## 4 Overview of Research Projects on AI/ML for Communications and Networking
### U.K.-EPSRC and U.S.-NSF  
The Engineering and Physical Sciences Research Council (EPSRC) in the U.K. has already funded 250 projects on AI technologies with an aggregate budget of around GBP 178 million, which roughly covers 3.2% of EPSRC's total investment portfolio [124]. Out of these grants, 100 projects fall under information and communication technologies (ICT), 24 grants are engineering focused, and 18 grants are used to train doctoral students. However, only a limited number of projects concern the integration of AI/ML into the B5G/6G wireless ecosystem. The LEANCOM project (GBP 0.9 million, November 2019 to November 2022) combines existing mathematical models for the performance evaluation at the PHY layer with deep learning, with an emphasis onlow-cost devices with hardware imperfections,which are overlooked by existing mathematical models [125]; recall from Section 2 the discussion on the model-aided ML. The 6 GRADIO project (GBP 0.5 million, December 2020 to November 2023) equips the Mitola radio [126] with the power of collective intelligence, using an intelligence gathering mechanism leveraging both game-theoretic approaches and DRL. Next, the overarching goal of the SWAN project (GBP 2.3 million, February 2020 to January 2025) is network security against cyber-attacks and resilience to network faults and failures. In this direction, SWAN applies AI/ML under four main pillars, namely, threat synthesis and assessment to proactively identify vulnerable interfaces, radio-frequency detection of cyber-attacks for risk mitigation, cyber-secure and agile design of waveforms using software-defined radios, and secure dynamic spectrum access [127]. Finally, the CONNECT project, funded by EPSRC through the European CHIST-ERA framework, is about collaborative and intelligent decision making at the edge through novel data caching, distributed computing, and federated learning [128], see Section 3.1.1 for a discussion on federated learning. Besides standard research projects, EPSRC has also created program grants, which bring together world-leading researchers to address significant challenges. One example in the fields of AI and networking is the TRANSNET grant (GBP 6.1 million, August 2018 to July 2024), intending to create an intelligent optical network, i.e., the backbone of the future digital infrastructure, which can dynamically allocate resources for maximising the network performance, where and when needed [129]. Under the same framework, EPSRC also funds theoretically oriented consortia, e.g., the MATHDL project (GBP 3.4 million, September 2021 to August 2026) aspires to develop a mathematically rigorous foundation for the training, inference, and performance of deep learning to enhance its explainability and trustworthiness [130]. Similarly, the GRAPHNEX project, funded through CHIST-ERA, focuses on explainable AI by decomposing highly connected DNNs into smaller units, which perform specific tasks with interpretable outcomes [131]. In the U.S., a partnership between Intel and the National Science Foundation (NSF) on ML for wireless networking systems was formed in 2019 [132]. The initiative has two main pillars, i.e., ML for spectrum management and distributed ML over wireless edge networks [133]. In a nutshell, under the first pillar, the funded projects cover model-based ML at the PHY layer to address poorly understood non-linear distortions and relax simplified assumptions on impairment models, construct robust channel codes under interference and enhance the network performance through intelligent power control, beamforming, scheduling, distributed spectrum sensing and spectrum access. Under the second pillar, most projects investigate how to realise collective intelligence at the edge, using enhanced and multi-hop federated learning.