Showing papers in "IEEE Wireless Communications in 2019"

Cellular-Connected UAV: Potential, Challenges, and Promising Technologies

Abstract: Enabling high-rate, low-latency and ultra-reliable wireless communications between UAVs and their associated ground pilots/users is of paramount importance to realize their large-scale usage in the future. To achieve this goal, cellular- connected UAV, whereby UAVs for various applications are integrated into the cellular network as new aerial users, is a promising technology that has drawn significant attention recently. Compared to conventional cellular communication with terrestrial users, cellular-connected UAV communication possesses substantially different characteristics that present new research challenges as well as opportunities. In this article, we provide an overview of this emerging technology, by first discussing its potential benefits, unique communication and spectrum requirements, as well as new design considerations. We then introduce promising technologies to enable the future generation of 3D heterogeneous wireless networks with coexisting aerial and ground users. Last, we present simulation results to corroborate our discussions and highlight key directions for future research.

UAV-Assisted Emergency Networks in Disasters

Abstract: Reliable and flexible emergency communication is a key challenge for search and rescue in the event of disasters, especially for the case when base stations are no longer functioning. Unmanned aerial vehicle (UAV)-assisted networking is emerging as a promising method to establish emergency networks. In this article, a unified framework for a UAV-assisted emergency network is established in disasters. First, the trajectory and scheduling of UAVs are jointly optimized to provide wireless service to ground devices with surviving BSs. Then the transceiver design of UAV and establishment of multihop ground device-to-device communication are studied to extend the wireless coverage of UAV. In addition, multihop UAV relaying is added to realize information exchange between the disaster areas and outside through optimizing the hovering positions of UAVs. Simulation results are presented to show the effectiveness of these three schemes. Finally, open research issues and challenges are discussed.

Vehicular Fog Computing: Enabling Real-Time Traffic Management for Smart Cities

Abstract: Fog computing extends the facility of cloud computing from the center to edge networks. Although fog computing has the advantages of location awareness and low latency, the rising requirements of ubiquitous connectivity and ultra-low latency challenge real-time traffic management for smart cities. As an integration of fog computing and vehicular networks, vehicular fog computing (VFC) is promising to achieve real-time and location-aware network responses. Since the concept and use case of VFC are in the initial phase, this article first constructs a three-layer VFC model to enable distributed traffic management in order to minimize the response time of citywide events collected and reported by vehicles. Furthermore, the VFC-enabled offloading scheme is formulated as an optimization problem by leveraging moving and parked vehicles as fog nodes. A real-world taxi-trajectory-based performance analysis validates our model. Finally, some research challenges and open issues toward VFC-enabled traffic management are summarized and highlighted.

Deep Learning in Physical Layer Communications

Abstract: DL has shown great potential to revolutionize communication systems. This article provides an overview of the recent advancements in DL-based physical layer communications. DL can improve the performance of each individual block in communication systems or optimize the whole transmitter/receiver. Therefore, we categorize the applications of DL in physical layer communications into systems with and without block structures. For DL-based communication systems with the block structure, we demonstrate the power of DL in signal compression and signal detection. We also discuss the recent endeavors in developing DL-based end-to-end communication systems. Finally, potential research directions are identified to boost intelligent physical layer communications. Introduction

Model-Driven Deep Learning for Physical Layer Communications

Abstract: Intelligent communication is gradually becoming a mainstream direction. As a major branch of machine learning, deep learning (DL) has been applied in physical layer communications and has demonstrated an impressive performance improvement in recent years. However, most existing works related to DL focus on data-driven approaches, which consider the communication system as a black box and train it by using a huge volume of data. Training a network requires sufficient computing resources and extensive time, both of which are rarely found in communication devices. By contrast, model-driven DL approaches combine communication domain knowledge with DL to reduce the demand for computing resources and training time. This article discusses the recent advancements in model-driven DL approaches in physical layer communications, including transmission schemes, receiver design, and channel information recovery. Several open issues for future research are also highlighted.

