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On the specialization of FDRL agents for scalable and distributed 6G RAN slicing orchestration Rezazadeh, Farhad Zanzi, Lanfranco Devoti, Francesco Chergui, Hatim Costa Pérez, Xavier Verikoukis, Christos Universitat Politècnica de Catalunya. Doctorat en Teoria del Senyal i Comunicacions Àrees temàtiques de la UPC::Enginyeria electrònica Mobile communication systems. B5G/6G Network slicing AI Federated learning Deep reinforcement learning Distributed management Sistemes de comunicacions mòbils ©2022 IEEE. Reprinted, with permission, from Rezazadeh, F., Zanzi, L., Devoti, F. et.al. On the Specialization of FDRL Agents for Scalable and Distributed 6G RAN Slicing Orchestration. IEEE Transactions on vehicular technology (Online) October 2022 Network slicing enables multiple virtual networks to be instantiated and customized to meet heterogeneous use case requirements over 5G and beyond network deployments. However, most of the solutions available today face scalability issues when considering many slices, due to centralized controllers requiring a holistic view of the resource availability and consumption over different networking domains. In order to tackle this challenge, we design a hierarchical architecture to manage network slices resources in a federated manner. Driven by the rapid evolution of deep reinforcement learning (DRL) schemes and the Open RAN (O-RAN) paradigm, we propose a set of traffic-aware local decision agents (DAs) dynamically placed in the radio access network (RAN). These federated decision entities tailor their resource allocation policy according to the long-term dynamics of the underlying traffic, defining specialized clusters that enable faster training and communication overhead reduction. Indeed, aided by a traffic-aware agent selection algorithm, our proposed Federated DRL approach provides higher resource efficiency than benchmark solutions by quickly reacting to end-user mobility patterns and reducing costly interactions with centralized controllers Peer Reviewed Preprint 2022-10-31 Article Rezazadeh, F. [et al.]. On the specialization of FDRL agents for scalable and distributed 6G RAN slicing orchestration. "IEEE Transactions on vehicular technology", 31 Octubre 2022, p. 1-15. 1939-9359 https://hdl.handle.net/2117/378217 10.1109/TVT.2022.3218158 eng https://ieeexplore.ieee.org/document/9933014 Open Access 15 p. application/pdf Institute of Electrical and Electronics Engineers (IEEE)