Throughput Enhancement of Multicarrier Cognitive M2M Networks Using NOMA Techniques

Abstract

The use of cellular networks will be increasing in the future technological world owing to the growth of a vast number of applications. Fifth generation (5G) of mobile communication systems is developed to become an all-encompassing solution to fundamentally every broadband wireless communication need of the current decade. One of the most prominent applications using the 5G system is the Internet of Things (IoT) which places a completely new set of demands on the 5G networks. Machine to machine (M2M) communications is one of the promising applications for the future technological world to realize IOT in future 5th generation networks, which can drive to new job opportunities in different fields such as healthcare, intelligent transport systems, vehicular, smart grids, environmental monitoring, smart houses, building automation, etc. M2M systems must meet many challenges due to the massive number of devices participating, the small amount of transmitted data, transmissions in dynamic environments and architectures, high data traffic and quality of service (QoS) demands for example bandwidth, scalability, coverage, lifetime, and latency. Numerous cellular and non-cellular wireless technologies such as general packet radio service (GPRS), long-term evolution (LTE), LTE-advanced (LTE-A), Wi-Fi, Zigbee, Bluetooth, etc. are considered for M2M communications. But they are insufficient to sustain