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The Fifth Generation (5G) cellular network can be considered the way to the ubiquitous Internet and pervasive paradigm.The Internet of Vehicles (IoV) uses the network infrastructure to allow cars to be connected to new radio technologies, and can be supported by 5G networks. In this way, the Vehicle-to-Everything (V2X) integration needs 5G connections unavoidably. This paper presents a 5G V2X ecosystem to provide IoV. The proposed ecosystem is based on the Software-Defined Networking (SDN) concept. Considering vehicles as entertainment consumer points, the network infrastructure must be huge enough to guarantee delivery and quality. For this purpose, this paper evaluates vehicular Internet-based video services traffic and Vehicle-to-Vehicle (V2V) communications in urban and rural scenarios. Simulations were performed through the Network Simulator ns-3, employing millimeter Wave (mmWave) communications. Three metrics, data transfer rate, transmission delay, and Packet Delivery Ratio (PDR), were analyzed and compared for rural and urban IoV scenarios. The results have shown satisfactory performance to the IoV communications requirements when adopting the 5G network with V2X communications.

The accuracy of channel state information (CSI) acquisition directly affects the performance of millimeter wave (mmWave) communications. In this article, we provide an overview on CSI acquisition, including beam training and channel estimation for mmWave massive multiple-input multiple-output systems. The beam training can avoid the estimation of a high-dimension channel matrix, while the channel estimation can flexibly exploit advanced signal processing techniques. In addition to introducing the traditional and machine learning-based approaches in this article, we also compare different approaches in terms of spectral efficiency, computational complexity, and overhead.

The fifth generation (5G) and beyond wireless communications will transform many exciting applications and trigger massive data connections with private, confidential, and sensitive information. The security of wireless communications is conventionally established by cryptographic schemes and protocols in which the secret key distribution is one of the essential primitives. However, traditional cryptography-based key distribution protocols might be challenged in the 5G and beyond communications because of special features such as device-to-device and heterogeneous communications, and ultra-low latency requirements. Channel reciprocity-based key generation (CRKG) is an emerging physical layer-based technique to establish secret keys between devices. This article reviews CRKG when the 5G and beyond networks employ three candidate technologies: duplex modes, massive multiple-input multiple-output (MIMO) and mmWave communications. We identify the opportunities and challenges for CRKG and provide corresponding solutions. To further demonstrate the feasibility of CRKG in practical communication systems, we overview existing prototypes with different IoT protocols and examine their performance in real-world environments. This article shows the feasibility and promising performances of CRKG with the potential to be commercialized.

The current wireless communication infrastructure has to face exponential development in mobile traffic size, which demands high data rate, reliability, and low latency. MIMO systems and their variants (i.e., Multi-User MIMO and Massive MIMO) are the most promising 5G wireless communication systems technology due to their high system throughput and data rate. However, the most significant challenges in MIMO communication are substantial problems in exploiting the multiple-antenna and computational complexity. The recent success of RL and DL introduces novel and powerful tools that mitigate issues in MIMO communication systems. This article focuses on RL and DL techniques for MIMO systems by presenting a comprehensive review on the integration between the two areas. We first briefly provide the necessary background to RL, DL, and MIMO. Second, potential RL and DL applications for different MIMO issues, such as detection, classification, and compression; channel estimation; positioning, sensing, and localization; CSI acquisition and feedback, security, and robustness; mmWave communication and resource allocation, are presented.

Considering the three-dimensional (3D) trajectory, 3D antenna array, and 3D beamforming of unmanned aerial vehicle (UAV), a novel non-stationary millimeter wave (mmWave) geometry-based stochastic model for UAV to vehicle communication channels is proposed. Based on the analysis results of measured and ray tracing simulation data of UAV mmWave communication links, the proposed parametric channel model is constructed by a line-of-sight path, a ground specular path, and two strongest single-bounce paths. Meanwhile, a new parameter computation method is also developed, which is divided into the deterministic (or geometry-based) part and the random (or empirical) part. The simulated power delay profile and power angle profile demonstrate that the statistical properties of proposed channel model are time-variant with respect to the scattering scenarios, positions and beam direction. Moreover, the simulation results of autocorrelation functions fit well with the theoretical ones as well as the measured ones.

