Deep learning has strong potential using data-driven solutions to improve the performance of cyber physical systems (CPS) in utilizing limited spectrum resources in wireless communications. Deep learning is also a powerful method of data exploration to learn about “normal” and “abnormal” behavior according to how CPS components and devices interact with each other. Furthermore, deep learning methods

Part 1 of this two-part column presented potential radio technologies for 6G. In Part 2, we focus on potential systems and networking technology areas for 6G. Paradigm shifts in the areas of protocol stack support for extreme applications, sub-networks of devices, distributed computing, AI/ML in networks and devices, semantic communications, seamless mobility, and enhanced application frameworks are

On April 21, 2022, the U.S. national spectrum regulator for the private sector, the Federal Communications Commission/FCC, formally asked for input on the issue of “the role of receiver performance in (its) spectrum management responsibilities” [1]. A previous issue of this column addressed related issues and the enigmatic question “Which uses the most spectrum: transmitters or receivers?” [2]. That

The proliferation of industrial cyber physical systems (CPSs) is changing our lives. CPS applications are often associated with sensitive data, core infrastructures, and assets, making them attractive in terms of vulnerability, data breach, and denial of services. Moreover, the heterogeneity in terms of protocols, operating systems, and devices combined with poor adoption of standard solutions create

With the development of wireless communication, cyber physical system (CPS) technologies are being applied to various fields, and people's daily lives are more dependent on CPS. As CPS brings convenience to people's lives, danger also arises. The most serious of these is attacks on CPS. Attackers obtain information without the user's permission. The main transmission medium used by attackers is the

An essential consideration in cyber-physical systems (CPS) is the ability to support secure communication services, such as points of interest (POI) microservices. Existing approaches to support secure POI microservices generally rely on anonymity and/or differential privacy technologies. There are, however, a number of known limitations with such approaches. Hence, this work presents a deep-federated-learning-based

Various smart meter data aggregation protocols have been developed in the literature to address the rising privacy threats against customers' energy consumption data. However, most of these protocols require a smart meter (installed at the consumer's end) to either maintain a secret key or to run an authenticated key establishment scheme for interacting with the aggregator. Both of these approaches

Malicious attacks in wireless cyber-physical systems have become more frequent in recent years. With the development of attack methods used by attackers, security in wireless cyber-physical systems needs to progress to match various attacks. Deep learning is a field that has developed rapidly in recent years, and generative adversarial network (GAN) is a deep learning model that has shown promising

In 6G wireless communication scenarios, the ultra-dense network (UDN) scenario has received extensive attention, as it is an inevitable case of 6G networks. How to keep users safe while providing universal service to a number of users is becoming a crucial topic of UDN. To battle this issue, we propose a distributed Q-learning-enabled multi-dimensional spectrum sharing security scheme for the millimeter-wave

The 6G wireless network is expected to drive cyber-physical systems (CPS) from merely connected things to securely connected intelligence. While 6G will offer real-time communication between cyber and physical entities, due to convergence of operational technology (OT) and information technology (IT) networks, security, and trustworthiness of the massive amount of data shared between cyber and physical

With the rapid development of the Internet of Things, a large number of mobile devices participate in the perception and aggregation of data, outsourcing and storing massive data on various cloud platforms. Thus, a new data perception and privacy protection model based on mobile group intelligence perception and cloud computing is required. The existing work on data security and privacy protection

With the outbreak of COVID-19, people are experiencing increasing physical and mental health issues. Therefore, personal daily healthcare and monitoring become vital for our physical and mental well being. As a combination of the Internet of Things (IoT) and healthcare services, the Internet of Medical Things (IoMT) has emerged to provide intelligent medical services. However, privacy and security

With the advances in 5G and IoT devices, industries are vastly adopting artificial intelligence (AI) techniques for improving classification and prediction-based services. However, the use of AI also raises concerns regarding data privacy and security that can be misused or leaked. Private AI was recently coined to address the data security issue by combining AI with encryption techniques, but existing

Cloud-edge-end collaboration enables harmonious and efficient resource allocation for the Power Internet of Things (PIoT). However, the security and complexity issues of computation offloading evolve into the main obstacles. In this article, we first propose a blockchain and AI-based secure cloud-edge-end collaboration PIoT (BASE-PIoT) architecture to ensure data security and intelligent computation

In the radio access network (RAN) infrastructure, fronthaul links territorially disperse remote units (RUs) to distributed units (DUs) in regular or open RAN. With the fifth generation (5G) rollout worldwide and the active research on technologies beyond 5G, fronthaul has become a critical part of RAN to balance throughput, delay, reliability, and security. Based on a group of Tier 1 operators' insights

