Home / Current Issue / Paper 1707329
Enhancing Satellite Internet with Generative AI-Driven Predictive Beamforming
Subject area: Science,Engineering and Technology · Area of research: Artificial Intelligence
Abstract
The integration of Generative Artificial Intelligence (AI) in satellite-based internet services presents a transformative approach to optimizing predictive beamforming for enhanced connectivity and efficiency. Traditional beamforming techniques rely on deterministic models and historical data, often struggling to adapt to dynamic environmental conditions, network congestion, and user mobility. This paper explores the potential of generative AI models, such as variational autoencoders (VAEs), generative adversarial networks (GANs), and transformer-based architectures, to predict optimal beam configurations in real time. By leveraging vast amounts of satellite telemetry, weather patterns, and user traffic data, generative AI can synthesize realistic future network states, mitigate latency, and improve signal coverage. We discuss the architectural considerations, training methodologies, and deployment challenges associated with AI-driven beamforming. Furthermore, we evaluate performance metrics, including beam alignment accuracy, spectral efficiency, and adaptability to disruptions, comparing AI-enhanced approaches with conventional predictive models. The findings suggest that generative AI can significantly enhance satellite internet services by improving coverage, reducing handover failures, and optimizing power allocation, paving the way for next-generation, AI-native satellite communication systems.
Keywords
Generative AI, Predictive Beamforming, Satellite Internet, AI-Driven Beam Steering, and Dynamic Beam Allocation.
References
[1] Khan, S., Alghayadh, F.Y., Ahanger, T.A. et al. Deep learning model for efficient traffic forecasting in intelligent transportation systems. Neural Comput & Applic (2024). https://doi.org/10.1007/s00521-024-10537-z
[2] M. Azrour, J. Mabrouki, A. Guezzaz, S. Ahmad, S. Khan, and S. Benkirane, "IoT, Machine Learning and Data Analytics for Smart Healthcare," ed: CRC Press, 2024.
[3] M. S. Rao, S. Modi, R. Singh, K. L. Prasanna, S. Khan, and C. Ushapriya, "Integration of Cloud Computing, IoT, and Big Data for the Development of a Novel Smart Agriculture Model," in 2023 3rd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), 2023, pp. 2779-2783: IEEE.
[4] S. Khan et al., "Manufacturing industry based on dynamic soft sensors in integrated with feature representation and classification using fuzzy logic and deep learning architecture," The International Journal of Advanced Manufacturing Technology, vol. 128, pp. 2885–2897, 2023.
[5] S. Khan, G. K. Moorthy, T. Vijayaraj, L. H. Alzubaidi, A. Barno, and V. Vijayan, "Computational Intelligence for Solving Complex Optimization Problems," in E3S Web of Conferences, 2023, vol. 399, p. 04038: EDP Sciences.
[6] S. Khan et al., "Transformer Architecture-Based Transfer Learning for Politeness Prediction in Conversation," Sustainability, vol. 15, no. 14, p. 10828, 2023.
[7] S. Khan, V. Ch, K. Sekaran, K. Joshi, C. K. Roy, and M. Tiwari, "Incorporating Deep Learning Methodologies into the Creation of Healthcare Systems," in 2023 International Conference on Artificial Intelligence and Smart Communication (AISC), 2023, pp. 994-998: IEEE.
[8] S. Khan and S. Alqahtani, "Hybrid machine learning models to detect signs of depression," Multimedia Tools and Applications, pp. 1-19, 2023.
[9] I. Keshta et al., "Energy efficient indoor localisation for narrowband internet of things," CAAI Transactions on Intelligence Technology, 2023.
[10] M. J. Antony, B. P. Sankaralingam, S. Khan, A. Almjally, N. A. Almujally, and R. K. Mahendran, "Brain–Computer Interface: The HOL–SSA Decomposition and Two-Phase Classification on the HGD EEG Data," Diagnostics, vol. 13, no. 17, p. 2852, 2023.
