# AI-Enabled Interference Mitigation for Autonomous Aerial Vehicles in Urban 5G Networks +
## 1 Introduction  
Over the past few years, the adoption of unmanned aerial vehicles (UAVs) or drones in commercial and civilian applications has increased significantly due to advances in manufacturing processes, resulting in their economic feasibility. This increase in usage has opened up an extensive range of potential applications, including photography, aerial inspection, disaster relief, traffic control, precision agriculture, delivery systems, and communications. Consequently, regulatory bodies and authorities have developed frameworks to ensure the safe and effective use of UAVs. For example, the Federal Aviation Administration (FAA) in the United States has issued operational regulations for small unmanned aircraft systems (UASs) weighing under 25 kg for civilian applications. Additionally, the FAA has launched the \"Drone Integration Pilot Program\" to facilitate the exploration of expanded UAV applications. This program includes rules for night flights, applications requiring UAVs to fly over people, and beyond visual line of sight (BVLoS) operations [1]. The issue of communication with cellular-connected UAVs has gained significant attention in recent times [2]. Existing cellular networks have not been specifically optimised to support UAVs and are primarily focused on providing high-quality service to terrestrial users. Given the stringent regulatory requirements, the need for extensive research and standardization efforts to ensure the reliable operation of UAVs in a range of deploymentscenarios is evident. These factors highlight the importance of optimizing current cellular networks to facilitate seamless communication with UAVs. Novel guidelines and programs like the FAA's \"Drone Integration Pilot Program\" are expected to accelerate the growth of the UAV industry globally. Thus, UAVs are seen as an interesting opportunity for businesses in the next decade. One of the prominent technologies to enable UAV communications is fifth-generation (5G) cellular technology. Indeed, 5G technology will ultimately replace fourth-generation (4G) networks as the new standard cellular networks. Currently, it provides connectivity to most cell phones, and 5G is beneficial because it is expected to provide higher download speeds and greater bandwidth. The future infrastructure of 5G networks can therefore link seamlessly and ubiquitously with everything. For instance, one attractive and growing technology is the Internet of Things (IoT), which has generated a tremendous increase in data traffic, thus leading to the requirement of advanced networks to cope with reliability and traffic requirements. The realization of 5G and beyond 5G (B5G) wireless networks is crucial to meet the requirements of connected UAVs. These networks offer low latency, high speed, massive capacity, and edge computing, which can enable UAVs to operate virtually in real time. This translates to fewer incidents of loss of control and mid-air collisions, making 5G networks a critical component for the safe and efficient operation of UAVs. Therefore, there is an urgent need to accelerate the development and deployment of 5G networks to support the growth of the UAV industry [3]. Although 5G networks can provide high data rates and low latency, they may not be fully optimised for UAVs and may face challenges such as signal blockage and limited coverage. Therefore, we may need to consider using sixth-generation (6G) networks, which are expected to provide advanced features such as intelligent networking, enhanced sensing and perception, and autonomous decision making to resolve current challenges in communication with UAVs. However, it should be noted that the scope of our project does not include the development of 6G networks [4; 5]. The utilization of UAVs in communication confers various promising advantages, including the ability for ad-hoc deployment, adaptable network reconfiguration, and a higher probability of achieving line of sight (LOS) links.