UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

FFDNet-Based Channel Estimation for Massive MIMO Visible Light Communication Systems

Gao, Z; Wang, Y; Liu, X; Zhou, F; Wong, KK; (2020) FFDNet-Based Channel Estimation for Massive MIMO Visible Light Communication Systems. IEEE Wireless Communications Letters , 9 (3) pp. 340-343. 10.1109/LWC.2019.2954511. Green open access

[img]
Preview
Text
FFDNet-Based Channel Estimation for m-MIMO VLC systems_.pdf - Accepted version

Download (371kB) | Preview

Abstract

Channel estimation is of crucial importance in massive multiple-input multiple-output (m-MIMO) visible light communication (VLC) systems. In order to tackle this problem, a fast and flexible denoising convolutional neural network (FFDNet)-based channel estimation scheme for m-MIMO VLC systems was proposed. The channel matrix of the m-MIMO VLC channel is identified as a two-dimensional natural image since the channel has the characteristic of sparsity. A deep learning-enabled image denoising network FFDNet is exploited to learn from a large number of training data and to estimate the m-MIMO VLC channel. Simulation results demonstrate that our proposed channel estimation based on the FFDNet significantly outperforms the benchmark scheme based on minimum mean square error.

Type: Article
Title: FFDNet-Based Channel Estimation for Massive MIMO Visible Light Communication Systems
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/LWC.2019.2954511
Publisher version: https://doi.org/10.1109/LWC.2019.2954511
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Channel estimation, m-MIMO, visible light communication, FFDNet, deep learning
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/10094118
Downloads since deposit
57Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item