Broadband LEO Satellite Communications: Architectures and Key Technologies

Abstract: This article aims to provide a comprehensive overview for key issues in broadband LEO satellite communication systems. First of all, the network architecture is introduced, which is the basis of the whole system. The space-based LEO system with ISL, which requires a small number of ground gateways, is the focus. In this system, the satellite constellation design is important with impact on key system performances such as coverage. Two popular LEO constellations, the walker Delta and Star constellations, are introduced. Given satellite constellations, proper beam coverage schemes should be employed at satellites to provide seamless coverage all over the world. A hybrid wide and spot beam coverage scheme is presented, where the LEO provides a wide beam for large area coverage and several steering spot beams for highspeed data access. Moreover, special coverage schemes should be designed in broadband LEO systems for the interference coordination between LEO and GEO. To protect GEO communications, LEO satellites should be turned off if they cause interference to GEO. In this case, to provide services for users covered by the turned-off LEO satellites, a progressive pitch method and a coverage expanding method can be employed. Finally, the coverage performance of LEO is also closely related to resource management schemes. The global resource management for broadband LEO systems is complicated, involving a large amount of data, and a two-level management structure should be employed. Using this structure, an NMC with powerful storage and processing capabilities is employed to carry out the first-level management, making strategies based on all information collected from the whole system. Then satellite base stations with limited capabilities are employed to respond to the strategies generated by NMC in real time.

UAV Communications Based on Non-Orthogonal Multiple Access

Abstract: This article proposes a novel framework for UAV networks with massive access capability supported by NOMA In order to better understand NOMA-enabled UAV networks, three case studies are carried out We first provide performance evaluation of NOMA-enabled UAV networks by adopting stochastic geometry to model the positions of UAVs and ground users Then we investigate the joint trajectory design and power allocation for static NOMA users based on a simplified 2D model of UAV flying around at fixed height As a further advance, we demonstrate the UAV placement issue with the aid of machine learning techniques when the ground users are roaming and the UAVs are capable of adjusting their positions in three dimensions accordingly With these case studies, we can comprehensively understand the UAV systems from fundamental theory to practical implementation

Optimizing Space-Air-Ground Integrated Networks by Artificial Intelligence

Abstract: It is widely acknowledged that the development of traditional terrestrial communication technologies cannot provide all users with fair and high quality services due to scarce network resources and limited coverage areas. To complement the terrestrial connection, especially for users in rural, disaster-stricken, or other difficult-to-serve areas, satellites, UAVs, and balloons have been utilized to relay communication signals. On this basis, SAGINs have been proposed to improve the users' QoE. However, compared with existing networks such as ad hoc networks and cellular networks, SAGINs are much more complex due to the various characteristics of three network segments. To improve the performance of SAGINs, researchers are facing many unprecedented challenges. In this article, we propose the AI technique to optimize SAGINs, as the AI technique has shown its predominant advantages in many applications. We first analyze several main challenges of SAGINs and explain how these problems can be solved by AI. Then, we consider the satellite traffic balance as an example and propose a deep learning based method to improve traffic control performance. Simulation results evaluate that the deep learning technique can be an efficient tool to improve the performance of SAGINs.

Artificial Intelligence Empowered Edge Computing and Caching for Internet of Vehicles

Abstract: Recent advances in edge computing and caching have significant impacts on the developments of vehicular networks. Nevertheless, the heterogeneous requirements of on-vehicle applications and the time variability on popularity of contents bring great challenges for edge servers to efficiently utilize their resources. Moreover, the high mobility of smart vehicles adds substantial complexity in jointly optimizing edge computing and caching. Artificial intelligence (AI) can greatly enhance the cognition and intelligence of vehicular networks and thus assist in optimally allocating resources for problems with diverse, time-variant, and complex features. In this article, we propose a new architecture that can dynamically orchestrate edge computing and caching resources to improve system utility by making full use of AI-based algorithms. Then we formulate a joint edge computing and caching scheme to maximize system utility and develop a novel resource management scheme by exploiting deep reinforcement learning. Numerical results demonstrate the effectiveness of the proposed scheme.

