ed PD-NOMA using AWGN and Rayleigh channels, and then they used ZF to decode the data. Then they developed CD-NOMA, decoding using SCMA and extracting data from users with MPA. Finally, they implemented a realistic transmission scenario in which users were randomly assigned to cells and a downlink network with a single base station servicing a group of users was employed. The system demonstrates that not all pos- sible NOMA users are regarded as NOMA users. Additionally, authors created a downlink PD-NOMA in NOMA users and displayed the BER performance as well as the sum rate of NOMA users. Chapter 6 covers comparisons of UTD-PO and FKE models for path loss prediction over an irregular terrain. In this paper, authors have proposed a comparative study for the path loss prediction of mobile radio waves over an irregular terrain scenario based on a uniform theory of diffraction-physical optics (UTD-PO) and Fresnel-Kirchhoff knife edge diffraction theory (FKE). The comparative results show that when the number of obstacles increases in the terrain between the point of transmission and the points of reception, the predicted path loss of the FKE approach gives inferior results in comparison to the path loss of the measurement data and the predicted path loss of the UTD-PO approach. Also, the data analysis of these approaches shows that the mean error of path loss obtained for the UTD-PO approach is smaller in comparison to the mean error of path loss for the FKE approach. Chapter 7 covers integrated blockchain and MEC systems empowered healthcare services. In this chapter, authors present the possible integration between healthcare IoT devices, MEC, blockchain, and AI as a base for future healthcare systems. Authors also explore the latest state, the shortcomings and the research opportunities of this integration. Chapter 8 covers optimized cognitive radio networks for 5G technology. In this work, authors propose an optimum beamforming design using the genetic algorithm Preface with multi-parent crossover (GA-MPC), and