Publications
2020 - Present
2026
- M. C. Kirana, P. Keyela, F. Rostamian, D. H. Tashman, and S. Cherkaoui, “ML-enabled open RAN: A comprehensive survey of architectures, challenges, and opportunities,” IEEE Communications Surveys & Tutorials, Early Access, 2026, doi: 10.1109/COMST.2026.3660649.
- D. H. Tashman and S. Cherkaoui, “Trustworthy AI-driven dynamic hybrid RIS: Joint optimization and reward poisoning-resilient control in cognitive MISO networks,” IEEE Transactions on Network and Service Management, Early Access, 2026, doi: 10.1109/TNSM.2026.3660728.
- M. Rahim and S. Cherkaoui, “Dual-tier IRS-assisted mid-band 6G mobile networks: Robust beamforming and user association,” arXiv preprint arXiv:2602.00431, Jan. 2026, doi: 10.48550/arXiv.2602.00431.
[🔓: arxiv ] - M. Rahim and S. Cherkaoui, “Reliable IoT communications in 6G non-terrestrial networks with dual RIS,” arXiv preprint arXiv:2602.00438, Jan. 2026, doi: 10.48550/arXiv.2602.00438.
[🔓: arxiv ] M. Sarker and S. Cherkaoui, “Priority-based bandwidth allocation in network slicing-enabled cell-free massive MIMO systems,” arXiv preprint arXiv:2601.12689, Jan. 2026.
[🔓: arxiv ]
M. Sarker and S. Cherkaoui, “Network slicing resource management in uplink user-centric cell-free massive MIMO systems,” arXiv preprint arXiv:2601.12687, Jan. 2026.
[🔓: arxiv ]
S. Abdelghani and S. Cherkaoui, “QFed: Parameter-Compact Quantum-Classical Federated Learning,” arXiv preprint arXiv:2601.09809, Jan. 2026.
[🔓: arxiv ]
Z. Yuan, Q. Li, X. Lin, T.-M. Grønl, and S. Cherkaoui, “Edge AI for Internet of Robotic Things,” IEEE Internet of Things Magazine, vol. 9, no. 1, pp. 4–6, Jan. 2026.
2025
- W. Hammami, S. Cherkaoui, J.-F. Laprade, O. Ahmad, and S. Wang, “Quantum Gated Recurrent GAN with Gaussian Uncertainty for Network Anomaly Detection,” arXiv preprint, Oct. 2025. doi: 10.48550/arXiv.2510.26487
[🔓: arXiv] W. Hamhoum, S. Cherkaoui, J.-F. Laprade, O. Ahmed, and S. Wang, “Multivariate Time Series Forecasting with Gate-Based Quantum Reservoir Computing on NISQ Hardware,” arXiv preprint arXiv:2510.13634, Oct. 2025.
[🔓: arXiv, INSPIRE-HEP]
K. M. Naguib, S. Cherkaoui, M. M. Elmessalawy, A. M. A. El-Haleem and I. I. Ibrahim, “DRL-Driven Edge-Aware Utility Optimization for Multi-Slice 6G Networks,” in IEEE Networking Letters, doi: 10.1109/LNET.2025.3614549.
[🔓: pdf ]D. H. Tashman and S. Cherkaoui, “Détection d'utilisateurs actifs assistée par la mécanique quantique pour le système CD-NOMA économe en énergie dans les réseaux de radio cognitive.,” 2025 International Wireless Communications and Mobile Computing (IWCMC), Abu Dhabi, United Arab Emirates, 2025, pp. 1661-1666, doi: 10.1109/IWCMC65282.2025.11059714.
[🔓: pdf ]W. Hammami, S. Cherkaoui and S. Wang, “Enhancing Network Anomaly Detection with Quantum GANs and Successive Data Injection for Multivariate Time Series,” 2025 International Wireless Communications and Mobile Computing (IWCMC), Abu Dhabi, United Arab Emirates, 2025, pp. 1667-1672, doi: 10.1109/IWCMC65282.2025.11059562.
