Arabian Journal for Science and Engineering

, Volume 44, Issue 3, pp 2413–2425 | Cite as

A Quality-Aware Fuzzy-Logic-Based Vertical Handover Decision Algorithm for Device-to-Device Communication

  • Meenakshi Subramani
  • Vinoth Babu KumaraveluEmail author
Research Article - Electrical Engineering


Device-to-device (D2D) communication is expected to play a significant role in the fifth-generation (5G) networks. To support seamless mobility and service continuity, the device(s) undergoing D2D communication should be handed over to the best access network among all the available wireless access networks. A seamless vertical handover (VHO) across the heterogeneous wireless networks is the key enabling solution for achieving the seamless service continuity and mobility. The VHO algorithm should be intelligent, and the decisions should also consider the quality requirements other than the conventional received signal strength (RSS). In this work, a two-stage fuzzy-logic-based VHO decision algorithm is developed to select suitable access network based on the quality-of-service requirements. The quality parameters like data rate and latency are given as the fuzzy inputs along with RSS. The resource availability check is also carried out for the target network, which makes the decision more intelligent. The simulation results show that the proposed scheme offers better performance than the traditional multi-attribute decision-making schemes.


Access network selection Device-to-device (D2D) communication Fuzzy logic Quality of service (QoS) Seamless mobility Vertical handover (VHO) 


