Intelligent Radio Resource Scheduling for LTE-Advanced using Wavelet Neural Network
Hashim Ali1, Santosh Pawar2, Manish Sharma3

1Hashim Ali, Electronics and Communication, Dr. A. P. J. Abdul Kalam University , Indore, India.
2Santosh Pawar, Electronics and Communication, Dr. A.P. J. Abdul Kalam University, Indore, India.
3Manish Sharma, Electronics and Telecommunication, D Y Patil College of Engineering, Pune, India. 

Manuscript received on 1August 2019. | Revised Manuscript received on 9 August 2019. | Manuscript published on 30 September 2019. | PP: 3063-3070 | Volume-8 Issue-3 September 2019 | Retrieval Number: C4866098319/2019©BEIESP | DOI: 10.35940/ijrte.C4866.098319

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Abstract: 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.
Keywords: LTE-A, Wavelet Neural Network, Scheduling Rule, TTI.

Scope of the Article:
Petroleum and Mineral Resources Engineering