{"title":"Editorial SI on Advances in AI for 6G Networks","authors":"Hatim Chergui;Kamel Tourki;Jun Wu","doi":"10.1109/LNET.2024.3519937","DOIUrl":"https://doi.org/10.1109/LNET.2024.3519937","url":null,"abstract":"The advent of 6G networks heralds a new era of telecommunications characterized by unparalleled connectivity, ultra-low latency, and immersive applications such as holographic communication and Industry 5.0. However, these advancements also introduce significant complexities in network management and service orchestration. This Special Issue of IEEE N<sc>etworking</small> L<sc>etters</small> explores cutting-edge research on Artificial Intelligence (AI)-driven automation techniques designed to address these challenges. The selected works span a diverse array of AI paradigms—ranging from generative AI (GenAI) and reinforcement learning to multi-agent systems and federated learning—showcasing their applications across various 6G technological domains. By highlighting these innovations, this issue aims to provide valuable insights into the pivotal role of AI in shaping the future of 6G networks.","PeriodicalId":100628,"journal":{"name":"IEEE Networking Letters","volume":"6 4","pages":"215-216"},"PeriodicalIF":0.0,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10880116","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143388619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"When to Reach for the Skies? A DRL-Based Routing Framework for Non-Terrestrial Networks","authors":"Akanksha Sharma;Sharda Tripathi;Sandeep Joshi","doi":"10.1109/LNET.2025.3529514","DOIUrl":"https://doi.org/10.1109/LNET.2025.3529514","url":null,"abstract":"Non-terrestrial networks are envisioned to be an integral component of the beyond-fifth-generation wireless communication networks, catering to both conventional and emerging communication applications. In particular, a plethora of use cases are emerging for ultra-reliable low-latency communication, which require dynamic and quality of service compliant frameworks. In this letter, we formulate a binary integer non-linear programming problem to route time-critical traffic through non-terrestrial nodes. As the problem is NP-hard, we propose the solution using a deep reinforcement learning framework, taking into account the interactions between the terrestrial and various non-terrestrial nodes with an end-to-end latency target while maximizing the coverage probability. We perform simulations for multiple latency deadlines and outage thresholds and the results corroborate the efficiency of the proposed framework. Furthermore, we benchmark the proposed framework and show an improvement of 96.31% in coverage while incurring only 3.2% latency violations compared to the state-of-the-art.","PeriodicalId":100628,"journal":{"name":"IEEE Networking Letters","volume":"7 1","pages":"16-20"},"PeriodicalIF":0.0,"publicationDate":"2025-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10841394","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143645267","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Salim El Ghalbzouri;Karim Boutiba;Adlen Ksentini;Mustapha Benjillali
{"title":"Neural-Driven Control of RIS in 6G Networks: A GoSimRIS and xApp-Based Framework","authors":"Salim El Ghalbzouri;Karim Boutiba;Adlen Ksentini;Mustapha Benjillali","doi":"10.1109/LNET.2025.3527683","DOIUrl":"https://doi.org/10.1109/LNET.2025.3527683","url":null,"abstract":"In this letter, we propose an O-RAN-based framework for reconfigurable Intelligent Surfaces (RIS) control in 6G. The key objective is to enable the development of RIS control algorithms as xApps running at the real-time intelligent controller (RIC) of Open RAN (O-RAN). To validate the proposed framework, we developed a Golang-based RIS simulator, GoSimRIS, intended to mimic and examine RIS behavior in various environmental scenarios. The simulator is linked with the RIC via a specialized Service Model (SM) devised in this letter, namely E2SM RIS, which allows the design of xApps that dynamically optimize RIS coefficients by computing the ideal phase shifts and applying them in real-time to maximize network performance using channel information that is retrieved from the GoSimRIS environment. Finally, we introduce an ML-based RIS control mechanism that runs as an xApp using only the positions of the transmitter (Tx) and receiver (Rx) and the presence of Line-of-Sight (LOS) conditions, which corresponds to a realistic indoor scenario in 6G such industry 4.0","PeriodicalId":100628,"journal":{"name":"IEEE Networking Letters","volume":"7 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143645265","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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