[11] Eldosoky, Mahmoud A., Jian Ping Li, Amin Ul Haq, Fanyu Zeng, Mao Xu, Shakir Khan, and Inayat Khan. "WallNet: Hierarchical Visual Attention-Based Model for Putty Bulge Terminal Points Detection." The Visual Computer (2024): 1-16.
[12] S. Khan, "Study Factors for Student Performance Applying Data Mining Regression Model Approach," International Journal of Computer Science Network Security, vol. 21, no. 2, pp. 188-192, 2021.
[13] S. Khan and M. Alshara, "Development of Arabic evaluations in information retrieval," International Journal of Advanced Applied Sciences, vol. 6, no. 12, pp. 92-98, 2019.
[14] S. Khan and M. Alshara, "Fuzzy Data Mining Utilization to Classify Kids with Autism," International Journal of Computer Science Network Security, vol. 19, no. 2, pp. 147-154, 2019.
[15] S. Khan and M. F. AlAjmi, "A Review on Security Concerns in Cloud Computing and their Solutions," International Journal of Computer Science Network Security, vol. 19, no. 2, p. 10, 2019.
[16] S. Khan, A. S. Al-Mogren, and M. F. AlAjmi, "Using cloud computing to improve network operations and management," presented at the 5th National Symposium on Information Technology: Towards New Smart World (NSITNSW), 2015.
[17] M. F. AlAjmi, S. Khan, and A. Sharma, "Collaborative learning outline for mobile environment," in 2014 International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT), 2014, pp. 429-434: IEEE.
[18] Saif, Sohail, et al. "A secure data transmission framework for IoT enabled healthcare." Heliyon 10.16 (2024).
[19] Jian, Wang, et al. "Feature elimination and stacking framework for accurate heart disease detection in IoT healthcare systems using clinical data." Frontiers in Medicine 11 (2024): 1362397.
[20] Sreekumar, Das, S., Debata, B.R., Gopalan, R., Khan, S. (2024). Diabetes Prediction: A Comparison Between Generalized Linear Model and Machine Learning. In: Acharjya, D.P., Ma, K. (eds) Computational Intelligence in Healthcare Informatics. Studies in Computational Intelligence, vol 1132. Springer, Singapore. https://doi.org/10.1007/978-981-99-8853-2_4
[21] Khan, S., Serajuddin, M., Hasan, Z., Alvi, S.A.M., Ayub, R., Sharma, A. (2025). Natural Language Generation (NLG) with Reinforcement Learning (RL). In: Dev, A., Sharma, A., Agrawal, S.S., Rani, R. (eds) Artificial Intelligence and Speech Technology. AIST 2023. Communications in Computer and Information Science, vol 2268. Springer, Cham. https://doi.org/10.1007/978-3-031-75167-7_25
[22] S. Khan, P. Sharma, K. R. Prasad, S. D, M. Serajuddin and R. Ayub, "The Implementation of Machine Learning in the Development of Sustainable Supply Chains," 2023 10th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON), Gautam Buddha Nagar, India, 2023, pp. 292-296, doi: 10.1109/UPCON59197.2023.10434528.
[23] Khan, S., Khari, M. & Azrour, M. IoT in retail and e-commerce. Electron Commer Res (2023). https://doi.org/10.1007/s10660-023-09785-3
[24] Halder, P., Hassan, M.M., Rahman, A.K.Z.R., Akter, L., Ahmed, A.S., Khan, S., Chatterjee, S., Raihan, M.: Prospects and setbacks for migrating towards 5G wireless access in developing Bangladesh: A comparative study. J. Eng. 2023, e12319 (2023). https://doi.org/10.1049/tje2.12319
[25] Alotaibi, Reemiah Muneer, and Shakir Khan. "Big Data and Predictive Data Analytics in the Smes Industry Using Machine Learning Approach." 2023 6th International Conference on Contemporary Computing and Informatics (IC3I). Vol. 6. IEEE, 2023.
