A Group Teaching Optimization Algorithm for Priority-Based Resource Allocation in Wireless Networks

In wireless networks, resource allocation (RA) is considered as a very important and it is used to enhance the wireless and communication networks performances. D2D (Device-to-device) communication based RA is expressed as a MINLP (mixed integer nonlinear programming) issue. Existing strategies based on RA cannot offer integrative consideration to spectrum efficiency, QoS (Quality of Service) for networks with mixed traffic. When multiple users with various priorities utilize the similar network resource, then it is necessary to utilize the resource on priority basis. In this work, priority based RA is introduced using the GTOA (group teaching optimization algorithm) by combining spectrum resources from unlicensed and licensed spectrum bands to the D2D users in the mixed traffic scenarios. The GTOA optimization framework maximizes all the D2D pair’s utility functions by reducing the whole energy utilization. The network contains the two types of users such as QoS services and BE (best effort) services. Along with several traffics, the function of utility is described for users. The priorities are assigned to the QoS services by the developed GTOA based RA mechanism for performing the resource allotment. As related to other current approaches, the GTOA procedure devours lessor complexity. For the real-time traffic, the developed GTOA can spontaneously assurance the QoS constraint and also owing to the utility function the developed GTOA system create the balance among fairness and throughput for BE traffic users. As a result, by executing RA, the resources and a user can be deliberated. The priority based RA is performed using MATLAB. Simulation outcomes show that the developed GTOA is most appropriate for the priority based RA to the D2D users in the mixed traffic scenarios.