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Performance Analysis of Cognitive Clustered M2M Random Networks with Joint User and Machine Device Selection

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posted on 2019-07-24, 13:44 authored by Mohammed A. M. Abdullah, Zaid Abdullah, Gaojie Chen, Jie Tang, Jonathon Chambers
In this paper, a machine-to-machine (M2M) communication system is proposed with joint M2M and cellular user equipment (CUE) device selection schemes to decrease the outage probability of the system. The machine devices and CUEs are positioned randomly according to a binomial point process (BPP), and two novel ordering metrics are proposed for the joint selection scheme: one based on the locations of the M2M devices and the other based on instantaneous channel gains. The simulation results confirm that the proposed selection scheme attains a significant reduction in the outage probability for M2M networks while limiting the interference to the base station (BS) by a delimited threshold. A hybrid-duplex BS is employed to switch between a half-duplex (HD) and a full-duplex (FD) to attain the best performance corresponding to various levels of residual self-interference. The closed-form formulas of the outage probability are derived for each of these ordering policies corresponding to different path loss exponents, and the analytical results are verified through Monte Carlo simulations. The proposed model and its related analysis is given in this paper lead the way for further work in the 5G Internet of Things (IoT) area.

Funding

Funding Agency: 10.13039/501100000266-Engineering and Physical Sciences Research Council;

History

Citation

IEEE Access, 2019, 7, pp. 83515-83525

Author affiliation

/Organisation/COLLEGE OF SCIENCE AND ENGINEERING/Department of Engineering

Version

  • VoR (Version of Record)

Published in

IEEE Access

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

eissn

2169-3536

Copyright date

2019

Available date

2019-07-24

Publisher version

https://ieeexplore.ieee.org/document/8744201

Language

en

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