In the 1940s,Claude Shannon developed the information theory focusing on quantifying the maximum data rate that can be supported by a communication channel. Guided by this fundamental work, the main theme of wireless system design up until the fifth generation(5G)was the data rate maximization. In Shannon’s theory, the semantic aspect and meaning of messages were treated as largely irrelevant to communication. The classic theory started to reveal its limitations in the modern era of machine intelligence, consisting of the synergy between Internet-of-things (IoT) and artificial intelligence (AI). By broadening the scope of the classic communication-theoretic framework, in this article, we present a view of semantic communication (SemCom) and conveying meaning through the communication systems. We address three communication modalities:human-to-human(H2H),human-to-machine(H2M),and machine-to-machine(M2M)communications. The latter two represent the paradigm shift in communication and computing, and define the main theme of this article. H2M SemCom refers to semantic techniques for conveying meanings understandable not only by humans but also by machines so that they can have interaction and“dialogue”. On the other hand, M2M SemCom refers to effective techniques for efficiently connecting multiple machines such that they can effectively execute a specific computation task in a wireless network. The first part of this article focuses on introducing the SemCom principles including encoding, layered system architecture, and two design approaches: 1) layer-coupling design; and 2) end-to-end design using a neural network. The second part focuses on the discussion of specific techniques for different application areas of H2M SemCom [including human and AI symbiosis,recommendation,human sensing and care, and virtual reality(VR)/augmented reality (AR)]and M2M SemCom(including distributed learning, split inference,distributed consensus,and machine-vision cameras). Finally,we discuss the approach for designing SemCom systems based on knowledge graphs.We believe that this comprehensive introduction will provide a useful guide into the emerging area of SemCom that is expected to play an important role in sixth generation (6G) featuring connected intelligence and integrated sensing, computing,communication,and control.

Artificial intelligence (AI) has shown great potential in wireless communications. AI-empowered communication algorithms have beaten many traditional algorithms through simulations. However, the existing works just use the simulated datasets to train and test the algorithms, which can not represent the power of AI in practical communication systems. Therefore, Peng Cheng Laboratory holds an AI competition, National Artificial Intelligence Competition (NAIC): AI+wireless communications, in which one of the topics is AI-empowered channel feedback system design using practical measurements. In this paper, we give a baseline neural network design, QuanCsiNet, for this competition, and the details of the channel measurements. QuanCsiNet shows excellent performance on channel feedback and the complexity of the neural networks is also given.

Physical layer security (PLS) in wireless communication systems has attracted extensive research attentions in recent years. Unlike cryptography-based methods applied in upper-layer in network, PLS methods are applied in physical layers and can provide information-theoretic security by utilizing the randomness of signals and wireless channels. In this survey, we provide a comprehensive review in the domain of physical layer authentication (PLA) in wireless communication systems, including the concepts, several key techniques of typical PLA architectures as well as future challenges and research trends in more sophisticated communication systems. The survey begins with an overview of the background and basic concepts of PLA, such as the general model of wireless security communication system, typical frameworks of key-based/less PLA systems, and the common attack models. We then discuss the major concerns and key techniques that are applied in PLA systems, where three types of authentication schemes are considered, i. e. , the authentication based on channel information, radio-frequency and identity watermarks. Basic models and representative research results about key approaches and techniques applied to the authentication systems above are subsequently covered. Finally, the associated challenges and potential research trends of PLA in future communication systems are presented at the end of the survey paper.

Ubiquitous computing facilitated by Internet of things (IoT) devices has made modern day life easier across many areas. It offers capabilities to measure parameters associated with the devices, to infer from their results, and to understand and control millions of such devices in various application domains. The enormous potential of IoT systems enables each and every device to communicate with each other, thereby providing more productivity. In this scenario, heterogeneity of technologies in use is expected to intensify the security threats. Policy enforcement for the assurance of privacy and security plays a key role in these systems. Fulfillment of privacy and security related requirements include confidentiality of data, user and device authentication, access control, and trust assurance among the things. However, recent reported events related to security attacks show colossal vulnerabilities among IoT devices capable of bringing security risks to the whole environment. One of the common uses of these devices by the attackers is to generate powerful distributed denial of service(DDoS)attacks. It is one of the most prominent attacking behaviors over a network by a group of geographically distributed zombie computers that interrupt and block legitimate users to use the network resources and hence, requires great attention. In this regard, the current work being novel in the field puts concentration on variants of DDoS attacks and their impact on IoT networks along with some of the existing countermeasures to defend against these attacks. The paper also discusses the detailed working mechanism of these attacks and highlights some of the commonly used tools that are deployed in such attack scenarios.

