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Modeling an Enhanced Modulation Classification Approach using Arithmetic Optimization with Deep Learning for MIMO-OFDM Systems


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Venkatramanan, M., Chinnadurai, M. (2024). Channel estimation in MIMO TFT-OFDM using hybrid BESOA-CSOA algorithms. Technical Gazette, 31 (1), 151-155. https://doi.org/10.17559/TV-20230502000598 Search in Google Scholar

He, H., Jin, S., Wen, C.-K., Gao, F., Li, G. Y., Xu, Z. (2019). Model-driven deep learning for physical layer communications. IEEE Wireless Communications, 26 (5), 77-83. https://doi.org/10.1109/MWC.2019.1800447 Search in Google Scholar

Qin, Z., Ye, H., Li, G. Y., Juang, B.-H. F. (2019). Deep learning in physical layer communications. IEEE Wireless Communications, 26 (2), 93-99. https://doi.org/10.1109/MWC.2019.1800601 Search in Google Scholar

Al-Rayif, M. I. (2021). PAPR reduction method based on in-phase/quadrature data symbol components in MIMO-OFDM systems. Journal of Communications Software and Systems, 17 (4), 326-333. https://doi.org/10.24138/jcomss-2021-0123 Search in Google Scholar

Jayamathi, A., Jayasankar, T., Vinoth Kumar, K. (2022). Novel selective mapping with oppositional hosted cuckoo optimization algorithm for PAPR reduction in 5G UFMC systems. Technical Gazette, 29 (2), 464-471. https://doi.org/10.17559/TV-20210524085655 Search in Google Scholar

Kavitha, G., Deny, J. (2023). Single and multi-point non-orthogonal multiple access based power adaptive design for improving bit error ratio. Measurement Science Review, 23 (4), 184-191. https://doi.org/10.2478/msr-2023-0024 Search in Google Scholar

Wang, T., Wen, C.-K., Jin, S., Li, G. Y. (2019). Deep learning-based CSI feedback approach for time-varying massive MIMO channels. IEEE Wireless Communications Letters, 8 (2), 416-419. https://doi.org/10.1109/LWC.2018.2874264 Search in Google Scholar

Vijay Anand, J., Manoharan, P. S., Jeyadheep Vignesh, J., Varatharajan, M., Rubina Sherin, M. (2021). Spider search algorithms for MIMO system and assessment using simatic PCS7. Technical Gazette, 28 (4), 1118-1126. https://doi.org/10.17559/TV-20200513113443 Search in Google Scholar

Yang, Y., Gao, F., Ma, X., Zhang, S. (2019). Deep learning-based channel estimation for doubly selective fading channels. IEEE Access, 7, 36579-89. https://doi.org/10.1109/ACCESS.2019.2901066 Search in Google Scholar

Soltani, M., Pourahmadi, V., Mirzaei, A., Sheikhzadeh, H. (2019). Deep learning-based channel estimation. IEEE Communications Letters, 23 (4), 652-655. https://doi.org/10.1109/LCOMM.2019.2898944 Search in Google Scholar

Han, S., Oh, Y., Song, C. (2019). A deep learning based channel estimation scheme for IEEE 802.11p systems. In IEEE International Conference on Communications (ICC 2019). IEEE. https://doi.org/10.1109/ICC.2019.8761354 Search in Google Scholar

Liao, Y., Hua, Y., Dai, X., Yao, H., Yang, X. (2019). ChanEstNet: A deep learning based channel estimation for high-speed scenarios. In IEEE International Conference on Communications (ICC 2019). IEEE. https://doi.org/10.1109/ICC.2019.8761312 Search in Google Scholar

Jiang, R., Wang, X., Cao, S., Zhao, J., Li, X. (2019). Deep neural networks for channel estimation in underwater acoustic OFDM systems. IEEE Access, 7, 23579-23594. https://doi.org/10.1109/ACCESS.2019.2899990 Search in Google Scholar

Alshahrani, E., Alghazzawi, D., Alotaibi, R., Rabie, O. (2022). Adversarial attacks against supervised machine learning based network intrusion detection systems. PLoS One, 17 (10), e0275971. https://doi.org/10.1371/journal.pone.0275971 Search in Google Scholar

Wang, M., Wang, A., Liu, Z., Chai, J. (2023). Deep learning based channel estimation method for mine OFDM system. Scientific Reports, 13 (1), 17105. https://doi.org/10.1038/s41598-023-43971-5 Search in Google Scholar

Melacci, S., Ciravegna, G., Sotgiu, A., Demontis, A., Biggio, B., Gori, M., Roli, F. (2022). Domain knowledge alleviates adversarial attacks in multi-label classifiers. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44 (12), 9944-9959. https://doi.org/10.1109/TPAMI.2021.3137564 Search in Google Scholar

Lal, S., Rehman, S. U., Shah, J. H., Meraj, T., Rauf, H. T., Damaševičius, R., Mohammed, M. A., Abdulkareem, K. H. (2021). Adversarial attack and defence through adversarial training and feature fusion for diabetic retinopathy recognition. Sensors, 21 (11), 3922. https://doi.org/10.3390/s21113922 Search in Google Scholar

Elnakeeb, A., Mitra, U. (2021). Bilinear channel estimation for MIMO OFDM: Lower bounds and training sequence optimization. IEEE Transactions on Signal Processing, 69, 1317-1331. https://doi.org/10.1109/TSP.2021.3056591 Search in Google Scholar

Soares, J. A., Mayer, K. S., de Castro, F. C. C., Arantes, D. S. (2021). Complex-valued phase transmittance RBF neural networks for massive MIMO-OFDM receivers. Sensors, 21 (24), 8200. https://doi.org/10.3390/s21248200 Search in Google Scholar

Ali, K. S., Khan, A. A., T, P., Ur Rehman, A., Ouahada, K. (2023). Learned-SBL-GAMP based hybrid precoders/combiners in millimeter wave massive MIMO systems. PLoS One, 18 (9), e0289868 https://doi.org/10.1371/journal.pone.0289868 Search in Google Scholar

Naqvi, S. H. R., Ho, P. H., Peng, L. (2021). 5G NR mmWave indoor coverage with massive antenna system. Journal of Communications and Networks, 23 (1), 1-11. https://doi.org/10.23919/JCN.2020.000031 Search in Google Scholar

eISSN:
1335-8871
Language:
English
Publication timeframe:
6 times per year
Journal Subjects:
Engineering, Electrical Engineering, Control Engineering, Metrology and Testing