[🔓: arXiv]
D. H. Tashman and S. Cherkaoui, “Dynamic Synergy: Leveraging RIS and Reinforcement Learning for Secure, Adaptive Underlay Cognitive Radio Networks,” 2025 Global Information Infrastructure and Networking Symposium (GIIS), Dubai, United Arab Emirates, 2025, pp. 1-6, doi: 10.1109/GIIS64151.2025.10921906.
[🔓: pdf ]P. Keyela and S. Cherkaoui, “Open RAN Slicing with Quantum Optimization,” 2025 Global Information Infrastructure and Networking Symposium (GIIS), Dubai, United Arab Emirates, 2025, pp. 1-6, doi: 10.1109/GIIS64151.2025.10921752.
[🔓: arXiv]
2024
B. Nour and S. Cherkaoui, “Matching-based Service Offloading for Compute-less Driven IoT Networks,” GLOBECOM 2024 – 2024 IEEE Global Communications Conference, Cape Town, South Africa, 2024, pp. 3122-3127, doi: 10.1109/GLOBECOM52923.2024.10901209.
[🔓: arXiv]
A. Vieloszynski et al., “LatentQGAN: A Hybrid QGAN with Classical Convolutional Autoencoder,” 2024 IEEE 10th World Forum on Internet of Things (WF-IoT), Ottawa, ON, Canada, 2024, pp. 1-7, doi: 10.1109/WF-IoT62078.2024.10811384.
[🔓: arXiv]A. Aaraba et al., “QuaCK-TSF: Quantum-Classical Kernelized Time Series Forecasting,” 2024 IEEE International Conference on Quantum Computing and Engineering (QCE), Montreal, QC, Canada, 2024, pp. 1628-1638, doi: 10.1109/QCE60285.2024.00190.
[🔓: arXiv]B. Kalfon, S. Cherkaoui, J.-F. Laprade, O. Ahmad, and S. Wang, “Successive data injection in conditional quantum GAN applied to time series anomaly detection,” IET Quantum Communication, vol. 5, no. 3, pp. 269–281, 2024, doi: 10.1049/qtc2.12088.
[🔓: IET, arXiv]Abouaomar, A., Filali, A., Taïk, A., & Cherkaoui, S. (2024). “Machine Learning Applications in CR-IoV“. In Bukhari, S. H. R., Rehan, M. M., & Rehmani, M. H. (eds.), Cognitive Radio-based Internet of Vehicles (pp. 21-49)
D. H. Tashman, S. Cherkaoui and W. Hamouda, “Optimizing Cognitive Networks: Reinforcement Learning Meets Energy Harvesting Over Cascaded Channels,” in IEEE Systems Journal, doi: 10.1109/JSYST.2024.3442017.
[🔓: arXiv]Y. Baseri, A. Hafid, M. D. Firoozjaei, S. Cherkaoui, and I. Ray, “Statistical privacy protection for secure data access control in cloud,” Journal of Information Security and Applications,
vol. 84, Art. no. 103823, Aug. 2024, doi: 10.1016/j.jisa.2024.103823.
[🔓: pdf]W. Hamhoum and S. Cherkaoui, "MistralBSM: Leveraging Mistral-7B for Vehicular Networks Misbehavior Detection,” arXiv preprint arXiv:2407.18462, Jul. 2024.
[🔓: arXiv]D. H. Tashman and S. Cherkaoui, “Securing Cognitive IoT Networks: Reinforcement Learning for Adaptive Physical Layer Defense,” 2024 6th International Conference on Communications, Signal Processing, and their Applications (ICCSPA), Istanbul, Turkiye, 2024, pp. 1-6, doi: 10.1109/ICCSPA61559.2024.10794361.
[🔓: pdf ]W. Hamhoum, H. Lakhdar, and S. Cherkaoui, “Fortifying Open RAN Security with Zero Trust Architecture and Transformers,“ICC 2024 – IEEE International Conference on Communications, Denver, CO, USA, 2024, pp. 2216-2221, doi: 10.1109/ICC51166.2024.10622553.
[🔓: pdf ]D. H. Tashman, S. Cherkaoui and W. Hamouda, “Federated Learning-based MARL for Strengthening Physical-Layer Security in B5G Networks,” ICC 2024 – IEEE International Conference on Communications, Denver, CO, USA, 2024, pp. 293-298, doi: 10.1109/ICC51166.2024.10622458.