An Overview of Network Slicing for 5G

Abstract: Besides conventional mobile broadband communication service, 5G is envisioned to support various new use cases from vertical industries. These new scenarios bring diverse and challenging requirements, such as a broader range of performance, cost, security protection, and mobility management. The one-size-fits-all design philosophy applied in existing networks is not viable any more. Slicing a single physical network into several logical networks customized to different unique requirements has emerged as a promising approach to fulfill such divergent requirements in a sustainable way. In this article, we provide a comprehensive survey of 5G network slicing. We first present the driving forces and the concept of network slicing. Then related key enabling technologies, including network function virtualization and modularization, dynamic service chaining, management and orchestration are discussed. The latest progress in 3GPP standardization and industry implementation on 5G network slicing is presented. Finally, the article identifies several important open issues and challenges to inspire further study toward a practical network slicing enabled 5G system.

Ultra-Dense LEO: Integration of Satellite Access Networks into 5G and Beyond

Abstract: To support the explosive growth of wireless devices and applications, various access techniques need to be developed for future wireless systems to provide reliable data services in vast areas. With recent significant advances in ultra-dense low Earth orbit (LEO) satellite constellations, satellite access networks (SANs) have shown their significant potential to integrate with 5G and beyond to support ubiquitous global wireless access. In this article, we propose an enabling network architecture for dense LEO-SANs in which the terrestrial and satellite communications are integrated to offer more reliable and flexible access. Through various physical-layer techniques such as effective interference management, diversity techniques, and cognitive radio schemes, the proposed SAN architecture can provide seamless and high-rate wireless links for wireless devices with different quality of service requirements. Three extensive applications and some future research directions in both the physical layer and network layer are then discussed.

Non-Orthogonal Multiple Access: Common Myths and Critical Questions

Abstract: Non-orthogonal multiple access (NOMA) has received tremendous attention for the design of radio access techniques for fifth generation (5G) wireless networks and beyond. The basic concept behind NOMA is to serve more than one user in the same resource block, for example, a time slot, subcarrier, spreading code, or space. With this, NOMA promotes massive connectivity, lowers latency, improves user fairness and spectral efficiency, and increases reliability compared to orthogonal multiple access (OMA) techniques. While NOMA has gained significant attention from the communications community, it has also been subject to several widespread misunderstandings, such as "NOMA is based on allocating higher power to users with worse channel conditions. As such, cell-edge users receive more power in NOMA and due to this biased power allocation toward celledge users inter-cell interference is more severe in NOMA compared to OMA. NOMA also compromises security for spectral efficiency." The above statements are actually false, and this article aims at identifying such common myths about NOMA and clarifying why they are not true. We also pose critical questions that are important for the effective adoption of NOMA in 5G and beyond and identify promising research directions for NOMA, which will require intense investigation in the future.

Massive MIMO in Sub-6 GHz and mmWave: Physical, Practical, and Use-Case Differences

Abstract: The use of base stations (BSs) and access points (APs) with a large number of antennas, called Massive MIMO (multiple-input multiple-output), is a key technology for increasing the capacity of 5G networks and beyond. While originally conceived for conventional sub-6 GHz frequencies, Massive MIMO (mMIMO) is also ideal for frequency bands in the range 30-300 GHz, known as millimeter wave (mmWave). Despite conceptual similarities, the way in which mMIMO can be exploited in these bands is radically different, due to their specific propagation behaviors and hardware characteristics. This article reviews these differences and their implications, while dispelling common misunderstandings. Building on this foundation, we suggest appropriate signal processing schemes and use cases to efficiently exploit mMIMO in both frequency bands.

