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Coverage Probability Analysis of D2D Communication Based on Stochastic Geometry Model

Conference paper
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Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 571)

Abstract

Relaying is a common application of D2D communication, which optimizes system capacity and increases the coverage of mobile cellular networks on shared downlink resources. We established a network model of cellular base-stations and adopted the theory of stochastic geometry. Based on the model, the coverage probability analysis of the network is analyzed to select a specific user as the relay node, and the relay point uses the forwarding strategy of the decoding and forwarding. Subsequently, D2D communication can help the edge user to communicate with the base-station. The coverage probability expression of the downlink cellular network is defined, then the coverage probability of the cellular link, the base-station to the relay link, and the relay to the edge user link are derived. Simulation results show that with the increasing of density of the macro base-stations, the coverage probability of the whole network will increase and the final coverage probability will become saturated.

Keywords

Stochastic geometry Relay D2D communication Coverage probability 

Notes

Acknowledgements

This work was supported by High and New Technology Project of Hainan Province Key R. & D. Plan (ZDYF2018012) and the National Natural Science Foundation of China (No. 61661018). Hui Li is the corresponding author.

References

  1. 1.
    Wyner AD (1975) The wiretap channel. Bell Labs Tech J 54(8):1355–1387CrossRefGoogle Scholar
  2. 2.
    Somekh O, Zaidel B, Shamai S (2007) Sum rate characterization of joint multiple cell-site processing. IEEE Trans Inf Theory 53(12):4473–4497MathSciNetCrossRefGoogle Scholar
  3. 3.
    Jing S, Tse DNC, Soriaga JB et al (2008) Multicell downlink capacity with coordinated processing. EURASIP J Wireless Commun Netw: 586878Google Scholar
  4. 4.
    ElSawy H, Hossain E, Haenggi M (2013) Stochastic geometry for modeling, analysis and design of multi-tier and cognitive cellular wireless networks: a survey. IEEE Commun Surv Tutorials 15(3):996–1019CrossRefGoogle Scholar
  5. 5.
    Haenggi M, Andrews J, Baccelli F et al (2009) Stochastic geometry and random graphs for the analysis and design of wireless networks. IEEE J Sel Areas Commun 27(7):1029–1046CrossRefGoogle Scholar
  6. 6.
    Lee CH, Shih CY, Chen YS (2013) Stochastic geometry based models for modeling cellular networks in urban aeas. Wireless Netw 19(6):1063–1072CrossRefGoogle Scholar
  7. 7.
    Ganti RK, Bacelli F, Andrews JG (2011) A new way of computing rate in cellular networks. In: IEEE international conference communications (ICC), June 2011Google Scholar
  8. 8.
    Andrews JG, Baccelli F, Ganti RK (2011) A tractable approach stochastic geometry for wireless networks coverage and rate in cellular networks. IEEE Trans Commun 59(11):3122–3134CrossRefGoogle Scholar
  9. 9.
    Universal Mobile Telecommunications System (UMTS), Selection procedures for the choice of radio transmission technologies of the UMTS, UMTS 30.03, version 3.2.0Google Scholar
  10. 10.
    Guidelines for evaluation of radio interface technologies for IMT-advanced, report ITU-R M.2135Google Scholar
  11. 11.
    Fodor G et al (2012) Design aspects of network assisted device-to-device communications. IEEE Commun Mag 50(3):170–177CrossRefGoogle Scholar
  12. 12.
    Peng T, Lu Q, Wang H, Xu S, Wang W (2009) Interference avoidance mechanisms in the hybrid cellular and device-to-device systems. In: Proceedings of IEEE international symposium on personal indoor and mobile radio communications, pp 617–621Google Scholar
  13. 13.
    Al-Hourani A, Kandeepan S, Jammalipour A (2016) Stochastic geometry study on device-to-device communication as a disaster relief solution. IEEE Trans Veh Technol 65(5):3005–3017CrossRefGoogle Scholar
  14. 14.
    Yu H, Li Y, Xu X, Wang J (2014) Energy harvesting relay-assisted cellular networks based on stochastic geometry approach. In: 2014 international conference on intelligent green building and smart grid (IGBSG), Taipei, pp 1–6Google Scholar
  15. 15.
    Stoyan D, Kendall WS, Mecke J et al (1995) Stochastic geometry and its application, Chichester. Wiley Chichester, UKzbMATHGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.College of Information Science and TechnologyHainan UniversityHaikouChina
  2. 2.Engineering Research Center of Marine Communication and Network in Hainan ProvinceHaikouChina

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