Move Away From Me! User Repulsion Under Proximity-Induced Interference in OWC Systems

Abstract:
As communication systems shift towards ever higher frequency bands, the propagation of signal between a user device and an infrastructure becomes more susceptible to nearby obstacles, including other users. As an extreme case, we consider such proximity-induced channel impairments in indoor optical wireless communication (OWC) systems. We set up a model, where the achievable OWC data rate depends not only on the relative position between a user device and an infrastructure access point, but also on the location of other users modeled as proximal interferers. We use a reinforcement learning (RL) approach to enable users to find suitable positions, both relative to the access point and to each other, that maximise the sumrate capacity of the system. Our initial results demonstrate a feasibility of RL-based approach that enables indoor OWC users to find suitable balance between establishing high-rate direct link while remaining distant from proximal interferers.