Continual Meta-Reinforcement Learning for UAV-Aided Vehicular Wireless Networks

An important use case is offered by vehicular ground users are static and have known locations. The same wireless networks, in which UABSs serve as relays authors in [28] extended their previous work by considering between vehicular users and the network, enabling the users multiple UABSs. Unlike these previous works, in this paper, to upload data collected by on-board sensors [5]-[11]. Such we consider traffic conditions characterized by vehicular users user-generated data are collected by the network, and then with a priori unknown locations and we move beyond conventional forwarded to other vehicles by means of BSs or road side meta-RL by accounting for the constraint that simulators units (RSUs). Being able to offer stronger, possibly line-ofsight for previous traffic configurations cannot be revisited. The (LoS), links to vehicles as compared to (static) ground rest of the paper is organized as follows. The system model BSs, UABSs can support demanding vehicle-to-everything and the problem formulation are described in Section II.