[🔓: arXiv ]C. Quémenéur and S. Cherkaoui, “FedPylot: Navigating Federated Learning for Real-Time Object Detection in Internet of Vehicles,” arXiv preprint arXiv:2406.03611, Jun. 2024.
[🔓: arXiv, GitHub]D. H. Tashman and S. Cherkaoui, “Securing Next-Generation Networks against Eavesdroppers: FL-Enabled DRL Approach,” 2024 International Wireless Communications and Mobile Computing (IWCMC), Ayia Napa, Cyprus, 2024, pp. 1643-1648, doi: 10.1109/IWCMC61514.2024.10592377.
[🔓: pdf ]D. H. Tashman, S. Cherkaoui and W. Hamouda, “Maximizing Reliability in Overlay Radio Networks With Time Switching and Power Splitting Energy Harvesting,” in IEEE Transactions on Cognitive Communications and Networking, vol. 10, no. 4, pp. 1307-1316, Aug. 2024, doi: 10.1109/TCCN.2024.3375500.
[🔓: arXiv]A. Filali, Z. Mlika and S. Cherkaoui, “Open RAN Slicing for MVNOs With Deep Reinforcement Learning,” in IEEE Internet of Things Journal, vol. 11, no. 10, pp. 18711-18725, 15 May15, 2024, doi: 10.1109/JIOT.2024.3365665.
[🔓: pdf]
2023
D. H. Tashman, S. Cherkaoui, W. Hamouda and S. M. Senouci, “Securing Overlay Cognitive Radio Networks Over Cascaded Channels with Energy Harvesting,” 2023 IEEE Globecom Workshops (GC Wkshps), Kuala Lumpur, Malaysia, 2023, pp. 620-625, doi: 10.1109/GCWkshps58843.2023.10464644.
[🔓: pdf ]N. Charef, M. Abdelhafidh, A. Ben Mnaouer, K. Andersson and S. Cherkaoui, “RL-Based Adaptive Duty Cycle Scheduling in WSN-Based IoT Nets,” GLOBECOM 2023 – 2023 IEEE Global Communications Conference, Kuala Lumpur, Malaysia, 2023, pp. 3777-3782, doi: 10.1109/GLOBECOM54140.2023.10437207.
Y. Tao, J. Wu, X. Lin, S. Mumtaz and S. Cherkaoui, “Digital Twin and DRL-Driven Semantic Dissemination for 6G Autonomous Driving Service,” GLOBECOM 2023 – 2023 IEEE Global Communications Conference, Kuala Lumpur, Malaysia, 2023, pp. 2075-2080, doi: 10.1109/GLOBECOM54140.2023.10437455.
[🔓: PDF ]H. Moudoud, W. Hamhoum and S. Cherkaoui, “Strengthening Open Radio Access Networks: Advancing Safeguards Through ZTA and Deep Learning,” GLOBECOM 2023 – 2023 IEEE Global Communications Conference, Kuala Lumpur, Malaysia, 2023, pp. 80-85, doi: 10.1109/GLOBECOM54140.2023.10437829.
[ IEEE, PolyPublie ] [🔓: pdf]
H. Moudoud and S. Cherkaoui, “Enhancing Open RAN Security with Zero Trust and Machine Learning,” GLOBECOM 2023 – 2023 IEEE Global Communications Conference, Kuala Lumpur, Malaysia, 2023, pp. 2772-2777, doi: 10.1109/GLOBECOM54140.2023.10437043.
[🔓: pdf ]
A. Saadallah, P. Brunet, I. El-Korbi, S. -M. Senouci and S. Cherkaoui, “Leveraging Graph Theory for Efficient Cache Policy Design in 360∘ Video Streaming,” GLOBECOM 2023 – 2023 IEEE Global Communications Conference, Kuala Lumpur, Malaysia, 2023, pp. 976-981, doi: 10.1109/GLOBECOM54140.2023.10436720.
