🔗 https://lnkd.in/eySdFCSQ 🌟 #PopularPaper
"At the Dawn of Generative AI Era: A Tutorial-cum-Survey on New Frontiers in 6G Wireless Intelligence" is now among the most popular papers of IEEE Open Journal of the Communications Society. Given its depth and breadth, we believe this 5️⃣7️⃣ pages document will be a pivotal reference for professionals and researchers planning to delve into the burgeoning field of #GenAI and #GenerativeModels (GMs).
💡The majority of data-driven wireless research leans heavily on #discriminative #AI (DAI) that requires vast real-world datasets. Unlike the DAI, #GenAI pertains to GMs capable of discerning the underlying data distribution, patterns, and features of the input data. This makes #GenAI a crucial asset in wireless domain wherein real-world data is often scarce, incomplete, costly to acquire, and hard to model or comprehend. With these appealing attributes, GenAI can replace or supplement DAI methods in various capacities.
📗 Following preliminaries on #DiscriminativeAI and #GenAI, we first present a tutorial on seminal examples of GMs such as 1️⃣ Generative Adversarial Networks (#GANs), 2️⃣ Variational Autoencoders (#VAEs), 3️⃣ Flow-based GMs, 4️⃣ Diffusion-based GMs, 5️⃣ Generative Transformers (#GPTs), 6️⃣ Large Language Models (#LLMs), 7️⃣ Autoregressive GMs, to name a few.
📘 Contrary to the prevailing belief that #GenAI is a nascent trend, our exhaustive review of more than 1️⃣2️⃣0️⃣ technical papers demonstrates the scope of research across core wireless research areas, including 1️⃣ Physical Layer Design; 2️⃣ Network Optimization, Organization, and Management; 3️⃣ Network Traffic Analytics; 4️⃣ Cross-Layer Network Security; and 5️⃣ Localization & Positioning. Interestingly, almost all these works focused on #GANs and #VAEs; leaving other promising GMs unexplored.
🔎There are many challenges to address and niche applications to explore! Hence, we outline the central role of GMs in pioneering areas of #6G network research, including #semantic / #THz / #nearfield communications, #ISAC, extremely large antenna arrays, #digitaltwins, #AI-generated content services, #mec and #edgeAI, #adversarial #ML, and #trustworthyAI. Lastly, we shed light on the multifarious challenges ahead, suggesting potential strategies and promising remedies.
👨🔬 Abdulkadir Çelik and Ahmed Eltawil
🏛 KAUST CEMSE, KAUST (King Abdullah University of Science and Technology)
IEEE IEEE Computer Society IEEE Xplore IEEE ComSoc Young Professionals IEEE Signal Processing Society ACM, Association for Computing Machinery ACM arXiv Machine Learning Research at arXiv IEEE Communications Society IEEE Access IEEE The Institute Proceedings of the IEEE Computer Engineering Computer Science Computer Networking Computer Literacy Shannon Wireless Huawei Ericsson 6G-life Wireless Networking Wireless Communications Systems Huawei Wireless 6G Flagship telecomhall International Telecommunication Union Generative AI
