Ant Colony Optimization for Programmable Wireless Environments: Enabling Model and Initial Results

Wireless communications are subject to the chaotic scattering of wireless waves. However, the recently-proposed software-defined metasurfaces (SDMs) can transform the wireless propagation into a programmable and even fully deterministic phenomenon. Unnatural aerial paths can be created by program-ming multiple SDMs deployed in an environment, to alter the direction, phase, amplitude and polarization of waves impinging upon them. Optimizing this programming is an open challenge as parasitic effects, e.g. parasitic reflection lobes, can appear and deteriorate the quality of the received power delay profile. This paper proposes a novel optimization algorithm based on the ant colony framework, through which the SDM programming options are explored, gradually converging to a significantly improved received power delay profile. The study first presents a novel graph-based model of SDM-enabled environments, which ab-stracts the underlying physics, facilitating their cross-disciplinary understanding. Simulation results showcase the flexibility of the model and optimization algorithm in multiple settings.