BEST-RIM: A mmWave Beam Steering Approach Based on Computer Vision-Enhanced Reconfigurable Intelligent Metasurfaces

In this work, we consider Reconfigurable Intelligent Meta-surfaces (RIMs) to provide effective beam steering functionality, while enhancing the coverage of fifth generation (5G) users in a urban city mobility context. particular, enable communications millimeter wave (mmWave) frequencies, that can occur simultaneously with other 5G communications. The main objective paper is demonstrate feasibility and advantages an integrated Computed Vision (CV) approach for tuning meta-atom states RIM structure working at mmWave frequency band, without estimating interferes' radio channel. CV system will feed logic unit running Machine Learning (ML) algorithm compute real-time coding schemes, namely sequence binary associated each unit-cell RIM, order obtain target reconfigurable radiation pattern. Specifically, Genetic Algorithm (GA) introduced derive most suitable pattern Beam Steering application, based on input infrastructure. Results show such kind system, higher achieved dense scenarios, by improving robustness against potential blockages technology. Moreover, robust inaccuracy GA.