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2015 | OriginalPaper | Chapter

Proposal of Channel Prediction by Complex-Valued Neural Networks that Deals with Polarization as a Transverse Wave Entity

Authors : Tetsuya Murata, Tianben Ding, Akira Hirose

Published in: Neural Information Processing

Publisher: Springer International Publishing

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Abstract

Multipath fading is one of the most serious problems in mobile communications. Various methods to solve or mitigate it have been proposed in time or frequency domain. Previously we proposed a channel prediction method that combines complex-valued neural networks and chirp z-transform that utilizes both the time- and frequency-domain representation, resulting in much higher performance. In this paper, we propose to deal with polarization additionally in its adaptive channel prediction to improve the performance further. A preliminary experiment demonstrates improvement larger than what is expected by a simple diversity gain.

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Metadata
Title
Proposal of Channel Prediction by Complex-Valued Neural Networks that Deals with Polarization as a Transverse Wave Entity
Authors
Tetsuya Murata
Tianben Ding
Akira Hirose
Copyright Year
2015
Book
Neural Information Processing

Print ISBN: 978-3-319-26554-4

Electronic ISBN: 978-3-319-26555-1

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-3-319-26555-1_61

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