An Efficient Multi-Carrier Resource Allocation with User Discrimination Framework for 5G Wireless Systems

TL;DR

This paper introduces a novel multi-carrier resource allocation framework for 5G systems that considers user classes, application types, and QoS guarantees to optimize resource distribution among diverse users.

Contribution

It proposes a new utility-based, user-discrimination resource allocation algorithm for 5G that guarantees minimum QoS and accounts for user classes and application types.

Findings

The algorithm guarantees minimum QoS for users.

Simulation results show improved resource utilization.

Optimal solutions exist for the proposed allocation problem.

Abstract

In this paper, we present an efficient resource allocation with user discrimination framework for 5G Wireless Systems to allocate multiple carriers resources among users with elastic and inelastic traffic. Each application running on the user equipment (UE) is assigned an application utility function. In the proposed model, different classes of user groups are considered and users are partitioned into different groups based on the carriers coverage area. Each user has a minimum required application rate based on its class and the type of its application. Our objective is to allocate multiple carriers resources optimally among users, that belong to different classes, located within the carriers' coverage area. We use a utility proportional fairness approach in the utility percentage of the application running on the UE. Each user is guaranteed a minimum quality of service (QoS) with a priority criterion that is based on user's class and the type of application running on the UE. In addition, we prove the existence of optimal solutions for the proposed resource allocation optimization problem and present a multi-carrier resource allocation with user discrimination algorithm. Finally, we present simulation results for the performance of the proposed algorithm.