W. Rafique, A. S. Hafid, and S. Cherkaoui, “SoftCaching: A framework for caching node selection and routing in Software-Defined Information Centric Internet of Things,” Computer Networks, vol. 235, Art. no. 109966, Nov. 2023, doi: 10.1016/j.comnet.2023.109966.
[🔓: PDF ]S. Cherkaoui, “Quantum Leap: Exploring the Potential of Quantum Machine Learning for Communication Networks,” in Proc. Int’l ACM Conf. on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM ’23). New York, NY, USA: ACM, 2023, doi: 10.1145/3616388.3625543.
S. Mumtaz et al., “Guest Editorial Digital Twins for Mobile Networks—Part I,” in IEEE Journal on Selected Areas in Communications, vol. 41, no. 10, pp. 3001-3007, Oct. 2023, doi: 10.1109/JSAC.2023.3313016.
[🔓: IEEE PDF ]S. Mumtaz et al., “Guest Editorial Digital Twins for Mobile Networks—Part II,” in IEEE Journal on Selected Areas in Communications, vol. 41, no. 11, pp. 3349-3354, Nov. 2023, doi: 10.1109/JSAC.2023.3313017.
[🔓: IEEE PDF ]A. Taik, A. Abouaomar, and S. Cherkaoui, “Green federated learning-based models and protocols,” in Green Machine Learning Protocols for Future Communication Networks. CRC Press, 2023, pp. 63–102.
H. Moudoud, Z. Mlika, S. Cherkaoui, and L. Khoukhi, “Green machine learning for Internet-of-Things: Current solutions and future challenges,” in Green Machine Learning Protocols for Future Communication Networks. Boca Raton, FL, USA: CRC Press, 2023, pp. 161–175.
[🔓: IEEE PDF ]H. Moudoud and S. Cherkaoui, “Empowering Security and Trust in 5G and Beyond: A Deep Reinforcement Learning Approach,” in IEEE Open Journal of the Communications Society, vol. 4, pp. 2410-2420, 2023, doi: 10.1109/OJCOMS.2023.3313352.
Z. Mlika and S. Cherkaoui, J.F. Laprade, S. Corbeil Letourneau, “User trajectory prediction in mobile wireless networks using quantum reservoir computing”, IET Quantum Communication. Jan 2023, doi: 10.1049/qtc2.12061.
[🔓: IET, arXiv ]A. Allouis, A. A. Hamza, I. Dayoub and S. Cherkaoui, “Maximum Sum Rate of MCM-NOMA in Future Vehicular Sensor Networks,”in IEEE Sensors Letters, vol. 7, no. 7, pp. 1-4, July 2023, Art no. 7500504, doi: 10.1109/LSENS.2023.3288938.
[🔓: HAL UPHF]D. H. Tashman, S. Cherkaoui and W. Hamouda, "Performance Optimization of Energy-Harvesting Underlay Cognitive Radio Networks Using Reinforcement Learning,” 2023 International Wireless Communications and Mobile Computing (IWCMC), Marrakesh, Morocco, 2023, pp. 1160-1165, doi: 10.1109/IWCMC58020.2023.10182973.
[🔓: arXiv]A. Azarnoush, O. A. Dambri, E. Ü. Karatop, D. Makrakis and S. Cherkaoui, “Simulation and Performance Evaluation of a Bio-Inspired Nanogenerator for Medical Applications,” in IEEE Transactions on Biomedical Engineering, vol. 70, no. 9, pp. 2616-2623, Sept. 2023, doi: 10.1109/TBME.2023.3260200.
[🔓: PDF ]A. Filali, B. Nour, S. Cherkaoui and A. Kobbane, “Communication and Computation O-RAN Resource Slicing for URLLC Services Using Deep Reinforcement Learning,” in IEEE Communications Standards Magazine, vol. 7, no. 1, pp. 66-73, March 2023, doi: 10.1109/MCOMSTD.0002.2100078.
[🔓: arXiv ]
H. Moudoud and S. Cherkaoui, “Federated Learning Meets Blockchain to Secure the Metaverse,” 2023 International Wireless Communications and Mobile Computing (IWCMC), Marrakesh, Morocco, 2023, pp. 339-344, doi: 10.1109/IWCMC58020.2023.10182956.
