# Efficient Radio Resource Management for Wireless Cellular Networks with Mobile Edge Computing

## TL;DR

This paper presents an integrated framework for computation offloading and interference management in wireless cellular networks with mobile edge computing, optimizing resource allocation to improve performance.

## Contribution

It introduces a novel combined approach for offloading decisions and interference mitigation using graph coloring and local overhead estimation.

## Key findings

- The proposed scheme improves resource utilization efficiency.
- Simulation results demonstrate enhanced network performance.
- The framework adapts well to different system parameters.

## Abstract

Mobile edge computing (MEC) has attracted great interests as a promising approach to augment computational capabilities of mobile devices. An important issue in the MEC paradigm is computation offloading. In this paper, we propose an integrated framework for computation offloading and interference management in wireless cellular networks with mobile edge computing. In this integrated framework, the MEC server makes the offloading decision according to the local computation overhead estimated by all user equipments (UEs) and the offloading overhead estimated by the MEC server itself. Then, the MEC server performs the PRB allocation using graph coloring. The outcomes of the offloading decision and PRB allocation are then used to allocate the computation resource of the MEC server to the UEs. Simulation results are presented to show the effectiveness of the proposed scheme with different system parameters.