Cloud computing facilitates convenient and on-demand network access to a centralized pool of resources. Currently, many users prefer to outsource data to the cloud in order to mitigate the burden of local storage. However, storing sensitive data on remote servers poses privacy challenges and is currently a source of concern. SE (Searchable Encryption) is a positive way to protect users sensitive data, while preserving search ability on the server side. SE allows the server to search encrypted data without leaking information in plaintext data. The two main branches of SE are SSE (Searchable Symmetric Encryption) and PEKS (Public key Encryption with Keyword Search). SSE allows only private key holders to produce ciphertexts and to create trapdoors for search, whereas PEKS enables a number of users who know the public key to produce ciphertexts but allows only the private key holder to create trapdoors. This article surveys the two main techniques of SE: SSE and PEKS. Different SE schemes are categorized and compared in terms of functionality, efficiency, and security. Moreover, we point out some valuable directions for future work on SE schemes.

The performance of a device-to-device (D2D) underlay communication system is limited by the co-channel interference between cellular users (CUs) and D2D devices. To address this challenge, a reconfigurable intelligent surface (RIS) aided D2D underlay system is studied in this paper. A two-timescale optimization scheme is proposed to reduce the required channel training and feedback overhead, where transmit beamforming at the base station(BS)and power control at the D2D transmitters are adapted to instantaneous effective channel state information (CSI); and the RIS phase shifts are adapted to slow-varying channel mean. Based on the two-timescale optimization scheme, we aim to maximize the D2D ergodic weighted sum-rate (WSR)subject to a given outage probability constrained signal-to-interference-plus-noise ratio (SINR) target for each CU. The two-timescale problem is decoupled into two sub-problems, and the two sub-problems are solved iteratively. Numerical results verified that the two-timescale based optimization performs better than two baselines, and also demonstrated a favourable trade-off between system performance and CSI overhead.

The wide spectrum and propagation characteristics over the air give mmWave communication unique advantages as well as design challenges for 5G applications. To increase the system speed, capacity, and coverage, there is a need for innovation in the RF system architecture, circuit, antenna, and package in terms of implementation opportunities and constraints. The discuss mmWave spectrum characteristics, circuits, RF system architecture, and their implementation issues are discussed. Moreover, the transmitter key components, i. e. , the receiver, antenna, and packaging are reviewed.

IoV (Internet of Vehicles) is a promising paradigm to the future of automobiles, which will undoubtedly boost the automobile market as well as accelerate innovation in Internet services and applications. The concept of SD-IoV (Software Defined IoV) is presented, which is capable of improving resource utilization, service quality, and network optimization in the harsh vehicular network environments. First, A generalized SD-IoV architecture as an intuitive big picture is presented. Then, the major functions realized by SD-IoV are elabrated on to illustrate how the current challenges are resolved. As the key enablers of SD-IoV, three possible implementation methods of the wireless control path are described and compared. Finally, the challenges and existing solutions of SD-IoV are disuessed and open issues are pointed out so as to shed light on future research.

In recent years, data mining and machine learning technologies have made great progress driven by enormous volumes of data. Meanwhile, the wireless-channel measurement data appears large in volume because of the large-scale antenna numbers, increased bandwidth, and versatile application scenarios. With powerful data mining and machine learning methods and large volumes of data, we can extract valuable and hidden rules from the wireless channel. Motivated by this, we propose a channel-modeling method using PCA in this paper. Its principle is to utilize the features and structures extracted from the CIR data collected by measurements, and then model the wireless channel of the targeted measurement scenario. In addition, a noise removing method using a BP neural network is designed for the proposed model, which can recognize and remove the noise of the polluted CIR accurately. The performance of the proposed scheme is investigated with the actual measured CIR data, and its superiority is verified.

