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Maximum Likelihood Based Channel Delay Estimation with Limited Number of Samples Using Diagonal Matrix Approximation

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Abstract

To achieve fast and computationally simplified channel estimation, we propose a maximum likelihood estimation (MLE) based “diagonal matrix approximation” (DMA) scheme which provides an effective solution to overcome the conflict between estimation accuracy, acquisition time, and complexity. Together with over sampling, the proposed scheme exhibits a performance approaching the Cramér-Rao Lower Bound (CRLB), while keeping computational complexity linear to the signal dimensions. The DMA scheme can still perform well even when the sample estimate of the covariance matrix, due to insufficient number of observation samples, is singular. Therefore, the proposed scheme is a viable solution for fast channel estimation.

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Authors and Affiliations

  1. Center for Communications and Signal Processing Research, New Jersey Institute of Technology, 323 Martin Luther King Blvd., Newark, NJ, 07102-1982, U.S.A.

    X. Tang & Y. Bar-Ness

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  1. X. Tang
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  2. Y. Bar-Ness
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Tang, X., Bar-Ness, Y. Maximum Likelihood Based Channel Delay Estimation with Limited Number of Samples Using Diagonal Matrix Approximation. Wireless Personal Communications 27, 183–194 (2003). https://doi.org/10.1023/B:WIRE.0000010146.60266.4e

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  • DOI: https://doi.org/10.1023/B:WIRE.0000010146.60266.4e

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