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COD: Diversity-Adaptive Subspace Processing for Multipath Separation and Signal Recovery

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Abstract

This paper proposes a generalized multipath separability condition for subspace processing and derives a novel COD (Combined Oversampling and Displacement) algorithm to utilize both spatial and temporal diversities for path separation, DOA (Direction of Arrival) estimation and signal recovery. A unique advantage lies in its ability to cope with the situation where the number of multipaths is larger than that of antenna elements, which has not been treated in the traditional approaches. COD strategy solves the antenna deficiency problem by combining vertical expansion with temporal oversampling and horizontal expansion with spatial displacement. We provide a detailed analysis on the theoretical footings for COD factorization and multipath separability conditions, which naturally leads to COD path separation and DOA estimation algorithms. Another advantage of COD factorization hinges upon its ability to generate a multiplicity of eigenvalues which greatly facilitates a SIMO channel equalization formulation useful for signal recovery. This paper also proposes a frequency-domain total-least-square algorithm for SIMO equalization procedure. Finally, simulation results on path separation, DOA estimation and signal recovery are demonstrated.

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Authors and Affiliations

  1. Dept. of Electrical Engineering, Princeton University, Princeton, NJ, 08544-5263

    Xinying Zhang & S.-Y. Kung

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  1. Xinying Zhang
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  2. S.-Y. Kung
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Zhang, X., Kung, SY. COD: Diversity-Adaptive Subspace Processing for Multipath Separation and Signal Recovery. The Journal of VLSI Signal Processing-Systems for Signal, Image, and Video Technology 30, 235–256 (2002). https://doi.org/10.1023/A:1014011328534

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