While the commercial deployment and promotion of 5G is ongoing, mobile communication networks are still facing three fundamental challenges, i. e. , spectrum resource scarcity, especially for low-frequency spectrum, exacerbated by fragmented spectrum allocation, user-centric network service provision when facing billions of personalized user demands in the era of Internet of everything (IoE), and proliferating operation costs mainly due to huge energy consumption of network infrastructure. To address these issues, it is imperative to consider and develop disruptive technologies in the next generation mobile communication networks, namely 6G. In this paper, by studying brain neurons and the neurotransmission, we propose the fully-decoupled radio access network(FD-RAN). In the FD-RAN, base stations (BSs) are physically decoupled into control BSs and data BSs, and the data BSs are further physically split into uplink BSs and downlink BSs. We first review the fundamentals of neurotransmission and then propose the 6G design principles inspired by the neurotransmission. Based on the principles, we propose the FD-RAN architecture, elastic resource cooperation in FD-RAN, and improved transport service layer design. The proposed fully decoupled and flexible architecture can profoundly facilitate resource cooperation to enhance the spectrum utilization, reduce the network energy consumption and improve the quality of user experience. Future research topics in this direction are envisioned and discussed.

As unmanned aerial vehicles (UAV) deployment is shifting from military to civilian sectors, and in particular as a means of facilitating more flexible and versatile wireless communications, the UAV channels that were previously not well understood are attracting increasing research and investigation. As the key component facilitating the UAV-aided communications, UAV channel characteristics and modeling are of critical importance to the designed UAV system to achieve satisfactory performance. In this article, we will provide a comprehensive overview and the future perspective of envisioned UAV communication system benefits, the existing and needed UAV channel measurements and modeling approaches, together with the new viewpoint of UAV channel applications in different communication and networking layers. Both existing work and future directions are extensively covered.

To better support the emerging vehicular applications and multimedia services,vehicular edge computing(VEC)provides computing and caching services in proximity to vehicles, by reducing network transmission latency and alleviating network congestion. However, current VEC networks may face some implementation challenges, such as high mobility of vehicles, dynamic vehicular environment,and complex network scheduling. Digital twin, as an emerging technology, can make the virtual representation of physical networks to predict, estimate,and analyze the real-time network state. In this paper, we integrate digital twin into VEC networks to adaptively make network management and policy schedule. We first introduce the framework of VEC networks and present the key problems in a VEC network.Next,we give the concept of digital twin and propose an adaptive digital twin-enabled VEC network. In the proposed network, digital twin can enable adaptive network management via the two-closed loops between physical VEC networks and digital twins. Further,we propose a digital twin empowered VEC offloading problem with vehicle digital models and road side unit (RSU) digital models. A deep reinforcement learning (DRL)-based offloading scheme is designed to minimize the total offloading latency. Numerical results demonstrate the effectiveness of the proposed DRL-based algorithm for VEC offloading.

Nowadays both satellite and terrestrial networks are expanding rapidly to meet the ever-increasing demands for higher throughput, lower latency, and wider coverage. However, spectrum scarcity places obstacles in the sustainable development. To accommodate the expanding network within a limited spectrum, spectrum sharing is deemed as a promising candidate. Particularly, cognitive radio (CR) has been proposed in the literature to allow satellite and terrestrial networks to share their spectrum dynamically. However, the existing CR-based schemes are found to be impractical and inefficient because they neglect the difficulty in obtaining the accurate and timely environment perception in satellite communications and only focus on link-level coexistence with limited interoperability. In this paper, we propose an intelligent spectrum management framework based on software defined network(SDN)and artificial intelligence (AI). Specifically, SDN transforms the heterogenous satellite and terrestrial networks into an integrated satellite and terrestrial network(ISTN)with reconfigurability and interoperability. AI is further used to make predictive environment perception and to configure the network for optimal resource allocation. Briefly, the proposed framework provides a new paradigm to integrate and exploit the spectrum of satellite and terrestrial networks.