A. Filali, B. Nour, S. Cherkaoui and A. Kobbane, “Communication and Computation O-RAN Resource Slicing for URLLC Services Using Deep Reinforcement Learning,” in IEEE Communications Standards Magazine, vol. 7, no. 1, pp. 66-73, March 2023, doi: 10.1109/MCOMSTD.0002.2100078.
[🔓: arXiv ]
2022
A. Abouaomar, A. Taik, A. Filali and S. Cherkaoui, “Federated Deep Reinforcement Learning for Open RAN Slicing in 6G Networks,” in IEEE Communications Magazine, vol. 61, no. 2, pp. 126-132, February 2023, doi: 10.1109/MCOM.007.2200555.
[🔓: arXiv ]R. Wang et al., “Collaborative Computation Offloading and Resource Allocation in Satellite Edge Computing,” GLOBECOM 2022 – 2022 IEEE Global Communications Conference, Rio de Janeiro, Brazil, 2022, pp. 5625-5630, doi: 10.1109/GLOBECOM48099.2022.10000770.
[ 🔓: PDF ]A. Triwinarko, S. Cherkaoui and I. Dayoub, “Performance of PHY/MAC Cross-Layer Design for Next-Generation V2X Applications,” 2022 IEEE International Conference on Internet of Things and Intelligence Systems (IoTaIS), Indonesia, 2022, pp. 98-104, doi: 10.1109/IoTaIS56727.2022.9975999.
[🔓: HAL UPHF]H. Moudoud and S. Cherkaoui, “Multi-tasking federated learning meets Blockchain to foster Trust and Security in the Metaverse,” Ad Hoc Networks, vol. 150, p. 103264, 2023, doi: 10.1016/j.adhoc.2023.103264.
[🔓: ScienceDirect]Triwinarko, A., Mlika, Z., Cherkaoui, S., & Dayoub, I. (2022, October). “Deep Reinforcement Learning to Improve Vehicle-to-Vulnerable Road User Communications in C-V2X,” 8th International Symposium on ubiquitous Networking (UNeT 2022), Montreal, Qc, Canada. https://doi.org/10.1007/978-3-031-29419-8_11.
W. Rafique, A. S. Hafid and S. Cherkaoui, “Complementing IoT Services Using Software-Defined Information Centric Networks: A Comprehensive Survey,” in IEEE Internet of Things Journal, vol. 9, no. 23, pp. 23545-23569, 1 Dec.1, 2022, doi: 10.1109/JIOT.2022.3206146.
[🔓: TechRxiv]Z. Mlika and S. Cherkaoui, “Deep Deterministic Policy Gradient to Minimize the Age of Information in Cellular V2X Communications,” in IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 12, pp. 23597-23612, Dec. 2022, doi: 10.1109/TITS.2022.3190799.
[🔓: arXiv ]B. Nour and S. Cherkaoui, “How Far Can We Go in Compute-less Networking: Computation Correctness and Accuracy,” in IEEE Network, vol. 36, no. 4, pp. 197-202, July/August 2022, doi: 10.1109/MNET.012.2100157.
[🔓: arXiv ]O. A. Dambri, S. Cherkaoui and D. Makrakis, “Design and Evaluation of a Receiver for Wired Nano-Communication Networks,” in IEEE Transactions on NanoBioscience, vol. 22, no. 2, pp. 223-236, April 2023, doi: 10.1109/TNB.2022.3182587.
[🔓: arXiv ]A. Abouaomar, S. Cherkaoui, Z. Mlika and A. Kobbane, “Service Function Chaining in MEC: A Mean-Field Game and Reinforcement Learning Approach,” in IEEE Systems Journal, vol. 16, no. 4, pp. 5357-5368, Dec. 2022, doi: 10.1109/JSYST.2022.3171232.
[🔓: arXiv ]A. Triwinarko, S. Cherkaoui and I. Dayoub, “Performance of Radio Access Technologies for Next Generation V2VRU Networks,” ICC 2022 – IEEE International Conference on Communications, Seoul, Korea, Republic of, 2022, pp. 1524-1529, doi: 10.1109/ICC45855.2022.9838580.