[26] Alfaifi, Asma Abdulsalam, and Shakir Gayour Khan. "Utilizing data from Twitter to explore the UX of “Madrasati” as a Saudi e-learning platform compelled by the pandemic." Arab Gulf Journal of Scientific Research 39.3 (2021).
[27] Xiang Li, Wang Zhou, Amin Ul Haq, Shakir Khan, LDPMF: Local differential privacy enhanced matrix factorization for advanced recommendation, Knowledge-Based Systems, Volume 309, 2025, 112892, ISSN 0950-7051, https://doi.org/10.1016/j.knosys.2024.112892.
[28] Jian, Wang, et al. "SA-Bi-LSTM: Self Attention With Bi-Directional LSTM based Intelligent Model for Accurate Fake News Detection to ensured information integrity on social media platforms." IEEE Access (2024).
[29] Sharma, Chirag, et al. "Lightweight Security for IoT." Journal of Intelligent & Fuzzy Systems Preprint (2023): 1-17.
[30] Akram, Abeeda, et al. "On Layout Optimization of Wireless Sensor Network Using Meta-Heuristic Approach." Comput. Syst. Sci. Eng. 46.3 (2023): 3685-3701.
[31] Shakir, Khan, and Alotaibi Reemiah Muneer. "A novel thresholding for prediction analytics with machine learning techniques." International Journal of Computer Science & Network Security 23.1 (2023): 33-40.
[32] Tayyab, Moeen, et al. "Recognition of Visual Arabic Scripting News Ticker From Broadcast Stream." IEEE Access 10 (2022): 59189-59204.
[33] Khan, Shakir. "Business Intelligence Aspect for Emotions and Sentiments Analysis." 2022 First International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT). IEEE, 2022.
[34] AlSuwaidan, Lulwah, et al. "Swarm Intelligence Algorithms for Optimal Scheduling for Cloud‐Based Fuzzy Systems." Mathematical Problems in Engineering 2022.1 (2022): 4255835.
[35] Sultan Ahmad, Sudan Jha, Abubaker E. M. Eljialy and Shakir Khan, “A Systematic Review on e-Wastage Frameworks” International Journal of Advanced Computer Science and Applications(IJACSA), 12(12), 2021. http://dx.doi.org/10.14569/IJACSA.2021.0121287
[36] Khan, Shakir, and Mohammed Ali Alshara. "Adopting Open Source Software for Integrated Library System and Digital Library Automation." International Journal of Computer Science and Network Security 20.9 (2020): 158-165.
[37] Khan, Shakir, and Amani Alfaifi. "Modeling of coronavirus behavior to predict it’s spread." International Journal of Advanced Computer Science and Applications 11.5 (2020): 394-399.
[38] Khan, Shakir. "Modern Internet of Things as a challenge for higher education." International Journal of Computer Science and Network Security 18.12 (2018): 34-41.
[39] Khan, Shakir, and M. Alajmi. "The Role Of Open Source Technology In Development Of E-Learning Education." Edulearn17 Proceedings. IATED, 2017.
[40] AlAjmi, M., and Shakir Khan. "Part of Ajax And Openajax In Cutting Edge Rich Application Advancement For E-Learning." INTED2015 Proceedings. IATED, 2015.
[41] Sattar, Kamran, et al. "Social networking in medical schools: Medical student’s viewpoint." Biomed Res 27.4 (2016): 1378-84.
[42] AlAjmi, Mohamed F., Shakir Khan, and Abdulkadir Alaydarous. "Data Protection Control and Learning Conducted Via Electronic Media IE Internet." International Journal of Advanced Computer Science and Applications 5.11 (2014).
[43] Khan, Shakir, et al. "Keeping Data on Clouds: Cloud Computing Significance." International Journal of Engineering & Science Research 3.2 (2013): 2321-2327.
