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.
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