While the idea of wavelength-division multiplex passive optical network (WDM-PON) has been around for many years, it has never been taken up in a significant way, mostly due to a lack of demand for its level of bandwidth. Fifth generation (5G) wireless has brought with it new centralized architectures that seem to require very-high-performance fixed networks. This article considers the use of WDM-PON

With the increasing wireless data and massive interconnections in B5G/6G, demands for an intelligent, flexible, and cost-effective fronthaul network have emerged to provide services for a ubiquitous mobile society. This calls for disruptive innovations in both the architecture and transmission technology. In this article, we introduce a point-to-multipoint coherent architecture as a promising solution

Wireless networks have been evolving at a frenetic pace to meet the ever increasing demands for higher capacity, lower latency, and massive number of connections. In the fifth generation (5G) radio access networks (RANS), millimeter-wave and higher band radio are instrumental in achieving such stringent requirements. The network deployment must go through significant densification to meet the extremely

During the development of 5G, much emphasis was placed on the core network and access enhancement. Slowly, the 5G fronthaul is also getting the attention it deserves to bring the entire network to the 5G world. Virtualization of network functions as well as architectural enhancement to the 5G RAN has made it necessary to re-examine the security aspect of the fronthaul. This article analyzes the security

The fifth generation (5G) communication network has been developed rapidly in the past few years, which provides substantial bandwidth capacities and higher quality of service (QoS). 5G technology commercialization includes mobile edge computing and communication technologies. The increasing deployment of mobile edge computing empowered 5G infrastructures facilitates further intelligent data processing

Next-generation systems aim to increase both the speed and responsiveness of wireless communications while supporting compelling applications such as edge-cloud computing, remote health, vehicle-to-infrastructure communications, etc. As these applications are expected to carry confidential personal data, ensuring user privacy becomes a critical issue. In contrast to traditional security and privacy

This article focuses on the exploitation of reconfigurable intelligent surfaces (RISs) in multiuser networks employing orthogonal multiple access (OMA) or non-orthogonal multiple access (NOMA), with an emphasis on investigating the interplay between NOMA and RIS. Depending on whether the RIS reflection coefficients can be adjusted only once or multiple times during one transmission, we distinguish

Multi-access edge computing (MEC) is an emerging paradigm that pushes resources for sensing, communications, computing, storage, and intelligence to the premises closer to the end users (i.e., the edge) so that they can leverage the nearby rich resources to improve their quality of experience. Due to the growing emerging applications targeted at intelligentizing life-sustaining cyber-physical systems

In 5G and beyond, newly emerging services, such as edge computing/intelligence services, may demand the provisioning of heterogeneous communications, computing, and storage (CCS) resources on and across network entities multiple hops apart. In such cases, traditional resource-oriented auction schemes, where buyers place bids on resources, may not be effective in providing end-to-end (E2E) quality of

Current maritime communications mainly rely on satellites having meager transmission resources, hence suffering from poorer performance than modern terrestrial wireless networks. With the growth of transcontinental air traffic, the promising concept of aeronautical ad-hoc networking relying on commercial passenger airplanes is potentially capable of enhancing satellite-based maritime communications

The Internet of Things (IoT) contains enormous computing resources. How to fully and efficiently use computing power is a very important research issue. This article proposes an active computing (AC) concept toward IoT. AC achieves the computing power integration by the means of actively pulling computing tasks; then a network is established with the provisioning of computing power as the core. Not

Visible light communication is a well-known emerging technology that enables high data rate wireless access in indoor environments by making dual-us e of light-emitting diode luminaires for providing lighting and communication. Managing multiple access and addressing the user's mobility are among the current challenges of this technology. To manage multiple access interference arising from unintended

The fifth generation (5G) wireless systems have been begun to be widely deployed over the world in recent years. As the 5G technology will not be able to meet the demands of the huge data traffic growth from massively interconnected devices that is forecasted for future years, the attention of the research community is shifting toward what will be the next innovations in wireless communication architectures

The industry is on the cusp of yet another G transition in the cellular technology roadmap. This is a good time to pause and assess where we are and where we go next. 3G/4G/5G technologies have paved the way for data communications to a point where the wireless communications pipe is highly capable of very high data rates, relatively low latency, and high reliability. While it is expected that these

Most wireless technology researchers view obtaining access to spectrum as a specialty for others who focus solely in spectrum policy. Thus, the researcher finds out from others what bands are available for their application. In many cases, the question of whether band x can be used for application $y$ ultimately depends on whether this application in this band will cause interference to other users