Spectrum Sharing for Internet of Things: A Survey

Abstract: The Internet of Things (IoT) is a promising paradigm to accommodate massive device connections in 5G and beyond. To pave the way for future IoT, spectrum should be planned in advance. Spectrum sharing is a preferable solution for IoT due to the scarcity of available spectrum resources. In particular, mobile operators are inclined to exploit the existing standards and infrastructures of current cellular networks and deploy IoT within licensed cellular spectrum. However, proprietary companies prefer to deploy IoT within unlicensed spectrum to avoid any license fee. In this article, we provide a survey of prevalent IoT technologies deployed within licensed cellular spectrum and unlicensed spectrum. Emphasis will be on spectrum sharing solutions, including shared spectrum, interference model, and interference management. To this end, we discuss both advantages and disadvantages of different IoT technologies. Finally, we identify challenges for future IoT and suggest potential research directions.

Machine Learning for Wireless Connectivity and Security of Cellular-Connected UAVs

Abstract: Cellular-connected UAVs will inevitably be integrated into future cellular networks as new aerial mobile users. Providing cellular connectivity to UAVs will enable a myriad of applications ranging from online video streaming to medical delivery. However, to enable reliable wireless connectivity for the UAVs as well as secure operation, various challenges need to be addressed such as interference management, mobility management and handover, cyber-physical attacks, and authentication. In this article, the goal is to expose the wireless and security challenges that arise in the context of UAV-based delivery systems, UAV-based real-time multimedia streaming, and UAV-enabled intelligent transportation systems. To address such challenges, ANN-based solution schemes are introduced. The introduced approaches enable UAVs to adaptively exploit wireless system resources while guaranteeing secure operation in real time. Preliminary simulation results show the benefits of the introduced solutions for each of the aforementioned cellular-connected UAV application use cases.

Physical Layer Security in UAV Systems: Challenges and Opportunities

Abstract: Unmanned aerial vehicle (UAV) wireless communications has experienced an upsurge of interest in both military and civilian applications, due to its high mobility, low cost, on-demand deployment, and inherent line-of-sight air-to-ground channels. However, these benefits also make UAV wireless communication systems vulnerable to malicious eavesdropping attacks. In this article, we aim to examine the physical layer security issues in UAV systems. In particular, passive and active eavesdropping are two primary types of attack in UAV systems. We provide an overview on emerging techniques, such as trajectory design, resource allocation, and cooperative UAVs, to fight against both types of eavesdropping in UAV wireless communication systems. Moreover, the applications of non-orthogonal multiple access, multiple-input multiple-output, and millimeter-wave in UAV systems are also proposed to improve the system spectral efficiency and to guarantee security simultaneously. Finally, we discuss some potential research directions and challenges in terms of physical layer security in UAV systems.

Fundamental Trade-offs in Communication and Trajectory Design for UAV-Enabled Wireless Network

Abstract: The use of unmanned aerial vehicles (UAVs) as aerial communication platforms is of high practical value to future wireless systems such as 5G, especially for swift and on-demand deployment in temporary events and emergency situations. Compared to the static terrestrial base stations (BSs) in cellular networks, UAV-mounted aerial BSs possess stronger line-of-sight links with the ground users due to their high altitude as well as high and flexible mobility in 3D space, which can be exploited to enhance the communication performance. On the other hand, unlike terrestrial BSs that have reliable power supply, aerial BSs in practice have limited onboard energy, but require high propulsion power to stay airborne and support high mobility. Motivated by the above new considerations, this article aims to revisit some fundamental trade-offs in UAV-enabled communication and trajectory design. Specifically, it is shown that the communication throughput, delay, and (propulsion) energy consumption can be traded off among each other by adopting different UAV trajectory designs, which sheds new light on their existing trade-offs in terrestrial communication. The main design challenges and promising directions for future research are also discussed.

Research Challenges and Opportunities of UAV Millimeter-Wave Communications

Abstract: Millimeter-wave (mmWave) communication with multi-gigahertz bandwidth availability enables much higher capacity and transmission rate than conventional microwave communications. However, mmWave signals suffer from propagation-related shortcomings. The flexibility of UAV communication can compensate most of the deficiencies of mmWave signals, preserve its advantages, and provide more opportunities. In this article, we present the current state of the art, research opportunities, and challenges for UAV mmWave communication. We present channel characteristics and show its modeling issues. We further analyze how to achieve UAV mmWave channel acquisition and precoder design. Moreover, we discuss the challenges and possible solutions for UAV mmWave cellular networks, including UAV-to-base-station and UAV-to-user communications and spectrum sharing.

