Path Planning Optimization Based Interference Awareness for Mobile Robots in mmWave Multi Cell Networks

The emerging beyond fifth-generation (B5G) and envisioned sixth-generation (6 G) wireless networks are considered as key enablers in supporting a diversified set of applications for industrial mobile robots (MRs). The scenario under investigation in this paper relates to mobile robots that autonomously roam on an industrial floor and perform a variety of tasks at different locations, whilst utilizing high directivity beamformers in millimeter wave (mmWave) small cells. In such scenarios, the potential close proximity of mobile robots connected to different base stations may cause excessive levels of interference having as a net result a decrease in the overall achievable data rate in the network. To resolve this issue, a novel MR optimal path planning scheme via a mixed integer programming formulation is proposed where robots' trajectory is considered jointly with the interference level at different beam sectors. To combat the curse of dimensionality, a geographical division clustering based MR path planning heuristic scheme is proposed to enable scalability and real-time decision making. The proposed heuristic aims to find a low interference path for each mobile robot whilst achieving a near-optimal performance. A wide set of numerical investigations reveal that the proposed optimal and heuristic path planning schemes for the mmWave connected mobile robots can improve the overall achievable throughput by up to 93% compared to an interference oblivious scheme without penalizing the total travel time.