[44] AlAjmi, Mohammed, and Shakir Khan. "Data Mining–Based, Service Oriented Architecture (SOA) In E-Learning." Iceri2012 Proceedings. IATED, 2012.
[45] AlAjmi, M., and Shakir Khan. "The Utility of New Technologies in Enhancing Learning Vigilance in Educationally Poor Populations." EDULEARN12 Proceedings. IATED, 2012.
[46] AlAjmi, Mohamed F., and Shakir Khan. "Effective Use of Web 2.0 Tools Complex Pharmatical Skills Teaching And Learning." ICERI2011, 3rd International Conference on Education and New Learning Technologies, Spain. 2011.
[47] Alajmi, M., and S. Khan. "EFFECTIVE USE OF WEB 2.0 TOOLS IN PHARMACY STUDENTS'CLINICAL SKILLS PRACTICE DURING FIELD TRAINING." iceri2011 proceedings. IATED, 2011.
[48] Khan, Shakir, Mohammed AlAjmi, and Arun Sharma. "Safety Measures Investigation in Moodle LMS." Special Issue of International Journal of Computer Applications (2012).
[49] Khan, Shakir, and Arun Sharma. "Moodle Based LMS and Open Source Software (OSS) Efficiency in E-Learning." International Journal of Computer Science & Engineering Technology 3.4 (2012): 50-60.
[50] AlAjmi, Mohamed F., Arun Sharma Head, and Shakir Khan. "Growing cloud computing efficiency." International Journal of Advanced Computer Science and Applications (IJACSA) 3.5 (2012).
[51] AlAjmi, Mohamed F., Shakir Khan, and Arun Sharma. "Studying data mining and data warehousing with different e-learning system." International Journal of Advanced Computer Science and Applications 4.1 (2013).
[52] Xiang Li, Wang Zhou, Amin Ul Haq, Shakir Khan, LDPMF: Local differential privacy enhanced matrix factorization for advanced recommendation, Knowledge-Based Systems, Volume 309, 2025, 112892, ISSN 0950-7051, https://doi.org/10.1016/j.knosys.2024.112892.
[53] Khan, S., Alghayadh, F.Y., Ahanger, T.A. et al. Deep learning model for efficient traffic forecasting in intelligent transportation systems. Neural Comput & Applic (2024). https://doi.org/10.1007/s00521-024-10537-z
[54] Saif, Sohail, et al. "A secure data transmission framework for IoT enabled healthcare." Heliyon 10.16 (2024).
[55] Veluri, Rahul Chiranjeevi, et al. "Modified M‐RCNN approach for abandoned object detection in public places." Expert Systems 42.2 (2025): e13648.
[56] Jian, Wang, et al. "Feature elimination and stacking framework for accurate heart disease detection in IoT healthcare systems using clinical data." Frontiers in Medicine 11 (2024): 1362397.
[57] Jian, Wang, et al. "SA-Bi-LSTM: Self Attention With Bi-Directional LSTM based Intelligent Model for Accurate Fake News Detection to ensured information integrity on social media platforms." IEEE Access (2024).
[58] S. Khan and S. Alqahtani, "Hybrid machine learning models to detect signs of depression," Multimedia Tools and Applications, pp. 1-19, 2023.
[59] Eldosoky, Mahmoud A., Jian Ping Li, Amin Ul Haq, Fanyu Zeng, Mao Xu, Shakir Khan, and Inayat Khan. "WallNet: Hierarchical Visual Attention-Based Model for Putty Bulge Terminal Points Detection." The Visual Computer (2024): 1-16.
[60] Saboor, Abdus, et al. "DDFC: deep learning approach for deep feature extraction and classification of brain tumors using magnetic resonance imaging in E-healthcare system." Scientific Reports 14.1 (2024): 6425.
