Wireless Networks

, Volume 25, Issue 8, pp 4849–4858 | Cite as

Performance analysis of clustered device-to-device networks using matern cluster process

  • Ying Wang
  • Qi ZhuEmail author


This paper presents a new analytical framework for clustered device-to-device (D2D) networks in dense urban scenarios. We model the D2D network as a Matern cluster process (MCP) instead of Poisson point process and Tomas cluster process. MCP modeling can capture both clustered and bounded properties of D2D communications in urban areas. Considering a typical D2D receiver (DR), we assume it receives the content of interest from a D2D transmitter (DT) in the same cluster. Two different choice methods of its serving DT are analyzed: (1) the serving DT is chosen uniformly at random; (2) the serving DT is the closest active DT to the typical DR. Based on this model, distributions of the serving distance and interfering distances of both choice methods are derived through geometric construction and order statistics theory, respectively. With these distance distributions, the coverage and area spectral efficiency (ASE) of the network can be obtained using stochastic geometry. According to the analysis and simulations, we know that ASE of the uniform choice can be maximized by optimizing the average number of simultaneously active DTs per cluster. Meanwhile, ASEs of both choice methods can be maximized by choosing a proper coverage threshold. This paper provides a guideline to the analysis of clustered D2D communications and can be extended to heterogeneous networks.


Device-to-device communication Matern cluster process Stochastic geometry Coverage probability Area spectral efficiency 


  1. 1.
    Golrezaei, N., Molisch, A. F., Dimakis, A. G., & Caire, G. (2013). Femtocaching and device-to-device collaboration: A new architecture for wireless video distribution. IEEE Communications Magazine, 51(4), 96–104.CrossRefGoogle Scholar
  2. 2.
    Doppler, K., Rinne, M., Wijting, C., Ribeiro, C. B., & Hugl, K. (2009). Device-to-device communication as an underlay to LTE-advanced networks. IEEE Communications Magazine, 47(12), 42–49.CrossRefGoogle Scholar
  3. 3.
    Tehrani, M. N., Uysal, M., & Yanikomeroglu, H. (2014). Device-to-device communication in 5G cellular networks: Challenges, solutions, and future directions. IEEE Communications Magazine, 52(5), 86–92.CrossRefGoogle Scholar
  4. 4.
    Liu, J., Kato, N., Ma, J., & Kadowaki, N. (2015). Device-to-device communication in LTE-advanced networks: A survey. IEEE Communications Surveys Tutorials, 17(4), 1923–1940. 4th Quart.Google Scholar
  5. 5.
    Asadi, A., Wang, Q., & Mancuso, V. (2014). A survey on device-to-device communication in cellular networks. IEEE Communications Surveys Tutorials, 16(4), 1801–1819. 4th Quart.Google Scholar
  6. 6.
    Andrews, J. G., Baccelli, F., & Ganti, R. K. (2011). A tractable approach to coverage and rate in cellular networks. IEEE Transactions on Communications, 59(11), 3122–3134.CrossRefGoogle Scholar
  7. 7.
    Peng, M., Li, Y., Quek, T. Q. S., & Wang, C. (2014). Device-to-device underlaid cellular networks under rician fading channels. IEEE Transactions on Wireless Communications, 13(8), 4247–4259.CrossRefGoogle Scholar
  8. 8.
    ElSawy, H., & Hossain, E. (2014). Analytical modeling of mode selection and power control for underlay D2D communication in cellular networks. IEEE Transactions on Communications, 62(11), 4147–4161.CrossRefGoogle Scholar
  9. 9.
    George, G., Mungara, R. K., & Lozano, A. (2015). An analytical framework for device-to-device communication in cellular networks. IEEE Transactions on Wireless Communications, 14(11), 6297–6310.CrossRefGoogle Scholar
  10. 10.
    Lin, X., Andrews, J. G., & Ghosh, A. (2014). Spectrum sharing for device-to-device communication in cellular networks. IEEE Transactions on Wireless Communications, 13(12), 6727–6740.CrossRefGoogle Scholar
  11. 11.
    Joshi, S., & Mallik, R. K. (2017). Analysis of dedicated and shared device-to-device communication in cellular networks over Nakagami-m fading channels. IET Communications, 11(10), 1600–1609.CrossRefGoogle Scholar
  12. 12.
    Jo, H. S., Sang, Y. J., Xia, P., & Andrews, J. G. (2012). Heterogeneous cellular networks with flexible cell association: A Comprehensive Downlink SINR Analysis. IEEE Transactions on Wireless Communications, 11(10), 3484–3495.CrossRefGoogle Scholar
  13. 13.
    Zhou, Y., Zhao, Z., Louët, Y., Ying, Q., Li, R., Zhou, X., et al. (2015). Large-scale spatial distribution identification of base stations in cellular networks. IEEE Access, 3, 2987–2999.CrossRefGoogle Scholar
  14. 14.
    Ganti, R. K., & Haenggi, M. (2009). Interference and outage in clustered wireless ad hoc networks. IEEE Transactions on Information Theory, 55(9), 4067–4086.CrossRefMathSciNetGoogle Scholar
  15. 15.
    Chun, Y. J., Hasna, M. O., & Ghrayeb, A. (2015). Modeling heterogeneous cellular networks interference using poisson cluster processes. IEEE Journal on Selected Areas in Communications, 33(10), 2182–2195.CrossRefGoogle Scholar
  16. 16.
    Afshang, M., Dhillon, H. S., & Chong, P. H. J. (2016). Modeling and performance analysis of clustered device-to-device networks. IEEE Transactions on Wireless Communications, 15(7), 4957–4972.Google Scholar
  17. 17.
    Afshang, M., & Dhillon H. S. (2015). Spatial modeling of device-to-device networks: Poisson cluster process meets Poisson Hole Process. In IEEE Asilomar conference on signals, systems and computers, pp. 317–321.Google Scholar
  18. 18.
    Afshang, M., Dhillon, H. S., & Chong, P. H. J. (2016). Fundamentals of cluster-centric content placement in cache-enabled device-to-device networks. IEEE Transactions on Communications, 64(6), 2511–2526.CrossRefGoogle Scholar
  19. 19.
    Afshang, M., Saha, C., & Dhillon, H. S. (2017). Nearest-Neighbor and contact distance distributions for matern cluster process. IEEE Communications Letters, 21(12), 2686–2689.CrossRefGoogle Scholar
  20. 20.
    Afshang, M., & Dhillon, H. S. (2017). Fundamentals of modeling finite wireless networks using binomial point process. IEEE Transactions on Wireless Communications, 16(5), 3355–3370.CrossRefGoogle Scholar
  21. 21.
    Azimi-Abarghouyi, S. M., Makki, B., Haenggi, M., Nasiri-Kenari, M., & Svensson, T. (2017). Stochastic geometry modeling and analysis of single- and multi-cluster wireless networks.
  22. 22.
    Stoyan, D., Kendall, W. S., & Mecke, J. (1995). Stochastic geometry and its applications (2nd ed.). New York, NY, USA: Wiley.zbMATHGoogle Scholar
  23. 23.
    Guo, J., Durrani, S., Zhou, X., & Yanikomeroglu, H. (2017). Device-to-device communication underlaying a finite cellular network region. IEEE Transactions on Wireless Communications, 16(1), 332–347.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Key Wireless Laboratory of Jiangsu Province, School of Telecommunication and Information EngineeringNanjing University of Posts and TelecommunicationsNanjingChina

Personalised recommendations