A System-by-Design Approach for Optimal Planning of EM Skins in Smart Urban Areas

This work deals with the optimal planning of low-cost/low-profile passive and static electromagnetic skins (EMSs) allowing to implement Smart Electromagnetic Environments (SEMEs) in large urban areas. Owing to the high complexity/scale of the EM problem at hand, the planning problem is formulated as a global optimization one efficiently solved thanks to a suitably-customized System-by-Design (SbD) methodology relying on Machine Learning (ML) and Evolutionary Algorithms (EAs). An illustrative example is shown to assess the effectiveness of the proposed SEME planning method in a realistic scenario.