A Predictive Algorithm for Handover Decisions between LTE and LTE-A Networks

Main Article Content

Wafa Benaatou
Adnane Latif
Vicent Pla


Handover Decision, PSO, ANFIS, Heterogeneous network, Neural networks


A heterogeneous wireless network needs to maintain seamless mobility and service continuity; for this reason, we have proposed an approach based on the combination of particle swarm optimization (PSO) and an adaptive neuro-fuzzy inference system (ANFIS) to forecast a handover during a movement of a mobile terminal from a serving base station to target base station. Additionally, the handover decision is made by considering several parameters, such as peak data rate, latency, packet loss, and power consumption, to select the best network for handover from an LTE to an LTE-A network. The performance efficiency of the new hybrid approach is determined by computing different statistical parameters, such as root mean square error (RMSE), coefficient of determination (R2), mean square error (MSE), and error standard deviation (StD). The execution of the proposed approach has been performed using MATLAB software. The simulation results show that the hybrid PSO-ANFIS model has better performance than other approaches in terms of prediction accuracy and reduction of handover latency and the power consumption in the network.



Download data is not yet available.
Abstract 86 | 370-PDF-v9n4pp110-126 Downloads 8


Aboelezz, Z. A., Nafea, H. B., & Zaki, F. W. (2020). Fuzzy logic design for handover and QoS control in LTE HetNet, International Journal of Scientific and Engineering Research, 11(6), 1–11. https://doi.org/10.1109/JAC-ECC48896.2019.9051126
Benaatou, W., Latif, A., & Pla, V. (2017). Vertical handover decision algorithm in heterogeneous wireless networks, International Journal of Internet Protocol Technology, 10(4), 197–213. https://doi.org/10.1504/IJIPT.2017.10009856
Benaatou, W., Latif, A., & Pla, V. (2019). Applying ANFIS Model in Decision-making of Vertical Handover between Macrocell and Femtocell Integrated Network, Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 11(1), 57–62. Retrieved from https://jtec.utem.edu.my/jtec/article/view/4723
Bin, M., Xiaofeng, L., & Xianzhong, X. (2013). Vertical Handoff Algorithm Based on Type-2 Fuzzy Logic in Heterogeneous Networks, Journal of Software, 8(11). https://doi.org/10.4304/jsw.8.11.2936-2942
Calhan, A., & Ceken, C. (2010). An adaptive neuro-fuzzy based vertical handoff decision algorithm for wireless heterogeneous networks. In: 21st Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, 2271–2276. https://doi.org/10.1109/PIMRC.2010.5671693
Calhan, A., & Ceken, C. (2012). An optimum vertical handoff decision algorithm based on adaptive fuzzy logic and genetic algorithm, Wireless Personal Communications, 64(4), 647–664. https://doi.org/10.1007/s11277-010-0210-6
Chinnappan, A., & Balasubramanian, R. (2016). Complexity consistency trade-off in multi attribute decision making for vertical handover in heterogeneous wireless networks, IET Journals & Magazines, 51, 13–21. https://doi.org/10.1049/iet-net.2015.0042
Davaasambuu, B. (2018). Handover with Buffering for Distributed Mobility Management in Software Defined Mobile Networks. Journal of Telecommunications and the Digital Economy, 6(1), 26–40. https://doi.org/10.18080/jtde.v6n1.137
Devi, R., Jha, R. K., Gupta, A., Jain, S., & Kumar, P. (2017). Implementation of Intrusion Detection System using Adaptive Neuro-Fuzzy Inference System for 5G wireless communication network, AEU - International Journal of Electronics and Communications, 74, 94–106. https://doi.org/10.1016/j.aeue.2017.01.025
Goudarzi, S., Hassan, W. H., Anisi, M. H., Soleymani, A., Sookhak, M., Khan, M. K., Hashim, A.-H. A., & Zareei, M. (2017). ABC-PSO for vertical handover in heterogeneous wireless networks, Neurocomputing. 256, 63–81. https://doi.org/10.1016/j.neucom.2016.08.136
Hashim, H. A., & Abido, M. A. (2019). Location management in LTE networks using multi-objective particle swarm optimization, Computer Networks. 157, 78–88. https://doi.org/10.1016/j.comnet.2019.04.009
Israt, P., Chakma, N., & Hashem, M. M. A. (2009). A Fuzzy Logic Based Adaptive Handoff Management Protocol for Next Generation Wireless Systems, Journal of Networks. 4, 288–293. https://doi.org/10.1109/ICCITECHN.2008.4802978
Jang, J. S. R. (1993). ANFIS: adaptive-network-based fuzzy inference system, IEEE Transactions on Systems, Man and Cybernetics, 23(3), 665–685. https://doi.org/10.1109/21.256541
Kassar, M., Kervella, B., & Pujolle, G. (2008). An overview of vertical handover decision strategies in heterogeneous wireless networks, Computer Communications, 31(10), 2607–2620. https://doi.org/10.1016/j.comcom.2008.01.044
Miyim, A. M., Ismail, M. & Nordin, R. (2014). Vertical Handover Solutions Over LTE-Advanced Wireless Networks: An Overview, Wireless Personal Communications, 77, 3051–3079. https://doi.org/10.1007/s11277-014-1695-1
Patil, M. B., & Patil, R. (2021). Fuzzy Based Network Controlled Vertical Handover Mechanism for Heterogeneous Wireless Network. Materials Today: Proceedings, 1-5. https://doi.org/10.1016/j.matpr.2021.06.364
Sharma, M. (2012). Fuzzy Logic Based Handover Decision System, International Journal of Ad hoc, Sensor & Ubiquitous Computing, 3(4), 21–29. https://doi.org/10.5121/ijasuc.2012.3403
Suleymani, M., & Bemani, A. (2018). Application of ANFIS-PSO algorithm as a novel method for estimation of higher heating value of biomass. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 40(3), 288-293. https://doi.org/10.1080/15567036.2017.1413453
Thumthawatworn, T., Tillapart, P., & Santiprabhob, P. (2017). Adaptive Multi-fuzzy Engines for Handover Decision in Heterogeneous Wireless Networks. Wireless Personal Communications, 93, 1005–1026. https://doi.org/10.1007/s11277-017-3963-3
Wang, N., Shi, W., Fan, S. & Liu, S. (2011). PSO-FNN-based vertical handoff decision algorithm in heterogeneous wireless networks. Procedia Environmental Sciences, 11, 55–62. https://doi.org/10.1016/j.proenv.2011.12.010