An Iterative-Based Optimum Power and Resource Allocation in Application-Dependent Scenarios for One-to-One D2D Communication

Abstract

Efficient and timely sharing of critical information is crucial for Public Safety (PS) communications, which can be fulfilled using one of the cutting-edge technologies, Device-to-device (D2D) communication. During an emergency, the PS applications should be prioritized over other applications, ensuring the emergency messages reach the first responders in time. Due to its inherent characteristics, the evolved Node Base station will not prioritize or categorize the D2D communication based on its application type, thus treating all applications equally. Further, D2D communication introduces significant interference to cellular users and vice-versa while sharing resources, and it is vital to reduce the impact of these interferences to ensure the Quality of Service for all users in the network. Hence, this article proposes a novel interference management approach to increase the overall sum rate of the system. In addition, the proposed approach also allows more D2D communication in general, particularly PS applicationbased D2D communication, to be active in the network. As the formulated problem is a Mixed-Integer Non-Linear Programming (MINLP) type of problem, it is split into two sub-problems, namely, Iterative Resource Allocation and Sharing and Iterative Power Optimization to achieve a polynomial time complexity. The theoretical proofs adequately explain the algorithm's time complexity and convergence property. The simulation results show that the proposed system enhances the overall sum rate by allowing more active PS D2D applications in the network.INDEX TERMS D2D communication, power optimization, interference management, iterative algorithm, one-to-one resource allocation.Recent research explores the possibility of sharing the Resource Blocks (RBs) (the smallest chunk of the spectrum) of Cellular User Equipment (CUEs) with D2D User Equipment (DUE) in underlay in-band communication to significantly enhance spectrum efficiency [4]. The different resource-sharing strategies in practice are one-to-one, oneto-many, and many-to-many. In the one-to-one technique,