[🔓: pdf ]B. Nour and S. Cherkaoui, “Unsupervised Data Splitting Scheme for Federated Edge Learning in IoT Networks”, ICC 2022 – IEEE International Conference on Communications, Seoul, Korea, Republic of, 2022, pp. 1-6, doi: 10.1109/ICC45855.2022.9882289.
[🔓: arXiv ]H. Moudoud, Z. Mlika, L. Khoukhi and S. Cherkaoui, “Detection and Prediction of FDI Attacks in IoT Systems via Hidden Markov Model,” in IEEE Transactions on Network Science and Engineering, vol. 9, no. 5, pp. 2978-2990, 1 Sept.-Oct. 2022, doi: 10.1109/TNSE.2022.3161479.
[🔓: arXiv ]A. Filali, Z. Mlika, S. Cherkaoui, A. Kobbane., “Dynamic SDN-based Radio Access Network Slicing with Deep Reinforcement Learning for URLLC and eMBB Services,” IEEE Transactions on Network Science and Engineering, 2022.doi:10.1109/TNSE.2022.3157274.
[🔓: arXiv ]A. Taïk, Z. Mlika and S. Cherkaoui, “Clustered Vehicular Federated Learning: Process and Optimization,” in IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 12, pp. 25371-25383, Dec. 2022, doi: 10.1109/TITS.2022.3149860.
[🔓: arXiv ]S. Cherkaoui, “Research Landscape – 6G Networks Research in Europe,” in IEEE Network, vol. 35, no. 6, pp. 4-6, November/December 2021, doi: 10.1109/MNET.2021.9687530
A. Taïk, Z. Mlika and S. Cherkaoui, “Data-Aware Device Scheduling for Federated Edge Learning,” in IEEE Transactions on Cognitive Communications and Networking, vol. 8, no. 1, pp. 408-421, March 2022, doi: 10.1109/TCCN.2021.3100574.
[🔓: arXiv ]
2021
H. Moudoud and S. Cherkaoui, “Toward Secure and Private Federated Learning for IoT using Blockchain,” GLOBECOM 2022 – 2022 IEEE Global Communications Conference, Rio de Janeiro, Brazil, 2022, pp. 4316-4321, doi: 10.1109/GLOBECOM48099.2022.10000623.
[🔓 : arXiv ]A. Triwinarko, I. Dayoub, and S. Cherkaoui, “PHY layer enhancements for next generation V2X communication,” Vehicular Communications, vol. 32, Art. no. 100385, Dec. 2021, doi: 10.1016/j.vehcom.2021.100385.
[🔓 : ScienceDirect PDF ]B. Nour, S. Cherkaoui and Z. Mlika, “Federated Learning and Proactive Computation Reuse at the Edge of Smart Homes,” in IEEE Transactions on Network Science and Engineering, vol. 9, no. 5, pp. 3045-3056, 1 Sept.-Oct. 2022, doi: 10.1109/TNSE.2021.3131246.
O. A. Dambri and S. Cherkaoui, “Modeling Self-Assembly of Polymer-Based Wired Nano-Communication Channel,” in IEEE Transactions on Molecular, Biological and Multi-Scale Communications, vol. 8, no. 2, pp. 107-118, June 2022, doi: 10.1109/TMBMC.2021.3118943.
[🔓: arXiv ]O. A. Dambri and S. Cherkaoui, “Modeling Self-Assembly of Polymer-Based Wired Nano-Communication Channel,” in IEEE Transactions on Molecular, Biological, and Multi-Scale Communications, vol. 8, no. 2, pp. 107-118, June 2022, doi: 10.1109/TMBMC.2021.3118943.
A. Taïk, H. Moudoud and S. Cherkaoui, “Data-Quality Based Scheduling for Federated Edge Learning,” 2021 IEEE 46th Conference on Local Computer Networks (LCN), Edmonton, AB, Canada, 2021, pp. 17-23, doi: 10.1109/LCN52139.2021.9524974.
[🔓: arXiv ]
A. Abouaomar, Z. Mlika, A. Filali, S. Cherkaoui and A. Kobbane, “A Deep Reinforcement Learning Approach for Service Migration in MEC-enabled Vehicular Networks,” 2021 IEEE 46th Conference on Local Computer Networks (LCN), Edmonton, AB, Canada, 2021, pp. 273-280, doi: 10.1109/LCN52139.2021.9524882.
