NDLI: Adaptive CIR prediction of time-varying channels for OFDM systems

Content Provider	IEEE Xplore Digital Library
Author	Oyerinde, O.O. Mneney, S.H.
Copyright Year	2009
Description	Author affiliation: School of Electrical, Electronic and Computer Engineering, University of KwaZulu-Natal, Durban, 4041, South Africa (Oyerinde, O.O.; Mneney, S.H.)
Abstract	Channel Impulse Response (CIR) prediction is important because it makes possible the provision of up-to-date channel state information which is essential for coherent detection of transmitted message symbols. Different prediction techniques have been proposed for OFDM systems. These range from the Minimum Mean Square Error (MMSE) techniques to Adaptive techniques. However, it has been confirmed that the adaptive predictors present better performance than its MMSE counterpart. Besides, the computational complexity of the MMSE class of predictors is more costly than the adaptive predictors. In this paper we propose an improved version of an adaptive Normalized Least Mean Square (NLMS) predictor named Variable Step Size Normalized Least Mean Square (VSSNLMS) predictor. The proposed VSSNLMS predictor is employed for the implementation of Decision Directed Channel Estimation (DDCE) for OFDM systems. Simulation results demonstrate that the proposed VSSNLMS predictor outperforms the NLMS predictor at a cost of a negligible high complexity, and its performance is very close to that of the Recursive Least Square (RLS) predictor that exhibits an enormous computational complexity.
Starting Page	1
Ending Page	5
File Size	462245
Page Count	5
File Format	PDF
ISBN	9781424439188
DOI	10.1109/AFRCON.2009.5308342
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-09-23
Publisher Place	Kenya
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Time-varying channels OFDM Computational complexity Channel state information Mean square error methods Channel estimation Computational modeling Predictive models Costs Least squares methods orthogonal frequency division multiplexing(OFDM) Channel impulse response (CIR) prediction adaptive predictors time-varying channels
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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