Performance enhancement of 5G Network using NB-IoT with LTE-M and Novel RASS Algorithm

Abstract

With the fast growth of heterogeneous technology, today’s world is influenced by the Internet of Things (IoT) in immense ways. IoT networks connect resource constrained devices to provide automatic services which require low energy consump tion rates, less memory to store information, better bandwidth rate, high processing speed, and a wide range of coverage to ensure a good Quality of Service (QoS). Recently, energy consumption is becoming increasingly concerned for the large de gree of IoT devices. Therefore, NB-IoT and LTE-M, low-power wide-area networks standardized by 3GPP, are used in 5G technology to cope with the required power. Moreover, another significant concern in the IoT network is resource allocation that guarantees load balancing along with low operational cost and less energy consump tion. In this work, OEA algorithm is used by incorporating appropriate data and parameters for resource allocation in 5G enable NB-IoT and LTE-M networks. We have also proposed a novel algorithm-RASS with Probabilistic Mating, which is used to assign transmissions and powers in an efficient manner. RASS is enabled to generate resource allocation strategies to produce a new optimization model for solving issues faster.This procedure fits the computation requirements, unless that statement is fulfilled, the alteration process goes successfully. This is best explained using methods farther down.