Reconfigurable intelligent surfaces (RIS), a device made of low-cost meta-surfaces that can reflect or refract the signals in the desired manner, have the immense ability to enhance the data transmission from the sender to the receiver. The concept of RIS is inspired by a smart radio environment or programmable radio environment. The introduction of this device in wireless communications aids in reducing the hardware requirements, energy consumption, and signal processing complexity. The integration of this device with various emerging technologies such as multiple-input multiple-output (MIMO) systems, non-orthogonal multiple access (NOMA) technique, physical layer security, etc., has increased its potentiality in terms of performance enhancement. One such integration could be studied, i.e. RIS-assisted unmanned aerial vehicles (UAVs). The UAVs exhibit aiding capability in various services to our society such as real-time data collection, traffic monitoring, military operations & surveillance, medical assistance, and goods delivery. Despite the positive appeal, the UAV has its limitations such as fuel efficacy, environment disturbances, limited network capability, etc. Considering these scenarios, the RIS can provide assistance to UAVs to enhance their performance when integrated. There is a limited number of articles and researches that consider UAV-assisted RIS systems. This article provides a detailed survey on RIS-assisted UAV systems considering multiple contexts such as optimization, communication techniques, deep reinforcement learning, secrecy performance, efficiency enhancement, and the internet of things. Finally, we draw attention to the open challenges and possible future directions of UAV-assisted RIS systems in phase shifting, channel modeling, energy efficacy, and federated learning.

In conventional cognitive radio (CR), the users in secondary network (SN) can only access the idle spectrum when users in primary network (PN) are absent. This novel strategy provides higher spectrum efficiency when detecting the presence of the PN. Hence, spectrum utilization of the traditional scheme can be further improved as exploiting application of non-orthogonal multiple access (NOMA). As combination of CR and NOMA, such CR-NOMA has been proposed to improve spectrum efficiency to adapt to requirements in 5G communications. In this study, the relaying scheme is employed in the SN of the proposed CR-NOMA and the relay is allowed to energy harvesting (EH) from the secondary transmitter to serve signal forwarding to distant secondary users. With this regard, the complex model of EH-assisted CR-NOMA is explored in outage behavior and throughput performance as awareness on imperfect successive interference cancellation (SIC) at the receiver. As most important results, the exact closed-form of the exact outage probability is derived for each NOMA destination by assuming that the channel coefficients among considered links follow Rayleigh distribution. Furthermore, performance gap between two NOMA users can be controlled by various parameters such as transmit power, energy harvesting coefficients and levels of imperfect SIC. Simulation results verify our analytical results.

Unmanned underwater vehicles (UUVs) are becoming increasingly important for a variety of applications, including ocean exploration, mine detection, and military surveillance. This paper aims to provide a comprehensive examination of the technologies that enable the operation of UUVs. We begin by introducing various types of unmanned vehicles capable of functioning in diverse environments. Subsequently, we delve into the underlying technologies necessary for unmanned vehicles operating in underwater environments. These technologies encompass communication, propulsion, dive systems, control systems, sensing, localization, energy resources, and supply. We also address general technical approaches and research contributions within this domain. Furthermore, we present a comprehensive overview of related work, survey methodologies employed, research inquiries, statistical trends, relevant keywords, and supporting articles that substantiate both broad and specific assertions. Expanding on this, we provide a detailed and coherent explanation of the operational framework of UUVs and their corresponding supporting technologies, with an emphasis on technical descriptions. We then evaluate the existing gaps in the performance of supporting technologies and explore the recent challenges associated with implementing the Thorp model for the distribution of shared resources, specifically in communication and energy domains. We also address the joint design of operations involving unmanned surface vehicles (USVs), unmanned aerial vehicles (UAVs), and UUVs, which necessitate collaborative research endeavors to accomplish mission objectives. This analysis highlights the need for future research efforts in these areas. Finally, we outline several critical research questions that warrant exploration in future studies.

The future of wireless communications looks exciting with the potential new use cases and challenging requirements of future 6th generation (6G) wireless networks. Since the traditional wireless communications, the propagation medium has been perceived as a randomly behaving entity between the transmitter and the receiver, which degrades the quality of the received signal due to the uncontrollable interactions of the transmitted radio waves with the surrounding objects. The recent advent of reconfigurable intelligent surfaces (RIS) in wireless communications enables, on the other hand, network operators to control the radio waves (the scattering, reflection, and refraction characteristics) to eliminate the negative effects of natural wireless propagation. Recent results have revealed that non-orthogonal multiple access (NOMA) benefits from RIS mechanism which can effectively provide effective transmissions. Motivated by the potential of these emerging technologies, we study the impact of hardware impairment in RIS-aided NOMA system in term of performance metrics. We then derive analytical expressions of outage probability and throughput as main performance metrics. Simulations are conducted to validate the analytical expressions. We find that the number of meta-surfaces in RIS, transmit power at the base station, power allocation factors play important role to demonstrate improvement in system performance of RIS relying on NOMA compared with orthogonal multiple access (OMA). Numerical results are presented to validate the effectiveness of the proposed RIS-aided NOMA transmission strategies.

The fifth generation achieved tremendous success, which brings high hopes for the next generation, as evidenced by the sixth generation (6G) key performance indicators, which include ultra-reliable low latency communication (URLLC), extremely high data rate, high energy and spectral efficiency, ultra-dense connectivity, integrated sensing and communication, and secure communication. Emerging technologies such as intelligent reflecting surface (IRS), unmanned aerial vehicles (UAVs), non-orthogonal multiple access (NOMA), and others have the ability to provide communications for massive users, high overhead, and computational complexity. This will address concerns over the outrageous 6G requirements. However, optimizing system functionality with these new technologies was found to be hard for conventional mathematical solutions. Therefore, using the ML algorithm and its derivatives could be the right solution. The present study aims to offer a thorough and organized overview of the various machine learning (ML), deep learning (DL), and reinforcement learning (RL) algorithms concerning the emerging 6G technologies. This study is motivated by the fact that there is a lack of research on the significance of these algorithms in this specific context. This study examines the potential of ML algorithms and their derivatives in optimizing emerging technologies to align with the visions and requirements of the 6G network. It is crucial in ushering in a new era of communication marked by substantial advancements and requires grand improvement. This study highlights potential challenges for wireless communications in 6G networks and suggests insights into possible ML algorithms and their derivatives as possible solutions. Finally, the survey concludes that integrating Ml algorithms and emerging technologies will play a vital role in developing 6G networks.

To apply cyber-physical system (CPS) technique in industrial internet, a wireless technology that is able to robustly maintain hyperconnectivity between a data center and distributed user entities and/or industrial Internet of Things devices is required. We investigate the feasibility of utilizing massive multiple-input multiple-output (MIMO) as such a wireless technology. We analyze the performance of a massive MIMO base station deployed at a data center to provide massive connectivity to a large number of devices. In addition, we discuss related research challenges for deploying massive MIMO in industrial internet applications of CPS, such as device scheduling and power control, energy efficient design and radio frequency energy transfer/harvesting, signaling techniques for drones and mobile robots, and applications of underwater industrial internet.