Resource Allocation in Large Intelligent Surfaces/Antennas Using Genetic Algorithm Approach

Recently, large intelligent surfaces/antennas (LISA) have been widely studied 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, LISA sensors are scarce resources which should be allocated among the D2D communications optimally. For this purpose, we propose a Genetic algorithm-based optimization to maximize the spectral efficiency and minimize the interference. Our approach has been evaluated with extensive simulations, thus providing new observations and findings.

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Resource Allocation in Large Intelligent Surfaces/Antennas Using Genetic Algorithm Approach

Semantic Scholar · Engineering · 2023

Abstract

Recently, large intelligent surfaces/antennas (LISA) have been widely studied 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, LISA sensors are scarce resources which should be allocated among the D2D communications optimally. For this purpose, we propose a Genetic algorithm-based optimization to maximize the spectral efficiency and minimize the interference. Our approach has been evaluated with extensive simulations, thus providing new observations and findings.

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