[🔓: arXiv ]
Z. Mlika and S. Cherkaoui, “Network slicing for vehicular communications: A multi-agent deep reinforcement learning approach,” Annals of Telecommunications, vol. 76, pp. 665–683, 2021, doi: 10.1007/s12243-021-00872-w.
[🔓: arXiv ]A. Taik, Z. Mlika, S. Cherkaoui., “Data-Aware Device Scheduling for Federated Edge Learning,” IEEE Transactions on Cognitive Communications and Networking, 2021, doi:10.1109/TCCN.2021.3100574.
[🔓: arXiv ]A. Alalewi, I. Dayoub and S. Cherkaoui, “On 5G-V2X Use Cases and Enabling Technologies: A Comprehensive Survey,” in IEEE Access, vol. 9, pp. 107710-107737, 2021, doi: 10.1109/ACCESS.2021.3100472.
[🔓: HAL UPHF]H. Moudoud, S. Cherkaoui and L. Khoukhi, “Towards a Scalable and Trustworthy Blockchain: IoT Use Case,” ICC 2021 – IEEE International Conference on Communications, Montreal, QC, Canada, 2021, pp. 1-6, doi: 10.1109/ICC42927.2021.9500535.
[🔓: arXiv ]Z. Mlika and S. Cherkaoui, “Competitive Algorithms and Reinforcement Learning for NOMA in IoT Networks,” ICC 2021 – IEEE International Conference on Communications, Montreal, QC, Canada, 2021, pp. 1-6, doi: 10.1109/ICC42927.2021.9500285.
[🔓: arXiv ]E. Vagnoni, F. Gerini, R. Cherkaoui, and M. Paolone, “Digitalization in hydropower generation: Development and numerical validation of a model-based Smart Power Plant Supervisor,” IOP Conf. Ser.: Earth Environ. Sci., vol. 774, Art. no. 012107, 2021, doi: 10.1088/1755-1315/774/1/012107.
[🔓: IOP PDF ]O. Chughtai, M. H. Rehmani, L. Musavian, S. -M. Senouci, S. Cherkaoui and S. Mao, “IEEE Access Special Section Editorial: Flying Ad Hoc Networks: Challenges, Potentials, Future Applications, and Way Forward,” in IEEE Access, vol. 9, pp. 74189-74193, 2021, doi: 10.1109/ACCESS.2021.3077816.
[🔓: MDPI ]H. Moudoud, S. Cherkaoui, and L. Khoukhi, “An overview of blockchain and 5G networks,” in Computational Intelligence in Recent Communication Networks (EAI/Springer Innovations in Communication and Computing), M. Ouaissa, Z. Boulouard, M. Ouaissa, and B. Guermah, Eds. Cham, Switzerland: Springer, 2022, doi: 10.1007/978-3-030-77185-0_1.
[🔓: arXiv ]Z. Mlika and S. Cherkaoui, “Massive IoT Access With NOMA in 5G Networks and Beyond Using Online Competitiveness and Learning,” in IEEE Internet of Things Journal, vol. 8, no. 17, pp. 13624-13639, 1 Sept.1, 2021, doi: 10.1109/JIOT.2021.3068061.
[🔓: arXiv ]M. Lakoju, A. Javed, O. Rana, et al., “‘Chatty Devices’ and edge-based activity classification,” Discover Internet of Things, vol. 1, Art. no. 5, Feb. 2021, doi: 10.1007/s43926-021-00004-9.
[🔓: Springer]A. Abouaomar, S. Cherkaoui, Z. Mlika and A. Kobbane, “Resource Provisioning in Edge Computing for Latency-Sensitive Applications,” in IEEE Internet of Things Journal, vol. 8, no. 14, pp. 11088-11099, 15 July15, 2021, doi: 10.1109/JIOT.2021.3052082.
