Trajectory planning of autonomous vehicles to ensure target QoS requirements in 6G mobile networks

The rollout of future 6G mobile networks is expected to deliver cutting-edge services with ultra-fast speeds, minimal latency and widespread connectivity. To support these target Quality-of-Service (QoS) requirements, Intelligent Transportation Systems involving self-driving vehicles should be designed to facilitate the autonomous driving operations to be decided in the 6G edge/core network, while providing seamless and immersive high bandwidth services to the humans that are travelling inside the vehicles. This task becomes particularly challenging in complex urban environments, especially when communication occurs over millimeter wave (mmWave) frequency bands, due to the fragmented coverage of cells in such situations. This paper studies the performance gains that is feasible when the trajectory of the Autonomous Vehicle (AV) is selected according to the QoS that the 6G network can provide in different parts of a Manhattan grid layout. More precisely, a graph is constructed in which the nodes are the crossroads and the weight of the edges connecting nodes is proportional to the minimum Spectral Efficiency (SE) across the streets that connect the given intersections. Then, the end-to-end trajectory of the vehicle can be selected based on the Maximizing the Minimum (Max-Min) scheme, which maximizes the minimum SE, encountered by the AV. The simulation results show that the proposed Max-Min scheme achieves significant performance improvements, delivering notable gains in the order of 40%-60% (20%-30%) are observed for 10th (50th) percentile SE, when the trajectory from the starting point to the destination is optimized based on the coverage of the mobile network.