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Model-Based Correlated Channels Estimation

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Abstract

In this paper we propose a noisy Multivariate Autoregressive (MVAR) process for modeling and estimating the correlated fading channels. The method can estimate joint MVAR processes and model parameters from noisy received signal. The proposed method is based on serial connection of two algorithms. In the first algorithm, we estimate MVAR model parameters. For this purpose, a combination of Yule–Walker equations is used. This combination is considered as a generalized eigenvalue problem; an estimate for receiver noise variance is obtained by solving this eigenvalue problem then Least-Squares method is used to estimate the MVAR model parameters. In the second algorithm, the fading process is estimated by using Kalman filter. Simulation results show that the proposed method has good performance compared with other existing methods.

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Authors and Affiliations

  1. Electrical Engineering Department, Faculty of Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran

    Alimorad Mahmoudi

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  1. Alimorad Mahmoudi
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Correspondence to Alimorad Mahmoudi.

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Mahmoudi, A. Model-Based Correlated Channels Estimation. Wireless Pers Commun 92, 483–493 (2017). https://doi.org/10.1007/s11277-016-3553-9

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  • DOI: https://doi.org/10.1007/s11277-016-3553-9

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