[ 🔓: arXiv ]Z. Mlika and S. Cherkaoui, “Network Slicing with MEC and Deep Reinforcement Learning for the Internet of Vehicles,” in IEEE Network, vol. 35, no. 3, pp. 132-138, May/June 2021, doi: 10.1109/MNET.011.2000591.
[ 🔓: arXiv ]M. Lakoju, A. Javed, O. Rana, P. Burnap, S. T. Atiba, and S. Cherkaoui, “‘Chatty Devices’ and edge-based activity classification,” Discover Internet of Things, vol. 1, Art. no. 5, Feb. 2021, doi: 10.1007/s43926-021-00004-9.
[🔓: cardiffmet.ac.uk pdf]Z. Mlika and S. Cherkaoui, “Network Slicing with MEC and Deep Reinforcement Learning for the Internet of Vehicles,” in IEEE Network, vol. 35, no. 3, pp. 132-138, May/June 2021, doi: 10.1109/MNET.011.2000591.
[🔓: arXiv ]A. Taik, B. Nour and S. Cherkaoui, “Empowering Prosumer Communities in Smart Grid with Wireless Communications and Federated Edge Learning,” in IEEE Wireless Communications, vol. 28, no. 6, pp. 26-33, December 2021, doi: 10.1109/MWC.017.2100187.
[🔓: arXiv ]
2020
- A. Filali, Z. Mlika, S. Cherkaoui and A. Kobbane, “Preemptive SDN Load Balancing With Machine Learning for Delay Sensitive Applications,” in IEEE Transactions on Vehicular Technology, vol. 69, no. 12, pp. 15947-15963, Dec. 2020, doi: 10.1109/TVT.2020.3038918.
- H. Moudoud, L. Khoukhi and S. Cherkaoui, “Prediction and Detection of FDIA and DDoS Attacks in 5G Enabled IoT,” in IEEE Network, vol. 35, no. 2, pp. 194-201, March/April 2021, doi: 10.1109/MNET.011.2000449.
[🔓: pdf] - J. Rezgui, É. Gagné, G. Blain, M. Harvey, O. St-Pierre and S. Cherkaoui, “Open Source Platform for Extended Perception Using Communications and Machine Learning on a Small-Scale Vehicular Testbed,” 2020 Global Information Infrastructure and Networking Symposium (GIIS), Tunis, Tunisia, 2020, pp. 1-4, doi: 10.1109/GIIS50753.2020.9248485.
[🔓: pdf] - A. Filali, A. Abouaomar, S. Cherkaoui, A. Kobbane and M. Guizani, “Multi-Access Edge Computing: A Survey,” in IEEE Access, vol. 8, pp. 197017-197046, 2020, doi: 10.1109/ACCESS.2020.3034136.
[🔓: IEEE PDF] - A. Tak and S. Cherkaoui, “Federated Edge Learning: Design Issues and Challenges,” in IEEE Network, vol. 35, no. 2, pp. 252-258, March/April 2021, doi: 10.1109/MNET.011.2000478.
[🔓: arXiv ] - J. H. Yi, R. Cherkaoui and M. Paolone, “Optimal Allocation of ESSs in Active Distribution Networks to Achieve Their Dispatchability,” in IEEE Transactions on Power Systems, vol. 36, no. 3, pp. 2068-2081, May 2021, doi: 10.1109/TPWRS.2020.3025991.
[🔓: arXiv ] - A. Taïk and S. Cherkaoui, “Electrical Load Forecasting Using Edge Computing and Federated Learning,” ICC 2020 – 2020 IEEE International Conference on Communications (ICC), Dublin, Ireland, 2020, pp. 1-6, doi: 10.1109/ICC40277.2020.9148937.
[🔓: arXiv ] - O. A. Dambri and S. Cherkaoui, “A physical channel model for wired nano-communication networks,” arXiv preprint arXiv:2005.12328, May 2020, doi: 10.48550/arXiv.2005.12328.
[🔓: arXiv ] - O. A. Dambri and S. Cherkaoui, “Toward a Wired Ad Hoc Nanonetwork,” ICC 2020 – 2020 IEEE International Conference on Communications (ICC), Dublin, Ireland, 2020, pp. 1-6, doi: 10.1109/ICC40277.2020.9148728.
[🔓: arXiv ]