Resource Management for Device to Device Communication in Heterogeneous Network Using AI

Abstract

The broad accessibility of high-speed Internet connectivity enables users to newlineengage with data-intensive applications like online gaming, live streaming, newlineand various others. Faster and more reliable Internet connections facilitate newlinethe seamless functioning of applications that require large amounts of data. newlineMoreover, it heightened the need for bandwidth accompanied by reduced newlinelatency. When the demand for bandwidth exceeds the available spectrum, newlineit can result in congestion and reduce spectral efficiency. So, there is a newlineneed to enhance the current cellular network infrastructure. Researchers newlineare investigating and highlighting the potential advantages of device-todevice newline(D2D) communication to enhance spectral efficiency. It provides newlinedirect communication, enabling devices to exchange data without depending newlineon the cellular infrastructure, which enhance spectrum efficiency and newlinenetwork capacity. Apart from these advantages, D2D communication faces newlineseveral issues, i.e., initial device discovery, resource allocation (ReA), and newlineinterference management. ReA is the major issue in underly D2D communication, newlinewhere the efficient allocation of power, spectrum, and channel newlineresources enhances fairness, energy efficiency, and system throughput. newlineIn ReA, the devices face interference like the D2D receiver faces interference newlinefrom the cellular users (CUs) and CU experiences interference from newlinethe D2D receiver. Hence, there is a requirement for an efficient ReA in a newlineD2D communication environment (DCE). Further, optimising the transmit newlinepower of D2D users (DUs) is required to mitigate interference in the DCE. newlineThe research community employed various schemes based on game theory, newlineheuristic algorithms, and graph theory for ReA and PC in DCE. However, newlinethe existing system faces computation overhead issues when more devices newlineare in the dynamically changing communication environment. Here, we newlineproposed an AI-based ReA and PC scheme that improves the system sum newlinerate Srate while reducing the computation overhead. newlineand#136; Firstly, we propose a novel scheme f