Performance Analysis of the Network Selection Algorithms in ‌5G Heterogeneous Wireless Networks

Document Type : Original Article

Authors

Faculty of Electrical and Computer Engineering, University of Shiraz, Shiraz, Iran

Abstract

Vertical handover is the essential feature of the next generation heterogeneous wireless networks. Network selection among accessible candidates is the most critical step in vertical handover procedure. Although various algorithms for network selection have been proposed, due to different approaches and diversity of parameters corresponding to this complicated problem, no unified benchmark or global indicator exists to evaluate the performances. In this paper, we define a global performance indicator (GPI) which comprehensively considers all subscriber satisfaction factors to assess users’ quality of experience (QoE). Our method is inspired by “Analytic Hierarchical Process” (AHP) and systematically utilizes both customer and network side parameters. This idea was led to propose a novel “automatic context-aware network selection” (ACANS) algorithm. ACANS is a “network-assisted”, “user centric” approach which dynamically and automatically affects customer context in the decision of the best network. A practical simulation platform evaluates and compares ACANS to well-known network selection algorithms such as SAW (Simple Additive Weighting), MEW (Multiplicative Exponential Weighting), TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and TRUST (TRigger-based aUtomatic Subjective weighTing). Simulation results show that the proposed algorithm is compatible to customer preference and has superior performance in “No. of handovers”, “user’s volume of download”, “consumed energy” and “service cost”.

