ABSTRACT
With the growth in global network users over the last several decades, the different Internet of Things (IoT) technologies and applications have seen strong demand. The IoT has improved thanks to ongoing technological advancements, including machine learning (ML), 5G, Industry 4.0, and edge computing. Since IoT-centric concepts and applications need a lot of bandwidth, low latency, larger data rates, high throughput, and more capacity, this chapter examines such topics in detail. The study will also pay attention to how the IoT has advanced the world and, as a result, offers seamless communication across HetNets. To enhance channel efficiency and spectrum efficiency in addition to random access flexibility, NOMA integration operates on space domains that have been added to the physical domains, like the power domains and code. On the other hand, the environmentally dependent traffic model and high application present a barrier to the creation of effective algorithms for huge connections in IoT. The advancements in ML have led to a new approach to solving this issue. The third topic covered in this chapter is ML techniques to deliver effective IoT connections. Wireless networking devices may now send data because of cutting-edge ML algorithms. This chapter also looks into the underlying challenges affecting the implementation of 5G IoT due to the high-data rates which require both IoT devices-based edge computing and cloud-based platforms. The chapter ends with a review of the current limitations of IoT in future networking fields and research areas.
