Improved Radio Resource Allocation in 5G Network Using Fuzzy Logic Systems

With recent advancements in machine-to-machine (M2M), the demand for fastest communication is an utmost concern of the M2M technology. The advent of 5G telecommunication networks enables to bridge the demand on satis-fying the Quality-of-Service (QoS) concerns in M2M communication. The mas-sive number of devices in M2M communication is henceforth do not lie under limited resource allocation by embedding the 5G telecommunication network. In this paper, we address the above limitation of allocation the resource to promi-nent M2M devices using Adaptive Neuro Fuzzy Inference System (ANFIS). In ANFIS, the adoption of rules will imply the resource allocation with the devices of top priority and it reduces based on the priority. The ANFIS controller acts as a central controller that implies the resource allocation with its rules on the M2M devices. The simulation is performed to test the efficacy of fuzzy logic system on allocation 5G resources to M2M model. The results show that the ANFIS mod-el achieves higher level of allocating the resources than other existing methods in terms of reduced network delay, increased throughput, packet delivery rate and energy efficiency.