In this review, research progress on the wideband wide-angle scanning two-dimensional phased arrays is summarized. The importance of the wideband and the wide-angle scanning characteristics for satellite communication is discussed. Issues like grating lobe avoidance, active reflection coefficient suppression and gain fluctuation reduction are emphasized in this review. Besides, techniques to address these issues and methods to realize the wideband wide-angle scanning phased array are reviewed.

Rapid and effective maritime search and rescue operations become the important guarantee for the safety of maritime navigation. The existing maritime search and rescue networking and model have slow response speed and low efficiency. The distribution, synergy, parallelism, robustness and intelligence of unmanned surface vehicle(USV)and unmanned aerial vehicle(UAV) provide a new idea for the novel maritime search and rescue networking, in which multi-agent could be used to build a layered control network. In this paper, a novel rapid search and rescue system is proposed by utilizing the improved ant colony optimization and the independent calculation decision of the agents. The system adopts the edge computing, relies on the information sharing and the cooperative decision between the search and rescue agent groups. It achieves the independent synchronous search and rescue. At the same time, we use particle swarm optimization to intelligently schedule data packets during the rescue process to optimize network forwarding performance. Based on the distributed cluster control of USV and UAV, this paper combines edge computing, cooperative communication and centralized task allocation together to make decision for rescue. The simulation results show that our proposed schemes realize a significant improvement for maritime search and rescue.

Due to space limitation, mutual coupling occurs almost invisibly in array antennas. In this paper, the mutual coupling effects on the two most popular categories of array antennas, i. e. , phased arrays and multiple-input multiple-output (MIMO) antennas, are reviewed. Some misconceptions regarding the mutual coupling effects are uncovered. It is shown that the steering pattern of a phased array at an arbitrary scanning angle can be readily calculated once the embedded radiation patterns of the array elements (including the mutual coupling effect)are obtained. As antenna spacing decreases, absorption loss increases, yet the phase terms tend to add up constructively as antenna spacing reduces, which may overcompensate the absorption loss due to mutual coupling. Thus, the array efficiency may be increased by reducing the antenna spacing. A patch antenna array is used to illustrate this phenomenon. It is further shown that while mutual coupling tends to reduce the correlation of two-element arrays, it has a negligible effect on the overall correlations of larger arrays. Finally, various mutual coupling reduction techniques are briefly presented. Two feasible techniques for large planar arrays are used to illustrate the benefits of array decoupling.

Orthogonal time frequency space (OTFS) modulation, collaborated with millimeter-wave (mmWave) massive multiple-input-multiple-output (MIMO), is a promising technology for next generation wireless communications in high mobility scenarios. However, one of the main challenges for mmWave massive MIMO-OTFS systems is the enormous computational complexity of channel estimation incurred by the huge OTFS symbol size and the large number of antennas. To address this issue, in this paper, a tensor-based orthogonal matching pursuit(OMP)channel estimation algorithm is proposed by exploiting the channel sparsity in the delayDoppler-angle domain. In particular, we firstly propose a novel pilot design for the OTFS symbol structure in the frequency-time domain. Then, based on the proposed pilot structure, we formulate the channel estimation as a sparse signal recovery problem, and the tensor decomposition and parallel support detection are introduced into the tensor-based OMP algorithm to reduce the signal processing dimension significantly. Numerical simulations are performed to verify the superiority and the robustness of the proposed tensor-based OMP algorithm.

