Open AccessIntelligent Radio Resource Scheduling for LTE-Advanced using Wavelet Neural Network
Author(s) -
Hashim Ali*,
Santosh Pawar,
Manish Sharma
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.c4866.098319
Subject(s) - computer science , scheduling (production processes) , artificial neural network , wavelet , dynamic priority scheduling , distributed computing , real time computing , computer network , artificial intelligence , engineering , quality of service , operations management
This paper presents a novel technique for the efficient resource scheduling for Long Term Evaluation Advanced downlink transmission using wavelet neural network. The dynamism and the uncertainty in the resource scheduling due to the large scale of the network has been taken care through wavelet neural network. The proposed neural network based approach is trained to provide the best scheduling rule at every transmission time interval. Due to the superior estimation capability and better dynamic characteristics than conventional neural network, wavelet neural network offers a better radio resource scheduling. The objective of the proposed scheme is to enhance the system throughput, spectral efficiency and the system capacity. The simulation analysis is performed to verify the effectiveness of the theoretical development.