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  1. 1.
    Gupta, A.; Jha, R.K.: A survey of 5G network: architecture and emerging technologies. IEEE Access 3, 1206–1232 (2015)CrossRefGoogle Scholar
  2. 2.
    Shah, S.T.; Hasan, S.F.; Seet, B.C.; Chong, P.H.J.; Chung, M.Y.: Device-to-device communications: a contemporary survey. Wirel Pers. Commun. 98, 1247–1284 (2018)CrossRefGoogle Scholar
  3. 3.
    Gandotra, P.; Jha, R.K.: Device-to-device communication in cellular networks: a survey. J. Netw. Comput. Appl. 71, 99–117 (2016)CrossRefGoogle Scholar
  4. 4.
    Thumthawatworn, T.; Tillapart, P.; Santiprabhob, P.: Adaptive multi-fuzzy engines for handover decision in heterogeneous wireless networks. Wirel. Pers. Commun. 93(4), 1005–1026 (2017)CrossRefGoogle Scholar
  5. 5.
    Zineb, A.B.; Ayadi, M.; Tabbane, S.: An enhanced vertical handover based on fuzzy inference MADM approach for heterogeneous networks. Arab. J. Sci. Eng. 42(8), 3263–3274 (2017)CrossRefGoogle Scholar
  6. 6.
    He, D.; Chi, C.; Chan, S.; Chen, C.; Bu, J.; Yin, M.: A simple and robust vertical handoff algorithm for heterogeneous wireless mobile networks. Wirel. Pers. Commun. 59(2), 361–373 (2011)CrossRefGoogle Scholar
  7. 7.
    Nasser, N.; Hasswa, A.; Hassanein, H.: Handoffs in fourth generation heterogeneous networks. IEEE Commun. Mag. 44(10), 96–103 (2006)CrossRefGoogle Scholar
  8. 8.
    Obayiuwana, E.; Falowo, O.E.: Network selection in heterogeneous wireless networks using multi-criteria decision-making algorithms: a review. Wirel. Netw. 23(8), 2617–2649 (2017)CrossRefGoogle Scholar
  9. 9.
    Maaloul, S.; Afif, M.; Tabbane, S.: Context awareness and class of service satisfaction for modeling handover decision-making. Int. J. Comput. Appl. 47(20), 6–15 (2012)Google Scholar
  10. 10.
    Savitha, K.; Chandrasekar, C.: Vertical handover decision schemes using SAW and WPM for network selection in heterogeneous wireless networks (2011). arXiv preprint arXiv:1109.4490
  11. 11.
    Biswas, S.A.; Datta, S.; Bhaumik, S.; Majumdar, G.: Application of VIKOR Based Taguchi Method for Multi Response Optimization: a case study in submerged arc welding (SAW). In: Proceedings of the International Conference on Mechanical Engineering, pp. 26–28 (2009)Google Scholar
  12. 12.
    Drissi, M.; Oumsis, M.; Aboutajdine, D.: A multi-criteria decision framework for network selection over LTE and WLAN. Eng. Appl. Artif. Intell. 66, 113–127 (2017)CrossRefGoogle Scholar
  13. 13.
    Yager, R.R.; Zadeh, L.A. (eds.): An Introduction to Fuzzy Logic Applications in Intelligent Systems, vol. 165. Springer, San Diego (2012)Google Scholar
  14. 14.
    Abdullah, R.M.; Zukarnain, Z.A.: Enhanced handover decision algorithm in heterogeneous wireless network. Sensors 17(7), 16–26 (2017)CrossRefGoogle Scholar
  15. 15.
    Xia, L.; Jiang, L.G.; He, C.: A novel fuzzy logic vertical handoff algorithm with aid of differential prediction and pre-decision method. In: IEEE International Conference on Communications, pp. 5665–5670 (2007)Google Scholar
  16. 16.
    Nasser, N.; Guizani, S.; Al-Masri, E.: Middleware vertical handoff manager: a neural network-based solution. In: IEEE International Conference on Communications, pp. 5671–5676 (2007)Google Scholar
  17. 17.
    Pahlavan, K.; Krishnamurthy, P.; Hatami, A.; Ylianttila, M.; Makela, J.P.; Pichna, R.; Vallstron, J.: Handoff in hybrid mobile data networks. IEEE Pers. Commun. 7(2), 34–47 (2000)CrossRefGoogle Scholar
  18. 18.
    Bari, F.; Leung, V.: Multi-attribute network selection by iterative TOPSIS for heterogeneous wireless access. In: IEEE Consumer Communications and Networking Conference, pp. 808–812 (2007)Google Scholar
  19. 19.
    Kwong, C.F.; Chuah, T.C.; Tan, S.W.; Akbari-Moghanjoughi, A.: An adaptive fuzzy handover triggering approach for long-term evolution network. Expert Syst. 33(1), 30–45 (2016)CrossRefGoogle Scholar
  20. 20.
    Kantubukta, V.; Maheshwari, S.; Mahapatra, S.; Kumar, C.S.: Energy and quality of service aware FUZZY-technique for order preference by similarity to ideal solution based vertical handover decision algorithm for heterogeneous wireless networks. IET Netw. 2(3), 103–114 (2013)CrossRefGoogle Scholar
  21. 21.
    Chinnappan, A.; Balasubramanian, R.: Complexityconsistency trade-off in multi-attribute decision making for vertical handover in heterogeneous wireless networks. IET Netw. 5(1), 13–21 (2016)CrossRefGoogle Scholar
  22. 22.
    Iancu, I.: A Mamdani type fuzzy logic controller. In: Fuzzy Logic-Controls, Concepts, Theories and Applications. InTech, Romania (2012)Google Scholar
  23. 23.
    Arthi, M.; Arulmozhivarman, P.: Power-aware fuzzy based joint base station and relay station deployment scheme for green radio communication. Sustain. Comput. Inform. Syst. 13, 1–14 (2017)Google Scholar
  24. 24.
    Nkansah-Gyekye, Y.: An intelligent vertical handoff decision algorithm in next generation wireless networks. Ph.D. dissertation, University of the Western Cape (2010)Google Scholar
  25. 25.
    Eshanta, C.M.; Ismail, M.; Jumari, K.; Yahaya, P.: VHO strategy for QoS-provisioning in the WiMAX/VVLAN interworking system. Asian J. Appl. Sci. 2(6), 511–20 (2009)CrossRefGoogle Scholar
  26. 26.
    Yan, X.; Mani, N.; Sekercioglu, Y.A.: A traveling distance prediction based method to minimize unnecessary handovers from cellular networks to WLANs. IEEE Commun. Lett. 12(1), 4–16 (2008)CrossRefGoogle Scholar
  27. 27.
    Mohanty, S.; Akyildiz, I.F.: A cross-layer (layer 2+3) handoff management protocol for next-generation wireless systems. IEEE Trans. Mob. Comput. 5(10), 1347–1360 (2006)CrossRefGoogle Scholar
  28. 28.
    Arthi, M.; Arulmozhivarman, P.: Fuzzy logic based coverage and cost effective placement of serving nodes for 4G and beyond cellular networks. Wirel. Commun. Mob. Comput. (2016) (in press) Google Scholar
  29. 29.
    Arthi, M.; Arulmozhivarman, P.: A flexible and cost-effective heterogeneous network deployment scheme for beyond 4G. Arab. J. Sci. Eng. 41(12), 5093–5109 (2016)CrossRefGoogle Scholar
  30. 30.
    Wang, S.S.; Lien, C.Y.; Liao, W.H.; Shih, P.: LASER: a load-aware spectral-efficient routing metric for path selection in IEEE 802.16 j multi-hop relay networks. Comput. Electr. Eng. 38(4), 953–962 (2012)CrossRefGoogle Scholar
  31. 31.
    Amali, C.; Mathew, B.; Ramachandran, B.: Intelligent network selection using fuzzy logic for 4G wireless networks. Int. J. Electron. Commun. Eng. Technol. 2(2), 451–461 (2013)Google Scholar
  32. 32.
    Yuan, Y.: LTE-a relay scenarios and evaluation methodology. In: LTE-Advanced Relay Technology and Standardization, pp. 9–38 (2013)Google Scholar
  33. 33.
    Srinivasan, R.: Draft IEEE 802.16 m evaluation methodology. IEEE 802.16 m-07/037r2 (2007)Google Scholar
  34. 34.
    Andrade, C.B.; Hoefel, R.P.F.: IEEE 802.11 WLANs: a comparison on indoor coverage models. In: 23rd Canadian Conference on Electrical and Computer Engineering, pp. 1–6 (2010)Google Scholar
  35. 35.
    Skoutas, D.N.; Skianis, C.: Enhancing the high speed downlink packet access operation of 3G WCDMA systems. Wirel. Commun. Mob. Comput. 14(1), 115–127 (2014)CrossRefGoogle Scholar
  36. 36.
    3GPP TR 25.942 V9.0.0.: Technical specification group radio access networks. Radio frequency (RF) system scenarios (Release 9), (2009–2012).Google Scholar
  37. 37.
    Mawjoud, S.A.: Path loss propagation model prediction for GSM network planning. Int. J. Comput. Appl. 84(7) (2013)Google Scholar

Copyright information

© King Fahd University of Petroleum & Minerals 2018

Authors and Affiliations

  1. 1.School of Electronics EngineeringVellore Institute of TechnologyVelloreIndia

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