Our research addresses pilot contamination in Massive MIMO systems to improve signal-to-noise ratio (SNR) and overall system performance. By employing advanced optimization techniques and machine learning models, we developed methods to enhance channel estimation accuracy, thereby mitigating interference and boosting SNR. These enhancements are crucial for achieving higher spectral efficiency and reliability in dense network environments, laying a solid foundation for next-generation wireless communication systems such as 5G and 6G.
Publications:
- M. Selim, A. Nazar, S. Ahmed, and A. Kamal, “Adaptive Deployment of Reconfigurable Intelligent Surfaces on Tethered and Untethered UAVs” 2024 Book Chapter in Springer Nature (accepted)
- M. Saeed, A. Khokhar, and S. Ahmed, “Deep Learning-Driven Cascaded Channel Estimation in RIS-Aided mm-Wave Massive MIMO Systems” (submitted to 2025 IEEE International Conference on Communications).
- K. Saeed, A. Khokhar, and S. Ahmed, “Pilot Contamination in Massive MIMO Systems: Challenges and Future Prospects,” 2024 International Wireless Communications and Mobile Computing (IWCMC), Ayia Napa, Cyprus, 2024, pp. 1504-1509.
- S. Ahmed and A. Kamal, “Sky’s the limit: Navigating 6G with SATAR RIS for UAVs optimal path planning,” 2023 28th IEEE Symposium on Computers and Communications (ISCC), Tunisia.
- S. Ahmed, I. Abdelmawla, A. Kamal, and M. Selim, “Blockage Prediction for mobile UE in RIS-assisted wireless networks: A deep learning approach,” in Proc. 39th IEEE MILCOM, Maryland, pp. 705-710, 2022.
- H. Sun, Q. Wang, S. Ahmed, and R. Q. Hu, “Non-orthogonal multiple access in a mmWave based IoT wireless system with SWIPT,” in Proc. 85th IEEE International Conference on VTC, Sydney, NSW, Australia, pp. 4-7, November 2017 (Invited paper).
- M. Alam, M. Rahman, S. Ahmed, M. Chowdhury, “Adaptive biasing cell association in FFR aided multi-tier heterogeneous networks under dynamic load variation,” in Proc. 5th IEEE International Conference on Informatics, Electronics, and Vision (ICIEV), May 2016, pp. 829-833 (Best paper award).
- S. Arnab, S. Alam, T. Mahmud, S. Sabuj, and S. Ahmed. “Deep Convolutional Generative Adversarial Networks: Performance Analysis in Wireless Systems,” Discover Internet of Things, Springer (accepted), 2024.
- S. Karobi, S. Ahmed, S. Sabuj, and A. Khokhar. “EcoEdgeTwin: Enhanced 6G Network via Mobile Edge Computing and Digital Twin Integration,” submitted to 2024 IET Digital Twins and Applications.
- M. Chowdhury, and S. Ahmed, “A New Conditional Generative Adversarial Network for Massive MIMO Channel Estimation,” submitted to 2024 Arabian Journal for Science and Engineering (AJSE).
- S. Ahmed, A. Kamal, and M. Selim. “Optimal Microcontroller Usage in Reconfigurable Intelligent Surface: A Batteryless IoT Systems Case Study,” submitted to 2024 Computer Networks.
- S. Ahmed, A. Kamal, M. Selim, and A. Khokhar. “Optimizing Small Cell Performance: A new MIMO paradigm with distributed ASTAR-RISs,” 2024 IEEE Open Journal of Vehicular Technology (accepted)
- S. Sabuj, S. Ahmed, and A. Khokhar. “Spectrum Scarcity in Vehicular Networks in 6G: Architecture, Challenges and Solutions,” in preparation for IEEE Vehicular Technology Magazine.
- S. Sabuj, S. Ahmed, and H. Jo. “Multiple CUAV-enabled mMTC and URLLC services: Review of energy efficiency and latency performance,” IEEE Transactions on Green Communications and Networking, vol. 7, no. 3, pp. 1369-1382, Sept. 2023.
- S. Ahmed, M.Z. Chowdhury, S. Sabuj, Y. Jang, and I. Alam. “Energy-efficient UAV relaying robust resource allocation in uncertain adversarial networks,” IEEE Access, vol. 9, pp. 59920-59934, 2021.
- M. Chowdhury, M. Shahjalal, S. Ahmed, Y. Jang. “6G wireless communication: Applications, requirements, technologies, and research directions,” IEEE Open Journal of the Communications Society, vol. 1, pp. 957-975, July 2020.