Deep learning based BER improvement for NOMA-VLC systems with perfect and imperfect successive interference cancellation
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Published:2023-06-08
Issue:8
Volume:55
Page:
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ISSN:0306-8919
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Container-title:Optical and Quantum Electronics
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language:en
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Short-container-title:Opt Quant Electron
Author:
Salama Wessam M.,Aly Moustafa H.,Amer Eman S.
Abstract
AbstractThis paper focuses in the improvement of the BER performance of multiple-input multiple-output (MIMO) systems is investigated utilizing non-orthogonal multiple access-visible light communication (NOMA-VLC). Applying multi-user downlink MIMO-NOMA-VLC system within equal gain combiner at the receiver is used with two types of modulation; On–Off Keying (OOK) and L-Pulse Position Modulation, with L = 4 and 8. The perfect and imperfect successive interference cancellation scenario is used in this system, and the scenario is considered for two and three users. Our proposed framework is divided into two stages. First, data is collected using the MATLAB software. Second, two deep learning models (DLMs); ResNet50V2 and InceptionResNetV2 which are trained and tested. Python software is then used to develop and train the DLMs. The obtained results assures the superiority of ResNet50V2 over InceptionResNetV2, in different cases and for all users. The BER performance is also studied versus α for two and three users OOK modulation single-input single-output (SISO), (2 × 2) and (3 × 2) MIMO-NOMA-VLC systems based on the two DL techniques; ResNet50V2 and InceptionResNetV2. Again, ResNet50V2 achieves better results than InceptionResNetV2. The obtained results are compared with the previously published ones, showing that the proposed system and techniques achieve better results.
Funder
Arab Academy for Science, Technology & Maritime Transport
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering,Atomic and Molecular Physics, and Optics,Electronic, Optical and Magnetic Materials
Reference27 articles.
1. Ai, J., Zhang, H., Zhang, Y., Lin, K., Zhang, Y., Wu, J., Wan, Y., Huang, Y., Song, J., Fu, Z., Wang, H.: Omicron variant showed lower neutralizing sensitivity than other SARS-CoV-2 variants to immune sera elicited by vaccines after boost. Emerg. Microbes Infect. 11(1), 337–343 (2022) 2. Almohimmah, E.M., Alresheedi, M.T.: Error analysis of NOMA-based VLC systems with higher order modulation schemes. IEEE Access 8, 2792–2803 (2020) 3. Al-Nahhal M., Basar E., Uysal M.: Adaptive unipolar MIMO-OFDM for visible light communications. In: Proceedings of the 2019 European Conference on Networks and Communications (EuCNC) pp. 73–77 (2019) 4. Al-Nahhal, M., Basar, E., Uysal, M.: Flexible generalized spatial modulation for visible light communications. IEEE Trans. Veh. Technol. 70(1), 1041–1045 (2021) 5. An, Z., Zhang, T., Shen, M., De Carvalho, E., Ma, B., Yi, C., Song, T.: Series-constellation feature based blind modulation recognition for beyond 5g MIMO-OFDM systems with channel fading. IEEE Trans. Cognit. Commun. Netw. 8(2), 793–811 (2022)
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