While 5G research is maturing toward a global standard, the focus has now shifted toward the development of beyond 5G solutions. Wireless data traffic is estimated to reach 4394 EB by 2030 (Source: International Telecommunication Union), and the number of connected devices might surge beyond 50 billion. 5G will be unable to provide adequate support for various applications that depend on this huge

Space-air-ground integrated communication networks and artificial intelligence (AI) play critical roles in future 6G wireless communication. The Power Internet of Things (PIoT) assisted by the space-air-ground integrated communication network, that is, space-air-ground integrated PIoT (SAG-PIoT), has emerged as a promising solution to provide seamless communication and computing services for PIoT devices

The integration of terrestrial and satellite multibeam systems has been regarded as a potential scheme for future communication networks aiming at high-rate, wide-coverage, and low-latency services. Relying on its ubiquitous coverage, integrated terrestrial and satellite multibeam systems (ITSMSs) will play a crucial role in the forthcoming 6G to increase coverage in unserved areas and support more

The huge number of Internet of Things (IoT) devices and sudden data packets make the process of wireless resource management in 6G networks very difficult. The design of a 6G network often needs to rely on the co-simulation of multiple technologies to complete. To solve this issue, this article proposes a novel wireless resource management technique specifically for 6G-network-enabled high-density

Feature applications envisioned in the 6G era, represented by holographic communication, full-sensing communication, intelligent transportation, and intelligent manufacturing in terms of virtual and physical integration, immersion, contextualization, and personalization, have placed high demands on the intelligentization of 6G networks. The current network operating mechanism based on rule-based algorithms

Visible light communication (VLC) technology was introduced as a key enabler for the next generation of wireless networks, mainly thanks to its simple and low-cost implementation. However, several challenges prohibit the realization of the full potential of VLC, namely, limited modulation bandwidth, ambient light interference, optical diffuse reflection effects, devices' nonlinearity, and random receiver

With the increasing number of commercial 5G deployments, research on beyond 5G (B5G) and 6G has started in earnest. Although it is too early to clearly identify what 6G systems will look like or how they will be designed, it is certain that 6G systems will support novel use cases with challenging key performance indicators (KPIs), which will be empowered by new enabling technologies and network architectures

With the development of the next generation of mobile networks, new research challenges have emerged, and new technologies have been proposed to face them. On one hand, the reconfigurable intelligent surface (RIS) technology is being investigated for partially controlling the wireless channels. RIS is a promising technology for improving the signal quality by controlling the propagation of the electromagnetic

Driven by the ever increasing penetration and proliferation of data-driven applications, a new generation of wireless communication, the sixth generation (6G) mobile system enhanced by artificial intelligence, has attracted substantial research interests. Among various candidate technologies of 6G, low Earth orbit (LEO) satellites have appealing characteristics of ubiquitous wireless access. However

6G systems are expected to serve a massive number of extremely heterogeneous network slices that cross multiple technological domains (i.e., RAN, edge, cloud, and core), posing significant challenges to classical centralized management and orchestration approaches in terms of scalability and sustainability. Within this context, a distributed and intelligent management and orchestration system is mandatory

Network slicing is a much discussed topic in fifth generation (5G) and beyond (B5G) networks. The network slice feature differentiates 5G and B5G networks from the earlier generations since it replaces the conventional concept of quality of service (QoS) with end-to-end multi-service provisioning and multi-tenancy. A diverse set of resources for computing, networking, storage, and power need to be

With the global rollout of fifth generation (5G) networks, it is necessary to look beyond 5G and envision 6G networks. 6G networks are expected to have space-air-ground integrated networks, advanced network virtualization, and ubiquitous intelligence. This article presents an artificial intelligence (AI)-native network slicing architecture for 6G networks to enable the synergy of AI and network slicing

For the goals of beyond 5G and 6G networks, it is essential to maintain access everywhere and offer low latency with high reliability. To achieve such goals, satellite networks are an instrumental technology that grants network coverage even in remote areas without ground infrastructure and provides an offloading option when ground networks are too crowded with workload. However, for an efficient implementation

Network slicing is expected to be critical in the deployment of 5G mobile networks and systems. On top of a single physical infrastructure, the technology enables operators to operate several virtual networks. As the 5G commercialization was recently deployed, network function virtualization (NFV) and software-defined networking (SDN) will drive network slicing. In this article, we present an overview

Network slicing is a promising approach supporting various Internet of Everything applications with diverse and differential requirements. To implement flexible and efficient network slices, unmanned aerial vehicle (UAV)-enabled mobile edge computing (MEC) is deployed to leverage aerial and ground segments, which provides multi-dimensional resources involving various hardware devices and facilities

