ABSTRACT
With the growth and expeditious advancement of IoT (Internet of Things), millions of devices are able to connect to the Internet. Therefore some important applications like smart cities, smart transportation, and smart healthcare have been made possible. In this context a need is felt to derive traditional IOT to cognitive IOT (CIOT), which may support automatic network operation, smart resource allocations, and intelligent servicing provisioning. In this chapter we have proposed a bio-inspired genetic algorithm (GA) to improve the spectral efficiency of a multiuser network to meet the requirements in CIOT. The natural process of biological evolution has paved way for GA, which is a search algorithm. In order to produce better individuals in the genetic algorithm, basic optimization procedure entails processing highly fit individuals as the search advances has been exploited in the proposed technique. Moreover, an attempt has been made toward improvement of spectral efficiency by increasing the number of users and employing cognitive radio (CR) sensing algorithm to sense the free slots in the channel. Further, it has been observed that GA and CR algorithms improve the channel capacity of the network. A new technique has also been proposed to improve the quality of excellence (QOE) in 5G networks using GA and cognitive concepts. The results have been presented in the form of various plots and graphs.