Low Probability of Detection Communication: Opportunities and Challenges

Abstract: LPD communication has recently emerged as a new transmission technology to address privacy and security in wireless networks. Recent studies have established the fundamental limits of LPD communication in terms of the amount of information that can be conveyed from a transmitter to a receiver subject to a constraint on a warden's detection error probability. The established information- theoretic metric enables analytical studies on the design and performance of LPD communication under various channel conditions. In this article, we present the key features of LPD communication and discuss various important design considerations. First, we clarify the differences between LPD communication and well-known physical-layer security. Then, from an information-theoretic point of view, we discuss the optimal signaling strategies for transmitting the message-carrying signal and artificial noise signal for LPD communication. Finally, we identify the key challenges in the design of practical LPD communication systems and point out future research directions in this context. This article provides guidelines for designing practical LPD communication strategies in wireless systems and networks.

Secure UAV Communication Networks over 5G

Abstract: Wireless communications can leverage UAVs to provide ubiquitous connectivity to different device types. Recently, integrating UAVs into a macro cell network is drawing unprecedented interest for supplementing terrestrial cellular networks. Compared with communications with fixed infrastructure, a UAV has salient attributes, such as easy-to-deploy, higher capacity due to dominant LoS communication links, and additional design degree-of-freedom with the controlled mobility. While UAV communication offers numerous benefits, it also faces security challenges due to the broadcasting nature of the wireless medium. Thus, information security is one of the fundamental requirements. In this article, we first consider two application cases of UAVs (i.e., a UAV as a flying base station and a UAV as an aerial node) in conjunction with safeguarding the exchange of confidential messages. Then, we demonstrate physical layer security mechanisms via two case studies to ensure security, and numerically show superior performance gains. Finally, we shed light on new opportunities in the emerging network architecture that can serve as a guide for future research directions.

Narrowband IoT: A Survey on Downlink and Uplink Perspectives

Abstract: Narrowband-IoT (NB-IoT) is a radio access technology standardized by the 3GPP to support a large set of use cases for massive machine-type communications. Compared to human-oriented 4G technologies, NB-IoT has key design features in terms of increased coverage, enhanced power saving, and a reduced set of functionalities. These features allow for connectivity of devices in challenging positions, enabling long battery life and reducing device complexity. This article provides a detailed overview on NB-IoT, together with analysis and performance evaluation of the technology. Both uplink and downlink directions are presented, including recent updates on the support of multicast transmissions. The article summarizes the possible configurations of NB-IoT, discusses the procedures for data transmission and reception, and analyzes aspects such as latency and resource occupation. We present a performance evaluation focusing on both uplink and downlink, with the aim to understand the channel occupancy of NB-IoT for different real-life IoT use cases and cell deployments. Further analysis focuses on the impact of various radio access parameters on the capacity of NB-IoT. Finally, results focusing on a new use case for NB-IoT (i.e., firmware update of a group of devices) are presented in the form of a comparison between unicast and multicast transmission modes.

Energy Efficient Tag Identification Algorithms For RFID: Survey, Motivation And New Design

Abstract: RFID is widely applied in massive tag based applications, thus effective anti-collision algorithms to reduce communication overhead are of great importance to RFID in achieving energy and time efficiency. Existing MAC algorithms are primarily focusing on improving system throughput or reducing total identification time. However, with the advancement of embedded systems and mobile applications, the energy consumption aspect is increasingly important and should be considered in the new design. In this article, we start with a comprehensive review and analysis of the stateof- the-art anti-collision algorithms. Based on our existing works, we further discuss a novel design of anti-collision algorithm and show its effectiveness in achieving energy efficiency for the RFID system using EPCglobal C1 Gen2 UHF standard.

