Neuro-fuzzy Architecture for Handover Decision Making in Emerging Heterogeneous Networks
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Abstract
In emerging heterogeneous networks, seamless vertical handover is a critical issue. There must be a trade-off between the handover decision delay and accuracy. This paper’s concern is to contribute to reliable vertical handover decision making that makes a trade-off between complexity and effectiveness. So, the paper proposes a neuro-fuzzy architecture that joints the capacity of learning of the artificial neural networks with the power of linguistic interpretation of the fuzzy logic. The architecture can learn from experience how executing a handover to a particular access network affects the quality of service. Simulation results reveal that this architecture is fast, enhances the overall performance and reliability better than the fuzzy logic-based approach.
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References
T. E. Bogale and L. B. Le, “Massive mimo and mmwave for 5g wireless hetnet: Potential benefits and challenges?”, IEEE Vehicular Technology Magazine, Vol. 11, No. 1, pp. 64-75, 2016.
Aymen Ben Zineb, Mohamed Ayadi, and Sami Tabbane “An Enhanced Vertical Handover Based on Fuzzy Inference MADM Approach for Heterogeneous Networks”, Arab J Sci Eng, King Fahd University of Petroleum & Minerals, 2017. doi:10.1007/s13369-017-2418-1
Xiaohong Li, Feng Liu, Zhiyong Feng, Guangquan Xu, and Zhangjie Fu, “A Novel Optimized Vertical Handover Framework for Seamless Networking Integration in Cyber-Enabled Systems”, Future Generation Computer Systems, 2017. http://dx.doi.org/10.1016/j.future.2017.03.031
S. Liang, Y. Zhang, B. Fan, et al. “Multi-attribute vertical handover decision-making algorithm in a hybrid VLC-femto system”, IEEE Communications Letters, Vol. 21, No. 7, pp. 1521-1524, 2017.
Meenakshi Subramani, and Vinoth Babu Kumaravelu, “A Quality-Aware Fuzzy-Logic-Based Vertical Handover Decision Algorithm for Device to Device Communication”, Arabian Journal for Science and Engineering, King Fahd University of Petroleum & Minerals, 2018. https://doi.org/10.1007/s13369-018-3560-0
A. Sarma, S. Chakraborty, and S. Nandi. “Deciding handover points based on context-aware load balancing in a WiFi-WiMAX heterogeneous network environment”, IEEE Transactions on Vehicular Technology, Vol. 65, No. 1,
pp. 348-357, 2016.
Yuanjie Li, Esha Datta, Jiaxin Ding, Ness Shroff, and Xin Liu, “Bandit Policies for Reliable Cellular Network Handovers in Extreme Mobility”, arXiv:2010.15237v1, 2020.
D. E. Asuquo and F. E. Onuodu, “A fuzzy ahp model for selection of university academic staff”, International Journal of Computer Applications, Vol. 975, pp. 88-87, 2016.
C. W. De Silva, Intelligent control: fuzzy logic applications, CRC press, 2018.
Bi Yuming, Tian Lei, Liu Mengmeng, Liu Zhenzi, and Chen Wei, “Research on joint handoff algorithm in vehicles networks”, Chinese Journal of Engineering, 2016.
Murad Khan, Awais Ahmad, Shehzad Khalid, Syed Hassan Ahmed, Sohail Jabbar, and Jamil Ahmad, “Fuzzy based multi-criteria vertical handover decision modeling in heterogeneous wireless networks”, Multimedia Tools and Applications, Vol. 76, No. 23, pp. 24649-24674, 2017.
Bushra Naeem, Razali Ngah, and Siti Z. Mohd Hashim, “Reduction in ping-pong effect in heterogeneous networks using fuzzy logic”, Soft Computing, Vol. 23, No. 1, pp. 269-283, Springer Nature, 2018. doi:10.1007/s00500-018-3246-2.
Ana G ́omez-Andrades, Pablo Munoz, Inmaculada Serrano, and Raquel Barco, “Automatic root cause analysis for LTE networks based on unsupervised techniques”, IEEE Transactions on Vehicular Technology, Vol. 65, No. 4, pp. 2369-2386, IEEE, 2016.
Wang Zhi, Li Lihua, Xu Yue, Tian Hui, and Cui Shuguang, “Handover Control in Wireless Systems via Asynchronous Multiuser Deep Reinforcement Learning”, IEEE Internet of Things Journal, Vol. 5, No. 6, pp. 4296-4307, IEEE, 2018.
Ali Zoraze, Nicola Baldo, Josep Mangues Bafalluy, and Lorenza Giupponi, “Machine learning based handover management for improved QoE in LTE”, in Proc. NOMS 2016-2016 IEEE/IFIP Network Operations and Management Symposium, pp. 794-798, IEEE, 2016.
Hamid R Berenji, and Pratap Khedkar, “Learning and tuning fuzzy logic controllers through reinforcements”, IEEE Transactions on neural networks, Vol. 3, No. 5, pp. 724-740, IEEE, 1992.
Mahdi H Miraz, Suhail A Molvi, Maaruf Ali, Muzafar A Ganie, AbdelRahman Hussein, “Analysis of QoS of VoIP traffic through WiFi-UMTS networks”, arXiv preprint arXiv:1708.05068, 2017.
Saida Driouache, Najib Naja, and Abdellah Jamali, “Fuzzy Logic Based Intelligent Vertical Handover Decision in Heterogeneous Networks”, in International Conference on Artificial Intelligence & Industrial Applications, pp. 99-109, Springer, 2020.