The purpose of this paper is to provide a high-level overview of the most important non-orthogonal multiple access (NOMA) protocols in 5G and 6G networks that incorporate code division within the context of 3GPP standardization. The article’s objective is also to look into and compare the various strategies that have been proposed as a solution to the issue of resource distribution to achieve high performance. Many different NOMA plans for 5G and 6G systems have been suggested by a multitude of businesses. NOMA is currently developing in two primary directions: one of them is with power division, and the other is with code division. During the process of standardization carried out by the 3GPP, the attention of the developers was concentrated in the second direction for the application of NOMA schemes in 5G and 6G systems. Hardware communication, also known as D2D communication, performs a significant role in the process of communication between devices. This will increase the efficiency with which network resources are utilized. Devices are now able to interact directly with one another, avoiding the need for transmission nodes. It also serves as one of the approaches to the problem of limited network coverage, which can be improved by utilizing D2D, and as a result fees and energy can be reduced. Increasing the size of the network is one way to achieve this goal, the explained of NOMA technology as well as its primary benefits in wireless technology. The most common variants of code division NOMA and the characteristics of those variants are discussed, as well as the opportunities and challenges associated with implementing those variants. NOMA protocols allow continuous expansion of wireless communication networks, i.e., 5G and 6G, which leads to enhanced performance of the networks.

The exponential development of wireless applications has increased problems in the spectrum. The unlicensed frequency spectrum is becoming highly saturated, in order to support the conditions of new radio devices with increasing data rates. The spectrum that has previously been allocated is also unused. As a consequence of these developments, scientists have been putting a lot of effort into developing an approach to the issue of the limited spectrum that could make it possible to create a more effective utilization of it. As cognitive radio permits opportunistic use of the licensed spectrum in less crowded areas, it has been proposed as a solution to this challenge. This paper provides an overview of the cognitive radio environment, including a dynamic spectrum access strategy, as well as additional information on the cognitive capabilities operating in combination IoT communication technologies. We investigate the utilization of cognitive radio in the Internet of Things along with the significant role that cognitive radio plays in making the Internet of Things possible. Cognitive radio will provide a comprehensive examination of spectrum sensing, which will cover the many types of sensing, sensing that is based on machine learning, as well as open topics that still need to be addressed further in this sector. This research paper is written in a way that provides detailed instructions for the purpose of assisting new researchers in the area of Cognitive Radio Networks.

The article discusses how Kudryashov's proposed self-phase modulation scheme and nonlinear chromatic dispersion cause the evolution of quiescent optical solitons in magneto-optic waveguides. Provide a comprehensive understanding of the governing model; generalised temporal evolution is considered. The modified sub-ODE approach is employed to facilitate the recovery of such solitons. This leads to a complete range of optical solitons and the necessary conditions that must be met for these solitons to exist, which are also provided.

The problem of utilizing machine learning in cyber security is complicated to resolve it. The explanation for this is not straightforward because developments in the sector have led to the opening so many opportunities. That is difficult to select the ones that are the greatest and most effective for making decisions and putting them into action. In addition, intruders can utilize technology of this kind to launch attacks against computer systems. The purpose of this research is to investigate the application of machine learning in the context of cyber defense and cyber-attacks. In addition, present a model of an attack driven by machine learning.