Efficient Resource Allocation Using Distributed Edge Computing in D2D Based 5G-HCN With Network Slicing

Abstract

Fifth Generation (5G) cellular networks aim to overcome the pressing demands posed by dynamic Quality of Service (QoS) constraints, which have primarily remained unaddressed using conventional network infrastructure. Cellular networks of the future necessitate the formulation of efficient resource allocation schemes that readily meet throughput requirements. The idea of combining Device-to-Device (D2D), Mobile Edge Computing (MEC), and Network slicing (NS) can improve spectrum utilization with better performance and scalability. This work presents a spectrum efficiency optimization problem in D2D based 5G-Heterogeneous Cellular Network (5G-HCN) with NS. Owing to the shortage of resources, we propose an underlay model where macro-cell users (MUs), small-cell users (SUs), and D2D users (DUs) reuse the resources while considering the effects of interference. The goal is to maximize the average network spectrum efficiency (SE) and throughput without degrading the system performance. The problem at hand is naturally a non-convex mixed-integer non-linear programming (MINLP) problem that is intractable. Therefore, we have suggested a distributed resource allocation strategy with an edge computing (DRA-EC) approach to find the sub-optimal solution. In distributed augmented Lagrange method, each edge router located at BS will solve its problem locally, and the consensus algorithm will find the global solution using these local estimates. The central slice controller will cut the customized network slices according to the bandwidth requirements of each user type with optimized spectrum information. The simulation outcomes prove that our proposed method is near the central optimization scheme with low computational complexity. It is much better because it reduces the computational time and system overhead.

Quality of Service based resource allocation in D2D enabled 5G-CNs with network slicing

“…All these works solved the problem of RA using centralized optimization methods, but none of them used the distributed approach, which is the major novelty of this work. In our previous work [8], we solved the problem of spectrum efficiency maximization using the distributed method in D2D enabled 5G-CNs with network slicing. Still, the QoS-based customized network slicing (mMTC and eMBB) was missing in that work.…”

“…The primary goal of research for all future enhancements these days is to design an innovative system model capable of connecting with an enormous number of devices supporting a vast range of customized services with minimum system overhead and computation delay. Efficient RA in such a system is the main challenge these days, which must be addressed [8]. Network slicing allows the users to use their required QoS slice to assign resources based on their needs.…”

A Survey of Resource Management in D2D Communication for B5G Networks

“…In order to support wireless networks and improve their Quality of Service (QoS), UAVs may be deployed rapidly and effectively due to their flexibility and mobility [41]. In the latter, MEC allows users to offload computational tasks to the edge server [42], which may reduce device costs and improve QoS [43]. However, the presence of D2D technology in the B5G network plays a vital role in assisting MEC and UAVs to enable communications when conventional terrestrial networks are damaged or infeasible [44].…”

An Accurate Model to Estimate 5G Propagation Path Loss for the Indoor Environment

“…In the last decade, different technologies are developed, such as the role of 5G in transportation in smart cities and in-vehicle communication [1], creating the artificial system to control network traffic (CTN) [2], permitting to create the protocol to increase the security of the application and software [3], satellite communication [4], IoT [5], in biomedical to detect the tumors [6], innovative sensors [7], Passive Optical Networks (PON) [8], energy harvesting [9], Massive Multiple Input Multiple Output (MIMO) [10], robotic control communication [11], and hybrid power systems for convenient cellular operation [12]. The "Big Three" of the coming wireless networks are small cell networks, mm-wave technology, and D2D communication [13]- [15].…”