[61] M. Azrour, J. Mabrouki, A. Guezzaz, S. Ahmad, S. Khan, and S. Benkirane, "IoT, Machine Learning and Data Analytics for Smart Healthcare," ed: CRC Press, 2024.
[62] Sreekumar, Das, S., Debata, B.R., Gopalan, R., Khan, S. (2024). Diabetes Prediction: A Comparison Between Generalized Linear Model and Machine Learning. In: Acharjya, D.P., Ma, K. (eds) Computational Intelligence in Healthcare Informatics. Studies in Computational Intelligence, vol 1132. Springer, Singapore. https://doi.org/10.1007/978-981-99-8853-2_4
[63] Khan, S., Serajuddin, M., Hasan, Z., Alvi, S.A.M., Ayub, R., Sharma, A. (2025). Natural Language Generation (NLG) with Reinforcement Learning (RL). In: Dev, A., Sharma, A., Agrawal, S.S., Rani, R. (eds) Artificial Intelligence and Speech Technology. AIST 2023. Communications in Computer and Information Science, vol 2268. Springer, Cham. https://doi.org/10.1007/978-3-031-75167-7_25
[64] I. Keshta et al., "Energy efficient indoor localisation for narrowband internet of things," CAAI Transactions on Intelligence Technology, 2023.
[65] Khan, S., Khari, M. & Azrour, M. IoT in retail and e-commerce. Electron Commer Res (2023). https://doi.org/10.1007/s10660-023-09785-3
[66] Halder, P., Hassan, M.M., Rahman, A.K.Z.R., Akter, L., Ahmed, A.S., Khan, S., Chatterjee, S., Raihan, M.: Prospects and setbacks for migrating towards 5G wireless access in developing Bangladesh: A comparative study. J. Eng. 2023, e12319 (2023). https://doi.org/10.1049/tje2.12319
[67] S. Khan et al., "Manufacturing industry based on dynamic soft sensors in integrated with feature representation and classification using fuzzy logic and deep learning architecture," The International Journal of Advanced Manufacturing Technology, vol. 128, pp. 2885–2897, 2023.
[68] Alotaibi, Reemiah Muneer, and Shakir Khan. "Big Data and Predictive Data Analytics in the Smes Industry Using Machine Learning Approach." 2023 6th International Conference on Contemporary Computing and Informatics (IC3I). Vol. 6. IEEE, 2023.
[69] M. J. Antony, B. P. Sankaralingam, S. Khan, A. Almjally, N. A. Almujally, and R. K. Mahendran, "Brain–Computer Interface: The HOL–SSA Decomposition and Two-Phase Classification on the HGD EEG Data," Diagnostics, vol. 13, no. 17, p. 2852, 2023.
[70] Yousef, Rammah, et al. "Bridged-U-Net-ASPP-EVO and deep learning optimization for brain tumor segmentation." Diagnostics 13.16 (2023): 2633.
[71] Saurabh, et al. ‘Lightweight Security for IoT’. 1 Jan. 2023: 5423 – 5439.
[72] Khan, Shakir, et al. "Transformer Architecture-Based Transfer Learning for Politeness Prediction in Conversation." Sustainability 15.14 (2023): 10828.
[73] M. S. Rao, S. Modi, R. Singh, K. L. Prasanna, S. Khan, and C. Ushapriya, "Integration of Cloud Computing, IoT, and Big Data for the Development of a Novel Smart Agriculture Model," in 2023 3rd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), 2023, pp. 2779-2783: IEEE.
[74] Akram, Abeeda, et al. "On Layout Optimization of Wireless Sensor Network Using Meta-Heuristic Approach." Comput. Syst. Sci. Eng. 46.3 (2023): 3685-3701.
[75] S. Khan, V. Ch, K. Sekaran, K. Joshi, C. K. Roy, and M. Tiwari, "Incorporating Deep Learning Methodologies into the Creation of Healthcare Systems," in 2023 International Conference on Artificial Intelligence and Smart Communication (AISC), 2023, pp. 994-998: IEEE.