The mobile Ad Hoc network (MANET) is a self-organizing and self-configuring wireless network, consisting of a set of mobile nodes. The design of efficient routing protocols for MANET has always been an active area of research. In existing routing algorithms, however, the current work does not scale well enough to ensure route stability when the mobility and distribution of nodes vary with time. In addition, each node in MANET has only limited initial energy, so energy conservation and balance must be taken into account. An efficient routing algorithm should not only be stable but also energy saving and balanced, within the dynamic network environment. To address the above problems, we propose a stable and energy-efficient routing algorithm, based on learning automata (LA) theory for MANET. First, we construct a new node stability measurement model and define an effective energy ratio function. On that basis, we give the node a weighted value, which is used as the iteration parameter for LA. Next, we construct an LA theory-based feedback mechanism for the MANET environment to optimize the selection of available routes and to prove the convergence of our algorithm. The experiments show that our proposed LA-based routing algorithm for MANET achieved the best performance in route survival time, energy consumption, energy balance, and acceptable performance in end-to-end delay and packet delivery ratio.

With the rapid growth of unmanned aerial vehicle (UAV), there is now an increasing interest in the security of UAV systems. There exist various attacks which have threatened the security of UAV systems, in terms of the global navigation satellite system (GNSS) spoofing. Consisted of multiple UAVs, the flying ad hoc networks (FANET) have been studied to extend the employment and coverage of UAV systems. Based on the connectivity and information interaction of FANET, in this article, the blockchain technology is applied to detect GNSS signal attacks for UAV systems. In particular, we first introduce an overview of the GNSS security of UAV systems and the principles for blockchain technology. Based on the principles, a logical architecture is proposed, where blockchain is taken into consideration for GNSS spoofing detection. Performance analysis verifies that the proposed GNSS spoofing detection system can be used effectively. Finally, several challenges in blockchain are discussed, including security, cost, and regulation.

Estates, especially those of public securityrelated companies and institutes, have to protect their privacy from adversary unmanned aerial vehicles(UAVs). In this paper, we propose a reinforcement learning-based control framework to prevent unauthorized UAVs from entering a target area in a dynamic game without being aware of the UAV attack model. This UAV control scheme enables a target estate to choose the optimal control policy, such as jamming the global positioning system signals, hacking, and laser shooting, to expel nearby UAVs. A deep reinforcement learning technique, called neural episodic control, is used to accelerate the learning speed to achieve the optimal UAV control policy, especially for estates with a large area, against complicated UAV attack policies. We analyze the computational complexity for the proposed UAV control scheme and provide its performance bound, including the risk level of the estate and its utility. Our simulation results show that the proposed scheme can reduce the risk level of the target estate and improve its utility against malicious UAVs compared with the selected benchmark scheme.

The space-air-ground network architecture integrates satellite systems, aerial networks, and terrestrial networks, where the unmanned aerial vehicle(UAV) communication in the air segment has attracted particular interest and demonstrated tremendous potential in both military and civilian applications. Orthogonal frequency division multiplexing(OFDM)can be an effective solution to provide high rate and reliable transmission in UAV communication systems because of its high spectral efficiency and robustness against frequency selective fading. We herein focus our attention on two critical issues in our proposed UAV aided OFDM system, i. e. , timing synchronization and ranging. Moreover, extensive simulations are conducted for evaluation. Finally, we design a real-world field test for verifying the effectiveness of our proposed multi-UAV OFDM communication system.

Mobile-edge computing (MEC), enabling to offload computing tasks on mobile devices towards edge servers, can reduce the terminals cost. However, a single MEC sever usually has limited computing capabilities, which can not meet a large number of terminals’ requirements. In this paper, we consider an ultra-dense networks (UDN) scenario where the macro base stations (MBSs) are assisted by MEC severs. In particular, we first construct system model for MEC assisted UDN,and build the system overhead minimization. Next, in order to solve the problem, we transform the problem into three sub-problems,i.e.,offloading strategies subproblem, channel assignments subproblem, and power allocation subproblem. Then, employing joint offloading and resource allocation algorithms,we obtain the optimal joint strategy for the MEC assisted UDNs. Finally,simulations are conducted to evaluate the performance of our proposed algorithms. Numerical results show that obtained algorithms can effectively reduce the energy consumption of the system and improve the overall performance of the system.

