RESOURCE ALLOCATION FOR LARGE INTELLIGENT SURFACE/ANTENNA

Abstract

Recently, large intelligent surfaces/antennas (LISA) have been widely stud- ied as an emerging technology for future wireless networks. In general, LISA

contains a large number of passive sensors that are able to adjust a phase-shift on impinging signals. To this end, an intelligent module can control this phase-shift resulting in controlling the wireless multipath channel phase-distortion, which is random in nature. In this work, we study on how a LISA can serve multiple

Device-to-device (D2D) communications. Here, we consider LISA sensors as re- sources and propose a genetic algorithm (GA) based optimization for the proper

resource allocation of LISA elements. The application of the algorithm produces admirable results that stand out compared to the resource allocation process that does not employ this method. The overall Spectral Efficiency values estimated in several aspects are much more improved using the GA-based scheme. The study in this thesis was able to not only provide a sensor allocation, but also enhance the sum rate values of the system.