading coefficients of uncorrelated signal sources in multipath propagation

机译:多径传播中不相关信号源衰落系数估计组合方法的性能评估

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In this study, we consider the challenge of estimation of fading coefficients for uncorrelated sources in the presence of multipath propagation. The combination of Joint Approximate Diagonalization of Eigenmatrices (JADE) and some well-known high-resolution algorithms such as Multiple Signal Classification (MUSIC), Minimum norm (Min-norm) and Modified Forward Backward Linear Prediction (MFBLP) are utilized to estimate the fading coefficients of a challenging environment containing many correlated signals. The results are compared with Estimation of Signal Parameters by Rotational Invariance Techniques (ESPRIT) based method in the literature. Several independent trials are performed and it is shown that the combined method of JADE and MFBLP has satisfactory fading coefficient performance even at very low signal-to-noise (SNR) levels and low number of antenna elements and data sample.
机译:在这项研究中,我们考虑了在存在多径传播的情况下估计不相关信号源的衰落系数所面临的挑战。本征矩阵的联合近似对角化(JADE)和一些著名的高分辨率算法(例如多信号分类(MUSIC),最小范数(Min-norm)和修正的前向后线性预测(MFBLP))相结合来估算包含许多相关信号的具有挑战性的环境的衰落系数。将结果与文献中基于旋转不变技术(ESPRIT)的方法的信号参数估计相比较。进行了几次独立的试验,结果表明,即使在非常低的信噪比(SNR)和少量天线元件和数据样本的情况下,JADE和MFBLP的组合方法也具有令人满意的衰落系数性能。

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