User Mobility Evaluation for 5G Small Cell Networks Based on Individual Mobility Model
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- 5 February 2016
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Journal on Selected Areas in Communications
- Vol. 34 (3), 528-541
- https://doi.org/10.1109/jsac.2016.2525439
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 evaluating 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.Keywords
Funding Information
- International Science and Technology cooperation program of China (2015DFG12580, 2014DFA11640)
- National Natural Science Foundation of China (NSFC) (61301128, 61461136004)
- NFSC Major International Joint Research Project (61210002)
- Fundamental Research Funds for the Central Universities (2015XJGH011, 2014QN155)
- EU FP7-PEOPLEIRSES
- S2EuNet (247083)
- WiNDOW (318992)
- CROWN (610524)
- Science and Technology Commission of Shanghai Municipality (STCSM) (15511103200)
- National Natural Science Foundation of China (NSFC) (61231009, 61461136003)
- Ministry of Science and Technolgoy (MOST) (2014DFE10160)
This publication has 39 references indexed in Scilit:
- Handoff Rate and Coverage Analysis in Multi-Tier Heterogeneous NetworksIEEE Transactions on Wireless Communications, 2015
- A Tractable Approach to Coverage and Rate in Cellular NetworksIEEE Transactions on Communications, 2011
- Mobility profiler: A framework for discovering mobility profiles of cell phone usersPervasive and Mobile Computing, 2010
- Mathematical modeling of rayleigh fading channels based on finite state markov chainsIEEE Communications Letters, 2009
- The Random Trip Model: Stability, Stationary Regime, and Perfect SimulationIEEE/ACM Transactions on Networking, 2006
- A general framework to construct stationary mobility models for the simulation of mobile networksIEEE Transactions on Mobile Computing, 2006
- The scaling laws of human travelNature, 2006
- Characterizing and modeling user mobility in a cellular data networkPublished by Association for Computing Machinery (ACM) ,2005
- On Distances in Uniformly Random NetworksIEEE Transactions on Information Theory, 2005
- Realistic individual mobility Markovian models for mobile ad hoc networksPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2004