The sixth-generation (6G) wireless communication network is expected to integrate the terrestrial, aerial, and maritime communications into a robust network which would be more reliable, fast, and can support a massive number of devices with ultra-low latency requirements. The researchers around the globe are proposing cutting edge technologies such as artificial intelligence (AI)/machine learning (ML), quantum communication/quantum machine learning (QML), blockchain, tera-Hertz and millimeter waves communication, tactile Internet, non-orthogonal multiple access (NOMA), small cells communication, fog/edge computing, etc., as the key technologies in the realization of beyond 5G (B5G) and 6G communications. In this article, we provide a detailed overview of the 6G network dimensions with air interface and associated potential technologies. More specifically, we highlight the use cases and applications of the proposed 6G networks in various dimensions. Furthermore, we also discuss the key performance indicators (KPI) for the B5G/6G network, challenges, and future research opportunities in this domain.

The combination of non-orthogonal multiple access (NOMA) and cooperative communications can be a suitable solution for fifth generation (5G) and beyond 5G (B5G) wireless systems with massive connectivity, because it can provide higher spectral efficiency, lower energy consumption, and improved fairness compared to the non-cooperative NOMA. However, the receiver complexity in the conventional cooperative NOMA increases with increasing number of users owing to successive interference cancellation (SIC) at each user. Space time block code-aided cooperative NOMA (STBC-CNOMA) offers less numbers of SIC as compared to that of conventional cooperative NOMA. In this paper, we evaluate the performance of STBC- CNOMA under practical challenges such as imperfect SIC, imperfect timing synchronization between distributed cooperating users, and imperfect channel state information (CSI). We derive closed-form expressions of the received signals in the presence of such realistic impairments and then use them to evaluate outage probability. Further, we provide intuitive insights into the impact of each impairment on the outage performance through asymptotic analysis at high transmit signal-to-noise ratio. We also compare the complexity of STBC-CNOMA with existing cooperative NOMA protocols for a given number of users. In addition, through analysis and simulation, we observe that the impact of the imperfect SIC on the outage performance of STBC-CNOMA is more significant compared to the other two imperfections. Therefore, considering the smaller number of SIC in STBC-CNOMA compared to the other cooperative NOMA protocols, STBC-CNOMA is an effective solution to achieve high reliability for the same SIC imperfection condition.

The next generation of wireless communication systems will integrate terrestrial and nonterrestrial networks, targeting the coverage of the undercovered regions, especially those connected to marine activities. Unmanned aerial vehicle (UAV)-based connectivity solutions offer significant advances to support conventional terrestrial networks. However, the use of UAVs for maritime communication is still an unexplored area of research. Therefore, this article highlights different aspects of UAV-based maritime communication, including the basic architecture, various channel characteristics, and use cases. The article afterward discusses several open research problems, such as mobility management, trajectory optimization, interference management, and beam forming.

The Internet of Things (IoT) is a mesh network of interconnected objects with unique identifiers that can transmit data and communicate with one another without the need for human intervention. The IoT has brought the future closer to us. It has opened up new and vast domains for connecting not only people, but also all kinds of simple objects and phenomena all around us. With billions of heterogeneous devices connected to the Internet, the network architecture must evolve to accommodate the expected increase in data generation while also improving the security and efficiency of connectivity. Traditional IoT architectures are primitive and incapable of extending functionality and productivity to the IoT infrastructure’s desired levels. Software-Defined Networking (SDN) and virtualization are two promising technologies for cost-effectively handling the scale and versatility required for IoT. In this paper, we discussed traditional IoT networks and the need for SDN and Network Function Virtualization (NFV), followed by an analysis of SDN and NFV solutions for implementing IoT in various ways.

Wireless use cases in the industrial Internet of Things networks often require guaranteed data rates ranging from a few kilobits per second to a few gigabits per second. Supporting such a requirement in a single radio access technique is difficult, especially when bandwidth is limited. Although nonorthogonal multiple access (NOMA) can improve the system capacity by simultaneously serving multiple devices, its performance suffers from strong device interference. In this article, we propose a Q-learning-based algorithm for handling many-to-many matching problems, such as bandwidth partitioning, device assignment to sub-bands, interference-aware access mode selection [orthogonal multiple access or NOMA], and power allocation to each device. The learning technique maximizes system throughput and spectral efficiency (SE) while maintaining quality-of-service (QoS) for a maximum number of devices. The simulation results show that the proposed technique can significantly increase overall system throughput and SE while meeting heterogeneous QoS criteria.

The world is moving toward globalization rapidly. Everybody has easy access to information with the spread of Internet technology. Businesses are growing beyond national borders. Internationalization affects every aspect of life. In this scenario, by dispersing functions and tasks across organizational borders, time and space, global organizations have higher requirements for collaboration. In order to allow decision‐makers and knowledge workers, situated at different times and spaces, to work more efficiently, collaborative technologies are needed. In this paper, we give an overview of potential collaborative technologies, their benefits, risks and challenges, types, and elements. Based on the conceptualization of terrestrial and non‐terrestrial integrated networks (TaNTIN), we highlight artificial intelligence (AI), blockchains, tactile Internet, mobile edge computing (MEC)/fog computing, augmented reality and virtual reality, and so forth as the key features to ensure quality‐of‐service (QoS) guarantee of futuristic collaborative services such as telemedicine, E‐education, online gaming, online businesses, the entertainment industry. We also discuss how these technologies will impact human life in the near future.