[76] S. Khan, G. K. Moorthy, T. Vijayaraj, L. H. Alzubaidi, A. Barno, and V. Vijayan, "Computational Intelligence for Solving Complex Optimization Problems," in E3S Web of Conferences, 2023, vol. 399, p. 04038: EDP Sciences.
[77] Shakir, Khan, and Alotaibi Reemiah Muneer. "A novel thresholding for prediction analytics with machine learning techniques." International Journal of Computer Science & Network Security 23.1 (2023): 33-40.
[78] Alfaifi, Asma Abdulsalam, and Shakir Gayour Khan. "Utilizing data from Twitter to explore the UX of “Madrasati” as a Saudi e-learning platform compelled by the pandemic." Arab Gulf Journal of Scientific Research 39.3 (2021).
[79] AlSuwaidan, Lulwah, et al. "Swarm Intelligence Algorithms for Optimal Scheduling for Cloud‐Based Fuzzy Systems." Mathematical Problems in Engineering 2022.1 (2022): 4255835.
[80] Sultan Ahmad, Sudan Jha, Abubaker E. M. Eljialy and Shakir Khan, “A Systematic Review on e-Wastage Frameworks” International Journal of Advanced Computer Science and Applications (IJACSA), 12(12), 2021.
[81] Khan, Shakir. "Visual Data Analysis and Simulation Prediction for COVID-19 in Saudi Arabia Using SEIR Prediction Model." International Journal of Online & Biomedical Engineering 17.8 (2021).
[82] Khan, Shakir, and Mohammed Altayar. "Industrial internet of things: Investigation of the applications, issues, and challenges." Int. J. Adv. Appl. Sci 8.1 (2021): 104-113.
[83] S. Khan, "Study Factors for Student Performance Applying Data Mining Regression Model Approach," International Journal of Computer Science Network Security, vol. 21, no. 2, pp. 188-192, 2021.
[84] Khan, Shakir, and Amani Alfaifi. "Modeling of coronavirus behavior to predict it’s spread." International Journal of Advanced Computer Science and Applications 11.5 (2020): 394-399.
[85] S. Khan and M. Alshara, "Development of Arabic evaluations in information retrieval," International Journal of Advanced Applied Sciences, vol. 6, no. 12, pp. 92-98, 2019.
[86] S. Khan and M. Alshara, "Fuzzy Data Mining Utilization to Classify Kids with Autism," International Journal of Computer Science Network Security, vol. 19, no. 2, pp. 147-154, 2019.
[87] S. Khan and M. F. AlAjmi, "A Review on Security Concerns in Cloud Computing and their Solutions," International Journal of Computer Science Network Security, vol. 19, no. 2, p. 10, 2019.
[88] Khan, Shakir. "Modern Internet of Things as a challenge for higher education." International Journal of Computer Science and Network Security 18.12 (2018): 34-41.
[89] S. Khan, A. S. Al-Mogren, and M. F. AlAjmi, "Using cloud computing to improve network operations and management," presented at the 5th National Symposium on Information Technology: Towards New Smart World (NSITNSW), 2015.
[90] AlAjmi, Mohamed F., and Shakir Khan. "Effective Use of Web 2.0 Tools Complex Pharmatical Skills Teaching And Learning." ICERI2011, 3rd International Conference on Education and New Learning Technologies, Spain. 2011.
[91] M. F. AlAjmi, S. Khan, and A. Sharma, "Collaborative learning outline for mobile environment," in 2014 International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT), 2014, pp. 429-434: IEEE.
[92] S. Khan, P. Sharma, K. R. Prasad, S. D, M. Serajuddin and R. Ayub, "The Implementation of Machine Learning in the Development of Sustainable Supply Chains," 2023 10th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON), Gautam Buddha Nagar, India, 2023, pp. 292-296, doi: 10.1109/UPCON59197.2023.10434528.
