Adaptive Multiuser Channel Estimation using Reduced Kalman/LMS Algorithm

Authors:
Amit Kumar Kohli;D. K. Mehra
Affiliations:
Department of Electronics and Communication Engineering, Thapar University, Patiala, India 147004;Department of Electronics and Computer Engineering, Indian Institute of Technology Roorkee, Roorkee, India 247667
Venue:
Wireless Personal Communications: An International Journal
Year:
2008

Citing 8
Cited 1

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Prediction in LMS-type adaptive algorithms for smoothly timevarying environments

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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.