A wideband 2 × 2 sequential-phase fed circularly polarized (CP) microstrip antenna array (MAA) with sequentially rotated elements is proposed. Firstly, the antenna element loaded with shorting pins is studied as compared to the traditional counterpart. Then, a feeding network is designed to be connected together in a sequential rotation manner, resulting in forming a four-port network to allow symmetrical positioning of CP microstrip patch elements. After that, straight strips are added to the feeding network in order to increase the distance and reduce coupling between array elements. They also play a role in improving the impedance matching of the array. Finally, the proposed antenna array is designed and simulated. The results are presented that its impedance bandwidth is about 36. 3% at 24. 1～34. 8 GHz for |S< sub> 11< /sub> |＆lt; ?10 dB and axial-ratio (AR) bandwidth is about 20.4% at 24. 2～29. 7 GHz for AR＆lt; 3 dB. Besides, a peak gain of 11. 1 dBic is simulated over the operating frequency range, which is significantly improved compared to the classic and existing works.

Indoor wireless communication networking has received significant attention along with the growth of indoor data traffic. VLC (Visible Light Communication) as a novel wireless communication technology with the advantages of a high data rate, license-free spectrum and safety provides a practical solution for the indoor high-speed transmission of large data traffic. However, limited coverage is an inherent feature of VLC. In this paper, we propose a novel hybrid VLC-Wi-Fi system that integrates multiple links to achieve an indoor high-speed wide-coverage network combined with multiple access, a multi-path transmission control protocol, mobility management and cell handover. Furthermore, we develop a hybrid network experiment platform, the experimental results of which show that the hybrid VLC-Wi-Fi network outperforms both single VLC and Wi-Fi networks with better coverage and greater network capacity.

Abstract: Focusing on its main requirements and challenges and by analyzing the characteristics of different space platforms, an overall architecture for space information networks is proposed based on national strategic planning and the present development status of associated technologies. Furthermore, the core scientific problems that need to be solved are expounded. In addition, the primary considerations and a preliminary integrated demonstration environment for verification of key technologies are presented.

With the rapid development of modern electronic technologies, antenna arrays typically operate in very complex electromagnetic environments. However, owing to the various errors such as systematic errors and random errors, conventional antenna arrays have relatively high sidelobes. Time modulated arrays (TMAs), also known as four-dimensional (4-D) antenna arrays, introduce time as an additional dimension for generating ultra-low sidelobes at fundamental component and realizing real-time beam scanning by harmonic components. Recently, the harmonic components can also be developed for various new applications including wireless communications and radar systems. In this review, we introduce comprehensively the fundamental methodologies and recent applications of TMAs. This aims to stimulate continuing efforts for the understanding of TMAs and explore their applications in various aspects. The methods mentioned in this review include three aspects: sideband radiation suppression, power efficiency of TMAs, and applications of harmonic components. These methods either improve the existing TMAs or promote the practical applications of TMAs. First, to suppress the sideband radiation, a method using non-uniform periodical modulation is introduced. The proposed method has an advantage of low computation and can be easily used for synthesizing a real-time radiation pattern according to the environmental need. Next, a TMA structure using reconfigurable power dividers/combiner is introduced to improve the power efficiency of feeding network. Finally, three applications of harmonic component including direction finding, calibration method, and space division multiple access are separately introduced to illustrate the development potential of TMAs.

Atmospheric ducting has a significant impact on electromagnetic wave propagation. Radio signals that are trapped and guided by the atmospheric duct can travel a much longer distance over the horizon with lower attenuation since the signal power does not spread isotropically through the atmosphere.Atmospheric ducting brings both challenges and opportunities to wireless communications. On one hand, the signals propagating in the atmospheric duct may interfere with a receiver far away as remote co-channel interference. On the other hand, a point-to-point link can be established directly through the atmospheric duct to enable beyond line-of-sight communications. In this article, the formation of the atmospheric duct and its effects on radio wave propagation are first overviewed. Then solutions and standardization activities in the 3rd Generation Partnership Project (3GPP) to mitigate atmospheric duct induced remote interference are presented. Finally, the applications and design challenges of atmospheric duct enabled beyond line-of-sight communications are reviewed and future research directions are suggested.