[93] Tayyab, Moeen, et al. "Recognition of Visual Arabic Scripting News Ticker From Broadcast Stream." IEEE Access 10 (2022): 59189-59204.
[94] Khan, Shakir. "Business Intelligence Aspect for Emotions and Sentiments Analysis." 2022 First International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT). IEEE, 2022.
[95] Khan, Shakir, and Mohammed Ali Alshara. "Adopting Open Source Software for Integrated Library System and Digital Library Automation." International Journal of Computer Science and Network Security 20.9 (2020): 158-165.
[96] Khan, Shakir, and M. Alajmi. "The Role Of Open Source Technology In Development Of E-Learning Education." Edulearn17 Proceedings. IATED, 2017.
[97] AlAjmi, M., and Shakir Khan. "Part of Ajax And Openajax In Cutting Edge Rich Application Advancement For E-Learning." INTED2015 Proceedings. IATED, 2015.
[98] Sattar, Kamran, et al. "Social networking in medical schools: Medical student’s viewpoint." Biomed Res 27.4 (2016): 1378-84.
[99] AlAjmi, Mohamed F., Shakir Khan, and Abdulkadir Alaydarous. "Data Protection Control and Learning Conducted Via Electronic Media IE Internet." International Journal of Advanced Computer Science and Applications 5.11 (2014).
[100] Khan, Shakir, et al. "Keeping Data on Clouds: Cloud Computing Significance." International Journal of Engineering & Science Research 3.2 (2013): 2321-2327.
[101] AlAjmi, Mohammed, and Shakir Khan. "Data Mining–Based, Service Oriented Architecture (SOA) In E-Learning." Iceri2012 Proceedings. IATED, 2012.
[102] AlAjmi, M., and Shakir Khan. "The Utility of New Technologies in Enhancing Learning Vigilance in Educationally Poor Populations." EDULEARN12 Proceedings. IATED, 2012.
[103] Alajmi, M., and S. Khan. "EFFECTIVE USE OF WEB 2.0 TOOLS IN PHARMACY STUDENTS'CLINICAL SKILLS PRACTICE DURING FIELD TRAINING." iceri2011 proceedings. IATED, 2011.
[104] Khan, Shakir, Mohammed AlAjmi, and Arun Sharma. "Safety Measures Investigation in Moodle LMS." Special Issue of International Journal of Computer Applications (2012).
[105] Khan, Shakir, and Arun Sharma. "Moodle Based LMS and Open Source Software (OSS) Efficiency in E-Learning." International Journal of Computer Science & Engineering Technology 3.4 (2012): 50-60.
[106] AlAjmi, Mohamed F., Arun Sharma Head, and Shakir Khan. "Growing cloud computing efficiency." International Journal of Advanced Computer Science and Applications (IJACSA) 3.5 (2012).
[107] AlAjmi, Mohamed F., Shakir Khan, and Arun Sharma. "Studying data mining and data warehousing with different e-learning system." International Journal of Advanced Computer Science and Applications 4.1 (2013).
[108] Khan, Shakir. "Data visualization to explore the countries dataset for pattern creation." International Journal of Online & Biomedical Engineering 17.13 (2021).
[109] AlAjmi, Mohamed Fahad, Shakir Khan, and Abu Sarwar Zamani. "Using instructive data mining methods to revise the impact of virtual classroom in e-learning." International Journal of Advanced Science and Technology 45.9 (2012): 125-134.
[110] Khan, Shakir. "Artificial intelligence virtual assistants (Chatbots) are innovative investigators." IJCSNS 20.2 (2020).
[111] Somnath Banerjee. Challenges and Solutions for Data Management in Cloud-Based Environments. International Journal of Advanced Research in Science, Communication and Technology, 2023, pp.370 - 378. ⟨10.48175/ijarsct-13555c⟩. ⟨hal-04901406⟩
[112] Parisa, S.K., Banerjee, S. and Whig, P. 2023. AI-Driven Zero Trust Security Models for Retail Cloud Infrastructure: A Next-Generation Approach. International Journal of Sustainable Devlopment in field of IT. 15, 15 (Sep. 2023).