Keywords


[1]      António Morgado et al., “A survey of 5G technologies: regulatory, standardization and industrial perspectives, “Elsevier Digital Communications and Networks,” Volume 4, Issue 2, pp. 87-97, April 2018.
[2]      W. H. Chin et al., “Emerging technologies and research challenges for 5G wireless networks,” IEEE Wireless Communications, vol.21, no. 2, pp. 106-112, April 2014.
[3]      A. Ahmed, L. M. Boulahia, and D. Ga¨ıti, “Enabling vertical handover decisions in heterogeneous wireless networks: a state-of-the-art and a classification”, IEEE Communications Surveys & Tutorials, vol. 16, no. 2, year 2014.
[4]      L. Wang and G. S. Kuo, “Mathematical modeling for network selection in heterogeneous wireless networks – a tutorial”, IEEE Communications Surveys & Tutorials, vol. 15, no. 1, pp. 271-292, 1st q. 2013.
[5]      Stefano Ferretti, Vittorio Ghini, Fabio Panzieri, “A survey on handover management in mobility architectures,” Elsevier Computer Networks, Volume 94, pp. 390-413, January 2016.
[6]      S. Lee et al., “Vertical handoff decision algorithms for providing optimized performance in heterogeneous wireless networks”, IEEE Transactions on Vehicular Technology, vol. 58, no. 2, pp. 865-881, February 2009.
[7]      Abdullah Gani, Golam Mokatder Nayeem, Muhammad Shiraz, Mehdi Sookhak,  Suleman Khan, “A review on interworking and mobility techniques for seamless connectivity in mobile cloud computing,” Elsevier Journal of Network and Computer Applications, Volume 43, Pages 84-102, August 2014.
[8]      Q. T. Nguyen-Vuong, Y. Ghamri-Doudane and N. Agoulmine, On utility models for access network selection in wireless Heterogeneous networks,” in Proc. IEEE Network Operations and Manage. Symp. (NOMS), pp. 144–151, 2008.
[9]      B. J. Chang and J. F. Chen, “Cross-layer-based adaptive vertical handoff with predictive rss in heterogeneous wireless networks,” IEEE. Trans. Veh. Technol., vol. 57, no. 6, pp. 3679-3692, 2008.
[10]      B. R. Chandavarkar, Ram Mohana Reddy Guddeti, “Simplified and improved multiple attributes alternate ranking method for vertical handover decision in heterogeneous wireless networks,” Elsevier Computer Communications, Volume 83, pp. 81-97, June 2016.
[11]      G. Tamea, M. Biagi and R. Cusani, “Soft multi-criteria decision algorithm for vertical handover in heterogeneous networks,” IEEE Communications Letters, vol. 15, no. 11, NOV. 2011.
[12]      S. Barmpounakis, A. Kaloxylos, P. Spapis and N. Alonistioti, “COmpAasS: a context-aware, user-oriented radio access technology selection mechanism in heterogeneous wireless networks”,Proc. Int. Conf. on Advanced Commun. and Computation (INFOCOMP), Paris, 2014.
[13]      J. Hou and DC. O’Brien, “Vertical handover decision making algorithm using fuzzy logic for the integrated Radio-and-OW system,” IEEE Trans. Wireless Commun., vol. 5, no. 1, pp. 176–185, Jan. 2006.
[14]      M. Cesana, N. Gatti, and I. Malanchini, “Game theoretic analysis of wireless access network selection: models, inefficiency bounds, and algorithms,” in Proc. Int. ICST Workshop on Game Theory in Commun. Net. (Gamecomm), pp. 1–10, Oct. 2008.
[15]      Ehsan Aryafar, Alireza Keshavarz-Haddad et al., “RAT selection games in HetNets,”in Proceedings of IEEE INFOCOM, pp. 998-1006, 2013.
[16]      C. Sun, E. Stevens-Navarro and V. W. S. Wong, “A constrained MDP based vertical handoff decision algorithm for 4G wireless networks,” in Proc. IEEE Int. Conf. Communication. (ICC), pp. 2169–2174, 2008.
[17]      J. Pérez-Romero, O. Sallent, R. Agustí, “A novel metric for context-aware RAT selection in wireless multi-access systems, "Proceedings of IEEE International Conference on Communications, ICC 2007, Glasgow, Scotland, June 2007.
[18]      M. Drissi and M. Oumsis, “Performance evaluation of multi-criteria vertical handover for heterogeneous wireless networks,” in Intelligent Systems and Computer Vision, ISCV 2015.
[19]      L. Wang and D. Binet, “TRUST: a trigger-based automatic subjective weighting method for network selection,” in Proc. Advanced Int. Conf.Telecommun. (AICT), pp. 362–368, 2009.
[20]      A. Mehbodniya et al., “Wireless network access selection scheme for heterogeneous multimedia traffic,” IET Networks, vol. 2, no. 4, pp. 214-223, 2013.
[21]      S. Wang, C. Fan, C. H. Hsu, Q. Sun and F. Yang, “A vertical handoff method via self-selection decision tree for internet of vehicles”, IEEE Systems Journal,  vol. 10, no. 3, pp. 1183-1192, 2016.
[22]      ETSI Standard TS 122.105.V14, Digital cellular telecommunications system (Phase 2+) (GSM), Universal Mobile Telecommunications System (UMTS); LTE Services and service capabilities, 2017.
[23]      T. S. Rappaport, Wireless Communications: Principles and Practice, 2nd Edition, Prentice Hall PTR, 2002.
[24]      Nain, Philippe, et al. "Properties of random direction models," INFOCOM 2005. 24th Annual Joint Conference of the IEEE Computer and Communications Societies, Proceedings IEEE, Vol. 3, 2005.
[25]      A. Habibzadeh, S. Shirvani Moghaddam, S.M. Razavizadeh, and M. Shirvanimoghaddam, “Modeling and Analysis of Traffic-aware Spectrum Handover Schemes in Cognitive HetNets,” Transactions on Emerging Telecommunications Technologies (ETT), Wiley, Vol. 28, No. 12, Dec. 2017.
[26]      A. Habibzadeh, S. Shirvani Moghaddam, M. Razavizadeh, and M. Shirvani Moghaddam, "A Novel Handover Decision-Making Algorithm for HetNets," The 15th IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), Abu Dhabi, UAE, pp. 438-442, December 2015.
[27]      Du. Ding-Zhu, Ko. Ker-I, Theory of Computational Complexity, John Wiley & Sons, 2000.