Dynamic Mobility Load Balancing for 5G Small-Cell Networks Based on Utility Functions

Khaled M Addali,Michel Kadoch,Zhenjiang Zhang,Yaser Khamayseh,Suhib Younis Bani Melhem

doi:10.1109/access.2019.2939936

Abstract

Deployment of small cells was introduced to support high data rate services and expand macro cell coverage for the envisioned 5G networks. A small cell network, which has a smaller size, along with the user equipment (UE) mobility, frequently undergoes unbalanced load status. Consequently, the network performance is affected in terms of throughput, increasing handover failure rate, and possibly higher link failure rate. Hence, load balancing has become an important part of recent researches on small cell networks. Mobility Load Balancing (MLB) involves load transfer from an overloaded small cell to under-loaded neighbouring small cells for the more load-balanced network. This transfer is performed by adjusting the handover parameters of the UEs according to the load situations of the small cells in the vicinity. However, inaccurate adjustment of parameters may lead to inefficient usage of network resources or degrade the Quality of Service (QoS). In this paper, we introduce a Utility-based Mobility Load Balancing algorithm (UMLB) and a new term named load balancing efficiency factor (LBEF). The UMLB algorithm considers the operator utility and the user utility for the MLB-based handover process. While LBEF is proposed to order the overloaded cells properly for the MLB algorithm operation. The simulation results show that the UMLB minimizes standard deviation with a higher average-UE data rate when compared to existing load balancing algorithms. Therefore, a well-balanced network is achieved.

Highlights

The increases in the use of smartphones and applications for information, and communications technologies are causing a rapid increase in the demand for mobile broadband services with higher data rates and higher Quality of Service (QoS)
The main contribution of this paper is to introduce a Utility-based Mobility Load Balancing algorithm (UMLB) by considering both the operator utility and the user utility at the same time for each lightly loaded neighbouring cell
We introduced a new term named load balancing efficiency factor (LBEF) that considers a load of neighbouring cells and the edge-user equipment (UE) for each overloaded cell

Summary

INTRODUCTION

The increases in the use of smartphones and applications for information, and communications technologies are causing a rapid increase in the demand for mobile broadband services with higher data rates and higher QoS. MLB utilizes cells load information to optimize the cell boundaries to offload UEs. SON uses mobility/handover parameters for load balancing [8], [9]. The main contribution of this paper is to introduce a Utility-based Mobility Load Balancing algorithm (UMLB) by considering both the operator utility and the user utility at the same time for each lightly loaded neighbouring cell. Researchers in [12] was the first to demonstrate through simulation the effectiveness of simple load balancing algorithms in reducing the call blocking rate and increasing cell-edge throughput based on auto-adjustment of handover parameters. When a small cell is detected to be overloaded, the SON has a function that decreases the power and makes some edge-UEs offload to the lightly-loaded side of the network. Examples of these characteristics could be the frequency and duration of the UEs’ connections and (or) the QoS metrics (throughput, and delay)

SYSTEM MODEL CONSTRAINTS

CELL LOAD CALCULATION

AN ADAPTIVE UTILIZATION THRESHOLD FOR LOAD STATUS DETECTION

Findings

VIII. CONCLUSION