NDLI: Fading channel prediction based on complex-valued neural networks in frequency domain

Content Provider	IEEE Xplore Digital Library
Author	Tianben Ding Hirose, A.
Copyright Year	2013
Description	Author affiliation: Dept. of Electr. Eng. & Inf. Syst., Univ. of Tokyo, Tokyo, Japan (Tianben Ding; Hirose, A.)
Abstract	Channel prediction is an important process for channel compensation in fading environment. If a future channel state is predicted, adaptive techniques such as pre-equalization and transmission power control is applicable before transmission in order to avoid degradation of communication quality. Previously, we proposed frequency-domain channel prediction methods employing the chirp z-transform with a linear extrapolation as well as a Lagrange-based nonlinear extrapolation of frequency-domain parameters. This paper presents a highly accurate method for predicting time-varying channels by using a complex-valued neural-network (CVNN) based prediction of frequency-domain channel characteristics. We demonstrate that the channel prediction accuracy of our CVNN method is better than those of the previous linear- and Lagrange-extrapolation prediction in a series of simulations for orthogonal frequency division multiplexing (OFDM) communications.
Sponsorship	Electron. Soc., Inst. Electron. Inf. Commun. Eng.
Starting Page	640
Ending Page	643
File Size	498957
Page Count	4
File Format	PDF
ISBN	9781467349390
e-ISBN	9784885522772
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-05-20
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	IEICE Institute of Electronics Informati
Subject Keyword	Fading Extrapolation Chirp Frequency-domain analysis OFDM Bit error rate Predictive models
Content Type	Text
Resource Type	Article

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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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