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Non-orthogonal multiple access (NOMA) scheme is emerging as a favourable multiple access scheme for future 5G networks. Compared to orthogonal multiple access techniques, NOMA provides spectral efficiency, user fairness, better connectivity, enhanced data rate and reduced latency. Thus, NOMA can be a suitable multiple access technique for 5G networks. On the other hand, in wireless networks, cooperation is a well-recognized proven technique for performance enhancement. Cooperative networks offer multiple desirable advantages, including high performance, reliability and greater coverage area. It is believed that in future 5G systems, many existing wireless technologies will be combined with new technologies. Power domain-NOMA (PD-NOMA) has features that can provide opportunities of improved performance and better spectral utilization for downlink cooperative networks. Recently, research works of incorporating PD-NOMA in cooperative networks have gained attention of researchers around the globe. This article surveys the recent research trends in PD-NOMA based cooperative network by reviewing related recent research on performance analysis of cooperative PD-NOMA systems, resources allocation, and impact of relay selection. Additionally, this review article discusses the performance of cooperative PD-NOMA networks when they are integrated with other 5G technologies including cognitive radio, full duplex radio and wireless energy harvesting. Furthermore, some unaddressed issues are highlighted for future research in this area. [ABSTRACT FROM AUTHOR]

In cognitive radio (CR), cooperative spectrum sensing (CSS) has been extensively explored to be accounted for in a spectrum scanning method that permits secondary users (SUs) or cognitive radio users to utilize discovered spectrum holes caused by the absence of primary users (PUs). This paper focuses on optimality of analytical study on the common soft decision fusion (SDF) CSS based on different iterative algorithms which confirm low total probability of error and high probability of detection in detail. In fact, all steps of genetic algorithm (GA), particle swarm optimization (PSO), and imperialistic competitive algorithm (ICA) will be well mentioned in detail and investigated on cognitive radio cooperative spectrum sensing (CRCSS) method. Then, the performance of CRCSS employing GA-, PSO-, and ICA-based scheme is analysed in MATLAB simulation to show superiority of these schemes over other conventional schemes in terms of detection and error performance with very less complexity. In addition, the ICA-based scheme also reveals noticeable convergence and time running performance in comparison to other techniques. [ABSTRACT FROM AUTHOR]

Spectrum scarcity is a major challenge in wireless communications systems requiring efficient usage and utilization. Cognitive radio network (CRN) is found as a promising technique to solve this problem of spectrum scarcity. It allows licensed and unlicensed users to share the same licensed spectrum band. Interference resulting from cognitive radios (CRs) has undesirable effects on quality of service (QoS) of both licensed and unlicensed systems where it causes degradation in received signal-to-noise ratio (SIR) of users. Power control is one of the most important techniques that can be used to mitigate interference and guarantee QoS in both systems. In this paper, we develop a new approach of a distributed power control for CRN based on utility and pricing. QoS of CR user is presented as a utility function via pricing and a distributed power control as a non-cooperative game in which users maximize their net utility (utility-price). We define the price as a real function of transmit power to increase pricing charge of the farthest CR users. We prove that the power control game proposed in this study has Nash Equilibrium as well as it is unique. The obtained results show that the proposed power control algorithm based on a new utility function has a significant reduction in transmit power consumption and high improvement in speed of convergence. [ABSTRACT FROM AUTHOR]

Interference resulting from Cognitive Radios (CRs) is the most important aspect of cognitive radio networks that leads to degradation in Quality of Service (QoS) in both primary and CR systems. Power control is one of the efficient techniques that can be used to reduce interference and satisfy the Signal-to-Interference Ratio (SIR) constraint among CRs. This paper proposes a new distributed power control algorithm based on game theory approach in cognitive radio networks. The proposal focuses on the channel status of cognitive radio users to improve system performance. A new cost function for SIR-based power control via a sigmoid weighting factor is introduced. The existence of Nash Equilibrium and convergence of the algorithm are also proved. The advantage of the proposed algorithm is the possibility to utilize and implement it in a distributed manner. Simulation results show considerable savings on Nash Equilibrium power compared to relevant algorithms while reduction in achieved SIR is insignificant. [ABSTRACT FROM AUTHOR]