Hybrid Weighted Multiple Attribute Decision Making Handover Method for Heterogeneous Networks

Authors: Mohanad Alhabo, Li Zhang, Naveed Nawaz

Abstract:

Small cell deployment in 5G networks is a promising technology to enhance the capacity and coverage. However, unplanned deployment may cause high interference levels and high number of unnecessary handovers, which in turn result in an increase in the signalling overhead. To guarantee service continuity, minimize unnecessary handovers and reduce signalling overhead in heterogeneous networks, it is essential to properly model the handover decision problem. In this paper, we model the handover decision problem using Multiple Attribute Decision Making (MADM) method, specifically Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), and propose a hybrid TOPSIS method to control the handover in heterogeneous network. The proposed method adopts a hybrid weighting policy, which is a combination of entropy and standard deviation. A hybrid weighting control parameter is introduced to balance the impact of the standard deviation and entropy weighting on the network selection process and the overall performance. Our proposed method show better performance, in terms of the number of frequent handovers and the mean user throughput, compared to the existing methods.

Keywords: Handover, HetNets, interference, MADM, small cells, TOPSIS, weight.

References:

[1] A. M. Akhtar, X. Wang, and L. Hanzo, “Synergistic spectrum sharing in 5g hetnets: A harmonized sdn-enabled approach,” IEEE Communications Magazine, vol. 54, no. 1, pp. 40–47, 2016.
[2] X. Chu, D. López-Pérez, Y. Yang, and F. Gunnarsson, Heterogeneous Cellular Networks: Theory, Simulation and Deployment. Cambridge University Press, 2013.
[3] G. T. 36.839, “Evolved universal terrestrial radio access (eutra); mobility enhancements in heterogeneous networks,” 2013.
[4] M. Alhabo and L. Zhang, “Unnecessary handover minimization in two-tier heterogeneous networks,” in Wireless On-demand Network Systems and Services (WONS), 2017 13th Annual Conference on. IEEE, 2017, pp. 160–164.
[5] M. Alhabo, L. Zhang, and N. Nawaz, “A trade-off between unnecessary handover and handover failure for heterogeneous networks,” in European Wireless 2017; 23th European Wireless Conference; Proceedings of. VDE, 2017.
[6] M. Alhabo, L. Zhang, and O. Oguejiofor, “Inbound handover interference-based margin for load balancing in heterogeneous networks,” in Wireless Communication Systems (ISWCS), 2017 International Symposium on. IEEE, 2017, pp. 1–6.
[7] N. Nasser, A. Hasswa, and H. Hassanein, “Handoffs in fourth generation heterogeneous networks,” Communications Magazine, IEEE, vol. 44, no. 10, pp. 96–103, 2006.
[8] C.-H. Yeh, “A problem-based selection of multi-attribute decision-making methods,” International Transactions in Operational Research, vol. 9, no. 2, pp. 169–181, 2002.
[9] F. Bari and V. C. Leung, “Automated network selection in a heterogeneous wireless network environment,” IEEE network, vol. 21, no. 1, pp. 34–40, 2007.
[10] B. Bakmaz, Z. Bojkovic, and M. Bakmaz, “Network selection algorithm for heterogeneous wireless environment,” in Personal, Indoor and Mobile Radio Communications, 2007. PIMRC 2007. IEEE 18th International Symposium on. IEEE, 2007, pp. 1–4.
[11] X. Chen, Y. H. Suh, S. W. Kim, and H. Y. Youn, “Reducing connection failure in mobility management for lte hetnet using mcdm algorithm,” in Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD), 2015 16th IEEE/ACIS International Conference on. IEEE, 2015, pp. 1–6.
[12] M. Alhabo and L. Zhang, “Multi-criteria handover using modified weighted topsis methods for heterogeneous networks,” IEEE Access, vol. 6, pp. 40 547–40 558, 2018.
[13] Q. Europe, “Hnb and hnb-macro propagation models,” 3GPP R4–071617, Oct, 2007.
[14] E. U. T. R. Access, “Radio frequency (rf) requirements for lte pico node b,” Release, vol. 9, p. V9, 2012.
[15] G.-H. Tzeng and J.-J. Huang, Multiple attribute decision making: methods and applications. CRC press, 2011.
[16] L. Wang and G.-S. G. Kuo, “Mathematical modeling for network selection in heterogeneous wireless networksU˚ a tutorial,” IEEE Communications Surveys & Tutorials, vol. 15, no. 1, pp. 271–292, 2013.
[17] M. F. Shipley, A. de Korvin, and R. Obid, “A decision making model for multi-attribute problems incorporating uncertainty and bias measures,” Computers & operations research, vol. 18, no. 4, pp. 335–342, 1991.
[18] Y.-M. Wang and Y. Luo, “Integration of correlations with standard deviations for determining attribute weights in multiple attribute decision making,” Mathematical and Computer Modelling, vol. 51, no. 1, pp. 1–12, 2010.
[19] E. U. T. R. Access, “Mobility enhancements in heterogeneous networks,” 3GPP TR 36.839, Tech. Rep., 2012.
[20] D. Lopez-Perez, I. Guvenc, and X. Chu, “Mobility management challenges in 3gpp heterogeneous networks,” IEEE Communications Magazine, vol. 50, no. 12, 2012.
[21] MathWorks, “Counting the floating point operations (flops),” 2015. (Online). Available: https://uk.mathworks.com