Empowering UAV Communication with Intelligent Learning

In the recent years, there is a proliferating demand from the end users for soaring capacity, improved speed, seamless connectivity, reduced latency, enormous bandwidth, high accuracy, better quality of service (QoS), improved security and privacy, high extensibility and scalability, etc. Therefore, to get the breakthrough from the previously set standards Unmanned Aerial Vehicle (UAV) communication in 5G was introduced to exploit its multifarious advantages and applications. A concurrent boom in the field of Machine Learning (ML) and its inclusion with UAV provides the cutting edge for numerous opportunities to be explored. This survey gives a deep insight into UAVs’ collaboration with the blooming and innovative learning techniques of ML including Gossip Learning (GL), Split Learning (SL), Reinforcement Learning (RL), Transfer Learning (TL), and Federated Learning (FL). In preceding years, focus was mainly on speedy development of wireless communication which drastically affected our environment as a result of increased radiations, electronic waste (e-waste), energy consumption, and massive deployments of Base Stations (BS) and cell towers. With raging environment awareness these techniques are being suggested as a great solution for various applications of UAVs and support our vision of green and smart communication.