[113] Banerjee, S. and Parisa, S.K. 2023. AI-Powered Blockchain for Securing Retail Supply Chains in Multi-Cloud Environments. International Journal of Sustainable Development in computer Science Engineering. 9, 9 (Feb. 2023).
[114] Somnath Banerjee. Exploring Cryptographic Algorithms: Techniques, Applications, and Innovations. International Journal of Advanced Research in Science, Communication and Technology, 2024, pp.607 - 620. ⟨10.48175/ijarsct-18097⟩. ⟨hal-04901389⟩
[115] Somnath Banerjee. Advanced Data Management: A Comparative Study of Legacy ETL Systems and Unified Platforms. International Research Journal of Modernization in Engineering Technology and Science, 2024, 6 (11), pp.5677-5688. ⟨10.56726/IRJMETS64743⟩. ⟨hal-04887441⟩
[116] Parisa, S.K. and Banerjee, S. 2024. AI-Enabled Cloud Security Solutions: A Comparative Review of Traditional vs. Next-Generation Approaches. International Journal of Statistical Computation and Simulation. 16, 1 (Jan. 2024).
[117] Somnath Banerjee. Intelligent Cloud Systems: AI-Driven Enhancements in Scalability and Predictive Resource Management. International Journal of Advanced Research in Science, Communication and Technology, 2024, pp.266 - 276. ⟨10.48175/ijarsct-22840⟩. ⟨hal-04901380⟩
[118] Banerjee, S., Whig, P. and Parisa, S.K. 2024. Cybersecurity in Multi-Cloud Environments for Retail: An AI-Based Threat Detection and Response Framework. Transaction on Recent Developments in Industrial IoT. 16, 16 (Oct. 2024).
[119] Banerjee, S., Whig, P. and Parisa, S.K. 2024. Leveraging AI for Personalization and Cybersecurity in Retail Chains: Balancing Customer Experience and Data Protection. Transactions on Recent Developments in Artificial Intelligence and Machine Learning. 16, 16 (Aug. 2024).
How to cite this paper
@article{1707329,
author = {Mohammad Serajuddin, Prabhdeep Singh},
title = {Enhancing Satellite Internet with Generative AI-Driven Predictive Beamforming},
journal = {Iconic Research And Engineering Journals},
year = {2025},
volume = {8},
number = {9},
pages = {1530-1543},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1707329.pdf},
abstract = {The integration of Generative Artificial Intelligence (AI) in satellite-based internet services presents a transformative approach to optimizing predictive beamforming for enhanced connectivity and efficiency. Traditional beamforming techniques rely on deterministic models and historical data, often struggling to adapt to dynamic environmental conditions, network congestion, and user mobility. This paper explores the potential of generative AI models, such as variational autoencoders (VAEs), generative adversarial networks (GANs), and transformer-based architectures, to predict optimal beam configurations in real time. By leveraging vast amounts of satellite telemetry, weather patterns, and user traffic data, generative AI can synthesize realistic future network states, mitigate latency, and improve signal coverage. We discuss the architectural considerations, training methodologies, and deployment challenges associated with AI-driven beamforming. Furthermore, we evaluate performance metrics, including beam alignment accuracy, spectral efficiency, and adaptability to disruptions, comparing AI-enhanced approaches with conventional predictive models. The findings suggest that generative AI can significantly enhance satellite internet services by improving coverage, reducing handover failures, and optimizing power allocation, paving the way for next-generation, AI-native satellite communication systems.},
keywords = {Generative AI, Predictive Beamforming, Satellite Internet, AI-Driven Beam Steering, and Dynamic Beam Allocation.},
month = {March},
}