Open AccessPredictive Algorithm for Handover Decisions between LTE and LTE-A Networks
Author(s) -
Wafa Benaatou,
Adnane Latif,
Vicent Pla
Publication year - 2021
Publication title -
journal of telecommunications and the digital economy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.202
H-Index - 6
ISSN - 2203-1693
DOI - 10.18080/jtde.v9n4.370
Subject(s) - handover , computer science , mean squared error , base station , particle swarm optimization , real time computing , network packet , adaptive neuro fuzzy inference system , artificial neural network , algorithm , computer network , simulation , fuzzy logic , artificial intelligence , fuzzy control system , statistics , mathematics
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.