QoS Aware Optimal Confederation based Radio Resource Management Scheme for LTE Networks
T. Ganga Prasad1, MSS. Rukmini2
1Mr. T. Ganga Prasad, Research Scholor, Department of ECE, VFSTR, Guntur (Andhra Pradesh), India.
2Mrs. Dr. MSS. Rukmini, Professor, Department of ECE, VFSTR, Vignan University, Guntur (Andhra Pradesh), India.
Manuscript received on 23 November 2019 | Revised Manuscript received on 17 December 2019 | Manuscript Published on 30 December 2019 | PP: 50-54 | Volume-9 Issue-1S5 December 2019 | Retrieval Number: A10141291S52019/19©BEIESP | DOI: 10.35940/ijeat.A1014.1291S519
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: ‘ In this paper proposed for future generation Long Term Evolution (LTE) networks a radio resource management using QoS with aware QOC-RRM method. In QOC-RRM scheme we present the hybrid Recurrent Deep Neural Network (RDNN) technique to differentiate the operators by priority wise based on multiple constraints and it control the allocated resource bybase stations. For routing share queuing criterion data with other schaotic weed optimization (CWO) algorithm are proposed. Once information received each BS schedules the resources for priority user first. The proposed QOC-RRM scheme is implemented in Network Simulator (NS3) tool and performance can better than conventional RRM schemes in terms of minimum date rate requirement, maximum number of active users and utilization of the radio spectrums.
Keywords: Quality of Service, Radio Resource Management, Long Term Evolution, Recurrent Deep Neural Network, Chaotic Weed Optimization.
Scope of the Article: QOS And Resource Management