This paper discusses the design, manufacturing, and experimental characterization of a Ka-band fully dielectric reflectarray realized using Zetamix ε 7.5 ceramic material and additive manufacturing. Properly tuning the infill during the manufacturing process, it is possible to control the permittivity of the material, which can therefore be considered, to all intents and purposes, an additional degree of freedom for optimizing the unit cell and consequently the reflectarray performance. The optimal values of εr are determined through numerical analysis of the unit cell and experimental characterization of bricks manufactured with different printing parameters. Then, the unit cell is used to design a medium-sized reflectarray with an aperture of 207.4λ02 and a thickness of 0.44λ0, at the design frequency f0=30 GHz. The full-wave simulations of the designed RA and experimental measurements of a prototype confirm the excellent performance of the antenna, which exhibits a broadband flat response from 28 to 31 GHz and an aperture efficiency exceeding 50%.

Fifth generation (5G) cellular networks promise to support multi-radio access technologies (multi-RATs) with low and high frequencies aiming at delivering good coverage, several gigabits data rate, and ultra-reliable services. In this context, user-association and resource allocation appear to be a huge challenge due to the variety of specifications and varied propagation environments. In this treatise, the focus is on the technical and administrative difficulties of the adoption of user association (UA) mechanism and spectrum sharing approach (SSA) in millimeter wave (mmWave) systems, for example, the technical design considerations and their underlying options, as well as their impact on users and network performance. In addition, details on the importance of the rules and regulations of SSA are presented. This study also identified a few possible design solutions and potential promising technologies in both UA and SSA. In the context of UA, several mechanisms are identified, such as backhaul-, caching-, and hybrid multi-criteria-aware UA to achieve seamless connectivity and to enhance the network utility. In the context of SSA, this study pinpoints varied subjects that need to be explored, such as joint efficient rules and regulations enactment, assessment of fairness and independence in multi-independent mobile network operators (multi-IMNOs) that support SSA, as well as the implementation of hybrid-SSA via Virtualized Cloud Radio Access Network. Finally, attention is drawn to several key conclusions to enable readers and interested researchers to learn about the most controversial points of mmWave 5G cellular networks.

In this paper, we address the problem of authenticating transmitters in millimeter-wave (mmWave) multiple-input multiple-output (MIMO) communication systems, and propose a location verification scheme based on multi-dimensional mmWave MIMO channel features. In particular, we first examine the mmWave MIMO channel features in terms of azimuth angle of arrival (AAoA), elevation angle of arrival (EAoA), and path gain, and then extract these fine-grained channel features through the maximum-likelihood (ML) estimation method. Based on the extracted feature parameters, authentication validation is cast in the framework of hypothesis testing theory. We also derive the analytical expressions for the typical false alarm and detection rates by using the likelihood ratio test and thus the statistical performance is analytically established. Finally, extensive numerical results are provided to demonstrate the performance of the proposed authentication scheme.

Angle-of-arrival (AoA) estimation in localized hybrid arrays suffers from phase ambiguity owing to its localized structure and vulnerability to noise. In this letter, we propose a novel phase shift design, allowing each subarray to exploit difference beam steering in two potential AoA directions. This enables the calibration of cross-correlations and an enhanced phase offset estimation between adjacent subarrays. We propose two unambiguous AoA estimation schemes based on the even and odd ratios of the number of antennas per subarray N to the number of different phase shifts per symbol K (i.e., N/K), respectively. The simulation results show that the proposed approach greatly improves the estimation accuracy as compared to the state of the art when the ratio N/K is even.

Cell-free millimeter wave (mmWave) multiple-input multiple-output (MIMO) can effectively overcome the shadow fading effect and provide macro gain to boost the throughput of communication networks. Nevertheless, the majority of the existing studies have overlooked the user-centric characteristics and practical fronthaul capacity limitations. To solve these practical problems, we introduce a resource allocation scheme using statistical channel state information (CSI) for uplink user-centric cell-free mmWave MIMO system. The hybrid beamforming (HBF) architecture is deployed at each access point (AP), while the central processing unit (CPU) only combines the received signals by the large-scale fading decoding (LSFD) method. We further frame the issue of maximizing sum-rate subject to the fronthaul capacity constraint and minimum rate constraint. Based on the alternating optimization (AO) and fractional programming method, we present an algorithm aimed at optimizing the users’ transmit power for the power allocation (PA) subproblem. Then, an algorithm relying on the majorization–minimization (MM) method is given for the HBF subproblem, which jointly optimizes the HBF and the LSFD coefficients.