Fog Computing for Smart Grid Systems in the 5G Environment: Challenges and Solutions

Abstract: Currently, the demand for electricity is increasing day by day, which necessitates upgrading of the existing power grid system. The conventional power grid has already been replaced with modern ICT-based infrastructure, which is known as smart grid (SG). In SG, smart meters generate a huge amount of data, and it is a challenging task to store, process, and analyze the data, which varies with respect to volume, velocity, and variety. The data generated in an SG system is generally stored and analyzed using cloud computing (CC), which provides real-time response for various applications. However, to handle the latency issue during the data analytics in SG, fog computing (FC) has emerged as a new technology that provides most of the computing resources in proximity of the end users. It acts as a bridge between SG and CC to fill the gap between processing power of remote data centers and smart devices in SG systems. To handle the aforementioned issues, there is a requirement to set up advanced sensors and measurement systems having communication network backbones in the upcoming fifth generation (5G). In this article, we discuss the architecture of SG in the context of FC for making the decision about energy requirements by the smart devices at the fog layer. Moreover, the communication and computing aspects are also explored in the context of 5G network infrastructure. We examine the influence of FC on response time, transmission delay, and energy management costs for delay-sensitive applications.

Air-Ground Heterogeneous Networks for 5G and Beyond via Integrating High and Low Altitude Platforms

Abstract: UAVs are expected to be an important complementary component for 5G (and beyond) communication systems to achieve the goal of global access to the Internet for all. To fully exploit the benefits of the distinct features of various UAVs, this article proposes a novel hierarchical network architecture enabled by software defined networking, which integrates cross-layer high and low altitude platforms into conventional terrestrial cellular networks to inject additional capacity and expand the coverage for underserved areas in a flexible, seamless, and cost-effective manner. Specifically, we first present a comprehensive comparison and review of different types of UAVs for communication services. Then, we propose an integrated airground heterogeneous network architecture and outline its characteristics and potential advantages. Next, several key enabling techniques for the integrated system are discussed in detail. In addition, we identify the potential application scenarios where the system can further enhance the performance of traditional terrestrial networks, followed by a case study to demonstrate the effectiveness of the proposed architecture. Finally, the discussions on challenges and open research issues are given.

Orbital Angular Momentum for Wireless Communications

Abstract: As the traditional resources (frequency, time, space, and so on) are efficiently utilized, it becomes more and more challenging to satisfy the ever-lasting capacity-growing and users-boosting demand in wireless networks. Recently, the EM wave was found to possess not only linear momentum, but also angular momentum. The OAM is a kind of wavefront with helical phase. The OAM-based vortex wave has different topological charges, which are orthogonal to each other, bridging a new way for multiple access in wireless communications. In this article, we introduce the fundamental theory of OAM and the OAM based wireless communications. The research challenges regarding OAM signal generation, OAM beam converging, and OAM signal reception are discussed. Further, we propose a new multiuser access with different OAM-modes in wireless networks, where multiple OAM-modes are used as a new orthogonal dimension for interference avoidance. Simulation results reveal the inherent property of OAM waves and show that OAM based radio transmission can significantly increase spectrum efficiency in wireless networks.

Wireless Power Transfer and Energy Harvesting: Current Status and Future Prospects

Abstract: The rechargeable battery is the conventional power source for mobile devices. However, limited battery capacity and frequent recharging requires further research to find new ways to deliver power without the hassle of connecting cables. Novel wireless power supply methods, such as energy harvesting and wireless power transfer, are currently receiving considerable attention. In this article, an overview of recent advances in wireless power supply is provided, and several promising applications are presented to show the future trends. In addition, to efficiently schedule the harvested energy, an energy scheduling scheme in the EH-powered D2D relay network is proposed as a case study. To be specific, we first formulate an optimization problem for energy scheduling, and then propose a modified two stage directional water filling algorithm to resolve it.

