Digital twins (DTs) have driven major advancements across various industrial domains over the past two decades. With the rapid advancements in autonomous driving and vehicle-to-everything (V2X) technologies, integrating DTs into vehicular platforms is anticipated to further revolutionize smart mobility systems. In this paper, a new smart mobility DT (SMDT) platform is proposed for the control of connected and automated vehicles (CAVs) over next-generation wireless networks. In particular, the proposed platform enables cloud services to leverage the abilities of DTs to promote the autonomous driving experience. To enhance traffic efficiency and road safety measures, a novel navigation system that exploits available DT information is designed. The SMDT platform and navigation system are implemented with state-of-the-art products, e.g., CAVs and roadside units (RSUs), and emerging technologies, e.g., cloud and cellular V2X (C-V2X). In addition, proof-of-concept (PoC) experiments are conducted to validate system performance. The performance of SMDT is evaluated from two standpoints: (i) the rewards of the proposed navigation system on traffic efficiency and safety and, (ii) the latency and reliability of the SMDT platform. Our experimental results using SUMO-based large-scale traffic simulations show that the proposed SMDT can reduce the average travel time and the blocking probability due to unexpected traffic incidents. Furthermore, the results record a peak overall latency for DT modeling and route planning services to be 155.15 ms and 810.59 ms, respectively, which validates that our proposed design aligns with the 3GPP requirements for emerging V2X use cases and fulfills the targets of the proposed design. Our demonstration video can be found at https://youtu.be/3waQwlaHQkk .

The technical exploration of safe automated driving has evolved from single vehicle intelligence to vehicular networking. Therefore, to a certain extent, the safety requirements have been translated into the requirements for network performance. Although Vehicle-to-Everything (V2X) communication technologies have developed decades of years, from the Dedicated Short-Range Communication (DSRC) to the Long Term Evolution V2X (LTE-V2X), the introduction of millimeter wave (mmWave) in the 5G era will achieve an unprecedented leap in V2X performance by empowering multi-gigabit data transmission with ultra-low latency. Meanwhile, the emergence of Software Defined Networking (SDN) enables centralized network management and allows flexible scheduling of communication resources to match V2X capacities. Their benefits for vehicular networks have been revealed by plenty of studies respectively. Nevertheless, no researchers investigate their combination to improve the safety of automated driving, especially lack of scalable prototype systems for proof-of-concepts (PoCs), not to mention the field test with real traffic. In this paper, we firstly propose a novel architecture, i.e. software-defined dynamic mmWave V2X network, to support cooperative perception. And then, necessary hardware and software platforms are introduced to compose prototype systems. Step by step, we conduct PoCs from the indoors to the outdoors, which demonstrate the network functions, the prototype scalability and most importantly, the significant enhancement to the vehicle perception for safe automated driving.

The quality-of-service (QoS)/quality-of-experience (QoE) demands of mobile services are soaring and have overwhelmed the obsolescent capability of 3G and 4G cellular networks. The emerging 5G networks will bring an unprecedented promotion in transmission data rates. However, the satisfaction of some service requirements is still in dilemma, especially the end-to-end (E2E) latency which varies in different applications. Multi-access edge computing (MEC), a promising technology in 5G cellular networks, can provide ultra-low E2E latency and reduce traffic load on mobile backhaul networks. The potential benefits of MEC for 5G and beyond services have been explored by preliminary studies. What remains is the uncertainty of revenue from the investment of MEC which will shake operators' decisions about whether and how to deploy MEC in cellular networks. In this light, this paper designs a MEC-assisted 5G and beyond ecosystem inclusive of three players: private (local) telecom operators, backhaul, and cloud service owners. We propose a revenue maximization model for private (local) telecom operators and cloud service owners to minimize the cost from the end-user perspective while satisfying the latency requirement. The derived model indicates that two players' revenues can be maximized by optimizing MEC resources and backhaul capacity. The game-theoretic analyses also reveal the optimized hybrid strategy of MEC and cloud for efficient mobile traffic management.

The transformation and innovation brought by vehicle-to-everything (V2X) communications are ongoing. Enhanced road safety, traffic efficiency, and vehicle automation are all promised on condition that the envisioned V2X applications can be realized. "Share what I can see" is one of the visions, known as cooperative perception (CP). CP enables sensor data sharing, while the types of data are diverse according to the levels of vehicle automation. To support sharing raw, pre-processed, and fully processed data, V2X is advancing. Emerging radio access technologies (RATs) like millimeter waves (mmWave) are introduced. V2X networks become more heterogeneous than ever before. To fill in the gaps that existing V2X networks lack interoperability and a network function to manage heterogeneous V2X, this paper proposes Het-SDVN, a software defined networking (SDN)-based vehicular network (SDVN) architecture for heterogeneous V2X. Compared to the counterparts, Het-SDVN features hierarchical control planes (C-planes), which can reduce overhead and latency, provide scalability, and guarantee the availability of CP. This paper also presents the demonstration of Het-SDVN in a real-life proof of concept. Through the response to diverse CP requests, the required V2X performance, the capability of local SDVN, and the importance of interference management are all revealed. Besides, a benchmarking test in flow installation for local and global SDVN controllers is carried out. Finally, this paper shows the visualization results of CP.

Among UAV applications, real-time high-resolution video surveillance systems using unmanned aerial vehicles (UAVs) especially gain our research interests, because high mobilities of UAVs and high qualities of videos can dramatically improve the surveillance performance and evolve the system, especially for artificial intelligence (AI)-based monitoring systems. However, it is challenging to transmit high-resolution videos to ground station in real-time and also impossible to perform AI detection based on these videos on UAVs. To address the challenges, we propose to take full advantages of mmWave communications and to apply it into UAV-based surveillance systems to transmit ultra-high-quality and ultra-high-resolution uncompressed 4 K videos. To increase energy efficiency of UAVs, we propose to offload all computations via mmWave from UAVs to ground station. Moreover, in addition to design of system architecture, proof-of-concept (PoC) prototype hardware of the proposed system is practically developed to demonstrate technical feasibilities of mmWave communication on UAVs and the enhancements to practical surveillance applications. The practical issues in the implementation and the necessary hardware/software applied in the prototype system are explained in detail in this paper. An outdoor PoC experiment is conducted, and the experimental results are consistent with design, so that the effectiveness of the system is confirmed.

In this article, a compact 94 GHz multibeam antenna array based on the binary phase-controlled concept is proposed. The feeding network is composed of four unconnected layers, and the ridge or groove gap waveguides are adopted as the guided wave structures. A key planar gap waveguide Magic-Tee is designed to obtain 0° and 180° phase states and then integrates with an $8\,\times \,8$ slot antenna array to achieve multibeam operation for the first time. Compared with the traditional phased array and passive beamforming networks (BFNs), the feeding design is simple in construction, consisting of only Magic-Tees and cascaded power dividers without any phase shifters. Benefiting from the gap waveguide technology, the antenna array does not require electrical contact among the metal layers, so it is simple and low cost to manufacture. The $8\times8$ slot antenna array can easily switch among one-beam and three different dual-beam states that point to ±7°, ±17°, and ±38°. The measurement results of 6.6% bandwidth from 91.7 to 98 GHz for both reflection coefficients $< -10$ dB and isolations >25 dB are achieved. The proposed multibeam antenna array would be an attractive candidate for millimeter-wave multiuser communication where it requires multiple beams simultaneously.