The arrival of the 5G era brings unprecedented opportunities and challenges to vehicular networks. As one of the most innovative and important technologies of 5G, network slicing can separate the physical substrate network into multiple logical networks, and meet the requirements of various vehicle services simultaneously. Therefore, its superiority in vehicular networks has attracted extensive attention

With the proliferation of wireless applications, the electromagnetic (EM) space is becoming more and more crowded and complex. This makes it a challenging task to accommodate the growing number of radio systems with limited radio resources. In this article, by considering the EM space as a radio ecosystem, and leveraging the analogy to the natural ecosystem in biology, a novel symbiotic communication

Improving learning efficiency is paramount for learning resource allocation with deep neural networks (DNNs) in wireless communications over highly dynamic environments. Incorporating domain knowledge into learning is a promising approach to dealing with this issue. It is also an emerging topic in the wireless community. In this article, we briefly summarize two approaches for using domain knowledge:

Opening-up sharing has prompted the multi-tenancy architecture, whereby different vendors (including outsourcees) work together with network operators to form a vibrant service ecosystem, resulting in several advantages as well as risks. In particular, the static nature of existing architectures in network functions virtualization-based (NFV-based) clouds facilitate hacking. Thus, much attention has

Intelligent reflecting surfaces (IRSs) have been introduced into wireless communications systems due to their great potential to smartly customize and reconfigure radio propagation environments in a cost-effective manner. Despite the promising advantages of IRSs, academic research on IRSs is still in its infancy. In particular, the design and analysis of IRS-assisted wireless communication systems

In 2021, IEEE Wireless Communications has made tremendous achievements again thanks to the great contributions of readers, authors, reviewers, editors, and the publications staff. In 2021, we published nine special issues and feature topics, with special topics on full duplex communications, edge intelligence, e-health applications, IoT applications, aerial computing, AI-assisted wireless communications

The ambition of providing ubiquitous, fast, and mobile communication services to all types of devices, such as handheld, vehicular and IoT, has resulted in tremendous complexity in our wireless networks, and the trend is only likely to accelerate. As a result, it is becoming exponentially harder to create good analytical models to describe the behavior of systems. Even if models exist, they are complex

As 5G rollout is underway in many countries, R&D is also underway on its successor 6G and along with deliberations in International Telecommunication Union – Radiocommunication Standardization Sector (ITU-R) Working Party 5D (WP 5D) [1]. 6G will likely use both the existing approximately 50 5G frequency bands that range from 617 MHz to 48.2 GHz, not all of which are available in every country, as well

The global economy is experiencing significant business growth leading to increasing demands for energy. Global energy consumption increased by 2.1 percent in 2017, and according to the 2019 U.S. Energy Information Administration (EIA) reports, the expected energy growth in Asia will reach 50 percent by 2050. Since it is unlikely that these demands will be met using conventional energy systems, the

Wireless networks (e.g., 5G networks) enable distributed energy infrastructures to be connected even when they are geometrically isolated. Intelligent monitoring from remote sites therefore becomes possible, allowing decision makers to examine the status of distributed energy infrastructures from a central location. The major challenge is when local devices cannot perform the monitoring independently;

Network trustworthiness is a critical component of network security, as it builds on positive inter-actions, guarantees, transparency, and accountability. And with the growth of smart city services and applications, trustworthiness is becoming more important. Most current network trustworthiness solutions are insufficient, particularly for critical infrastructures where end devices are vulnerable and

The exponential growth of distributed energy resources is enabling the transformation of traditional consumers in the smart grid into prosumers. This transition presents a promising opportunity for sustainable energy trading. However, the integration of prosumers in the energy market imposes new considerations in designing unified and sustainable frameworks for efficient use of the power and communication

The provision of communication services via portable and mobile devices, such as aerial base stations, is a crucial concept to be realized in 5G/6G networks. Conventionally, IoT/edge devices need to transmit data directly to the base station for training the model using machine learning techniques. The data transmission introduces privacy issues that might lead to security concerns and monetary losses

Many countries and organizations have proposed smart city projects to address the exponential growth of the population by promoting and developing a new paradigm for maximizing electricity demand in cities. Since Internet of Things (IoT)-based systems are extensively used in smart cities where huge amounts of data are generated and distributed, it could be challenging to directly capture data from

Advances in artificial intelligence (AI) techniques have offered great opportunities for the optimization of sustainable energy systems. AI techniques rely on the collection of big data, and thus it is necessary to design a fast and reliable communication network to support the need. This article studies the 6G network design based on the intelligent reflective surface (IRS) to realize an extraordinary