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In this paper, the authors aim to design analog beam forming weight vector for two user down link non-orthogonal multiple access (NOMA) scenario. Millimeter wave (mm-wave) channel with one line-of-sight (LOS) path and multiple non line-of-sight (NLOS) paths is considered. The components of beamforming vector vary only in phase whereas their magnitudes are same. This restriction guarantees that power amplifiers need not be designed with different power amplification factors, thereby minimizing the complexity of power amplifier design. In this work, two users located at different angle of departure (AoD) with different gains are considered. The weight vector is designed aiming to minimize the total power requirement. Simulation results show that the proposed approach requires less power with minimum complexity compared with the time division multiple access (TDMA) for the same spectral efficiency requirements.

There still exist some open research issues in context of the implementation of NOMA enabled UAV networks.

Recently, machine learning has been extensively applied in various areas including wireless communications. The more recent work has shown the power of deep learning in physical layer communications (Qin et al., IEEE Wireless Commun 26:93–99, 2019) and resource allocation (Ye et al., IEEE Veh Technol Mag 13:94–101, 2018). In this chapter, we will discuss the adaptive NOMA enabled by artificial intelligence AI and the new application of NOMA in the unmanned aerial vehicle (UAV) networks, with the goal to provide a potential solution to realize UAV networks with NOMA.

In this chapter, the sustainability of NOMA will be discussed by talking about cooperative NOMA and wireless powered NOMA networks. Particularly, the average performance of wireless powered NOMA will be presented in detail as an example.

In this chapter, the security of NOMA will be demonstrating by introducing average performance of physical layer security (PLS).

In this chapter, the compatibility of NOMA will be introduced by discussing the applications of NOMA to various techniques, such as heterogeneous networks (HetNets), cognitive radio networks (CRNs), and multiple-input multiple-output (MIMO). Particularly, the average performance of NOMA enabled HetNets will be provided as an example.

This chapter is to conclude the book and also provide discussions for promising future research directions. Particularly, in this book, various important topics about multiple access techniques, including the fundamental limits of these multiple access techniques and their applications to practical communication systems, have been discussed. Since multiple access techniques for 5G wireless networks and beyond are still emerging research topics, there are still plenty of open problems. In particular, it is not clear how these multiple access techniques can be efficiently used together with conventional multiple access techniques, advanced physical layer technologies, as well as other communication systems other than cellular networks, and these challenges will be discussed in detail in this chapter.

In this paper, we study the secrecy capacity of the proposed transmission scheme. It is provided that the SNR at the selected best relay, destination and eavesdropper are same due to the symmetrical setup. The outage probability is considered here to evaluate the performance of such a secrecy communication system. Then the system will be extended into outdated channel state information (CSI) scenarios. The correlation coefficients between the actual and outdated channel will influence the system performance. The closed-form expressions of the achievable outage probability will be derived to demonstrate the performance of the proposed secure transmission scheme, and numerical results are presented.

The availability of more realistic road conditions and dynamics provides sound ground to study the issues of Vehicular ad-hoc Network (VANET). In this chapter a new heterogeneous traffic flow based mathematical model is presented, to gain the time and space dynamics of vehicles. To achieve more accurate and realistic data about road conditions, microscopic parameters of varying safety distance between the vehicles and vehicular length are considered in the model. The density dynamics under different road scenarios are calculated under the influence of these constraints with the use of a defined mathematical model. The model is able to capture the impact of road constraints such as traffic lights and road incidents, on the traffic flow. The concept of Vehicular Ad-hoc Networks (VANET) has given mankind opportunities for secure and safe journeys on the roads. VANET is defined as a subclass of Mobile Ad-hoc Networks which holds the characteristics of ad-hoc networks. However due to the dynamic road conditions, traffic flow theory concepts, mobility constraints, human behaviours and vehicular characteristics VANET exhibits different dynamics. These factors have strong influences on the VANET architecture from physical to application layers. This highlights different areas of interest in VANET for researchers to investigate. This study aims to capture the impact of traffic flow theory constraints on the vehicular density under the heterogeneous traffic flow on the road. The microscopic and macroscopic characteristics of vehicles moving on the roads are utilized for the improvement of VANET connectivity dynamics.