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Adaptive Multiuser Channel Estimation using Reduced Kalman/LMS Algorithm

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Abstract

This paper presents an adaptive multiuser channel estimator using the reduced-Kalman least-mean-square (RK-LMS) algorithm. The frequency-selective fading channel is modeled as a tapped-delay-line filter with smoothly time-varying Rayleigh distributed tap coefficients. The multiuser channel estimator based on minimum-mean-square-error (MMSE) criterion is used to predict the filter coefficients. We also present its convergence characteristics and tracking performance using the RK-LMS algorithm. Unlike the previously available Kalman filtering algorithm based approach (Chen, Chen IEEE Trans Signal Process 49(7): 1523–1532, 2001) the incorporation of RK-LMS algorithm reduces the computational complexity of multiuser channel estimator used in the code division multiple access wireless systems. The computer simulation results are presented to demonstrate the substantial improvement in its tracking performance under the smoothly time-varying environment.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, Thapar University, Patiala, 147004, Punjab, India

    Amit Kumar Kohli

  2. Department of Electronics and Computer Engineering, Indian Institute of Technology Roorkee, Roorkee, 247667, India

    D. K. Mehra

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  1. Amit Kumar Kohli
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  2. D. K. Mehra
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Correspondence to Amit Kumar Kohli.

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Kohli, A.K., Mehra, D.K. Adaptive Multiuser Channel Estimation using Reduced Kalman/LMS Algorithm. Wireless Pers Commun 46, 507–521 (2008). https://doi.org/10.1007/s11277-008-9450-0

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  • DOI: https://doi.org/10.1007/s11277-008-9450-0

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