Handover Prediction and Network Selection using Neuro-Fuzzy Model (HPNS-NF) for 5G-IoT Networks

  • Rashad T.S , A. Ch. Sudhir

Abstract

Generally Handover (HO) prediction in 5th Generation (5G) networks involves classification of large volumes of mobility history over vast time period. This results in higher handover cost and energy consumption. In this paper, a handover prediction and network selection using Neuro-Fuzzy model for 5G-IoT networks is proposed. For performing vertical handover decision, Back Propagation Neural Network (BPNN) is utilized which will determine the user movement depending on the parameters distance, Received Signal Strength (RSS), speed and direction. For performing target network selection Fuzzy logic decision is used with input variables load, handover latency and residual energy. The proposed HPNS-NF model is simulated in NS3. Experimental results show that HPNS-NF model has improved throughput, reduced handoff latency and handoff cost.

Published
2021-11-12
How to Cite
Rashad T.S , A. Ch. Sudhir. (2021). Handover Prediction and Network Selection using Neuro-Fuzzy Model (HPNS-NF) for 5G-IoT Networks. Design Engineering, 11759 - 11775. Retrieved from http://thedesignengineering.com/index.php/DE/article/view/6246
Section
Articles