User Mobility Evaluation for 5G Small Cell Networks Based on Individual Mobility Model

TL;DR

This paper evaluates user mobility in 5G small cell networks by incorporating human tendency and clustering behaviors into a new individual mobility model, providing insights into network performance.

Contribution

It introduces an individual mobility model that considers human habits, deriving key probabilities and coverage metrics for 5G small cell networks, unlike traditional models.

Findings

Derived user pause, arrival, and departure probabilities.

Calculated coverage probabilities for small and macro cells.

IMM offers a new perspective on mobility impact in 5G networks.

Abstract

With small cell networks becoming core parts of the fifth generation (5G) cellular networks, it is an important problem to evaluate the impact of user mobility on 5G small cell networks. However, the tendency and clustering habits in human activities have not been considered in traditional user mobility models. In this paper, human tendency and clustering behaviors are first considered to evaluate the user mobility performance for 5G small cell networks based on individual mobility model (IMM). As key contributions, user pause probability, user arrival and departure probabilities are derived in this paper for evaluat-ing the user mobility performance in a hotspot-type 5G small cell network. Furthermore, coverage probabilities of small cell and macro cell BSs are derived for all users in 5G small cell networks, respectively. Compared with the traditional random waypoint (RWP) model, IMM provides a different viewpoint to investigate the impact of human tendency and clustering behaviors on the performance of 5G small cell networks.