Static Reflecting Surface Based on Population-level Optimization

Abstract

We consider a Static Reflecting Surface (SRS) assisted communication system. Part of a cell served by a Base Station (BS) is blocked from Line-of-Sight (LoS), and an SRS is deployed to assist communication in that target area. The SRS has a high number of reflecting elements, with a static phase shift matrix, optimized offline at installation phase for a user population. To find the beamformer at the BS and phase shift matrix at the SRS, we formulate an optimization problem aiming to maximize the average data rate in the target area assuming LoS communication between SRS and BS, as well as between SRS and the users. A local optimum of the population-level problem is obtained using the interior point method. We furthermore consider a low complexity approach, where we divide the SRS & BS antennas into sub-blocks and the target area into subareas; each sub-block is designed to serve a user at the center of the corresponding subarea. Simulation results show that as compared to a fully dynamic Reconfigurable Intelligent Surface (RIS) of the same size, where there is real-time electronic control of the phase shifter, an SRS loses 30% in performance. Comparing to other SRS approaches, and broadcast approach from the literature, the population based approach provides higher average Spectrum Efficiency (SE), 5% SE and fairness index.