Integrated Millimeter Wave and Sub-6 GHz Wireless Networks: A Roadmap for Joint Mobile Broadband and Ultra-Reliable Low-Latency Communications

Abstract: Next-generation wireless networks must enable emerging technologies such as augmented reality and connected autonomous vehicles via a wide range of wireless services that span enhanced mobile broadband (eMBB) and ultra-reliable low-latency communication (URLLC). Existing wireless systems that solely rely on the scarce sub-6 GHz, mW frequency bands will be unable to meet such stringent and mixed service requirements for future wireless services due to spectrum scarcity. Meanwhile, operating at high-frequency mmWave bands is seen as an attractive solution, primarily due to the bandwidth availability and possibility of large-scale multi-antenna communication. However, even though leveraging the large bandwidth at mmWave frequencies can potentially boost the wireless capacity for eMBB services and reduce the transmission delay for low-latency applications, mmWave communication is inherently unreliable due to its susceptibility to blockage, high path loss, and channel uncertainty. Hence, to provide URLLC and high-speed wireless access, it is desirable to seamlessly integrate the reliability of mW networks with the high capacity of mmWave networks. To this end, in this article, the first comprehensive tutorial for integrated mmWave-mW communications is introduced. This envisioned integrated design will enable wireless networks to achieve URLLC along with eMBB by leveraging the best of two worlds: reliable, long-range communications at the mW bands and directional high-speed communications at the mmWave frequencies. To achieve this goal, key solution concepts are discussed that include new architectures for the radio interface, URLLC-aware frame structure and resource allocation methods along with mobility management, to realize the potential of integrated mmWave-mW communications. The opportunities and challenges of each proposed scheme are discussed and key results are presented to show the merits of t

CONet: A Cognitive Ocean Network

Abstract: The scientific and technological revolution of the Internet of Things has begun in the area of oceanography. Historically, humans have observed the ocean from an external viewpoint in order to study it. In recent years, however, changes have occurred in the ocean, and laboratories have been built on the sea floor. Approximately 70.8 percent of the Earth's surface is covered by oceans and rivers. The Ocean of Things is expected to be important for disaster prevention, ocean resource exploration, and underwater environmental monitoring. Unlike traditional wireless sensor networks, the Ocean Network has its own unique features, such as low reliability and narrow bandwidth. These features will be great challenges for the Ocean Network. Furthermore, the integration of the ocean network with artificial intelligence has become a topic of increasing interest for oceanology researchers. The cognitive ocean network (CONet) will become the mainstream of future ocean science and engineering developments. In this article, we define the CONet. The contributions of the article are as follows: a CONet architecture is proposed and described in detail; important and useful demonstration applications of the CONet are proposed; and future trends in CONet research are presented.

Safeguarding Wireless Network with UAVs: A Physical Layer Security Perspective

Abstract: Integrating unmanned aerial vehicles (UAVs) into future wireless systems such as the fifth-generation cellular network is anticipated to bring significant benefits for both the UAV and telecommunication industries. Generally speaking, UAVs can be used as new aerial platforms in the cellular network to provide communication services for terrestrial users, or become new aerial users of the cellular network served by the terrestrial base stations. Due to their high altitude, UAVs usually have dominant line-ofsight channels with the ground nodes, which, however, pose new security challenges to future wireless networks with widely deployed UAVs. On one hand, UAV-ground communications are more prone than terrestrial communications to eavesdropping and jamming attacks by malicious nodes on the ground. On the other hand, compared to malicious ground nodes, malicious UAVs can launch more effective eavesdropping and jamming attacks to terrestrial communications. Motivated by the above, in this article, we aim to identify such new issues from a physical-layer security viewpoint and present novel solutions to tackle them efficiently. Numerical results are provided to validate their effectiveness, and promising directions for future research are also discussed.

Physical Layer Security for the Internet of Things: Authentication and Key Generation

Abstract: A low-complexity, yet secure framework is proposed for protecting the IoT and for achieving both authentication and secure communication. In particular, the slight random difference among transceivers is extracted for creating a unique radio frequency fingerprint and for ascertaining the unique user identity. The wireless channel between any two users is a perfect source of randomness and can be exploited as cryptographic keys. This can be applied to the physical layer of the communications protocol stack. This article reviews these protocols and shows how they can be integrated to provide a complete IoT security framework. We conclude by outlining the future challenges in applying these compelling physical layer security techniques to the IoT.