The fifth generation (5G) wireless communication networks are being deployed worldwide from 2020 and more capabilities are in the process of being standardized, such as mass connectivity, ultra-reliability, and guaranteed low latency. However, 5G will not meet all requirements of the future in 2030 and beyond, and sixth generation (6G) wireless communication networks are expected to provide global coverage, enhanced spectral/energy/cost efficiency, better intelligence level and security, etc. To meet these requirements, 6G networks will rely on new enabling technologies, i.e., air interface and transmission technologies and novel network architecture, such as waveform design, multiple access, channel coding schemes, multi-antenna technologies, network slicing, cell-free architecture, and cloud/fog/edge computing. Our vision on 6G is that it will have four new paradigm shifts. First, to satisfy the requirement of global coverage, 6G will not be limited to terrestrial communication networks, which will need to be complemented with non-terrestrial networks such as satellite and unmanned aerial vehicle (UAV) communication networks, thus achieving a space-air-ground-sea integrated communication network. Second, all spectra will be fully explored to further increase data rates and connection density, including the sub-6 GHz, millimeter wave (mmWave), terahertz (THz), and optical frequency bands. Third, facing the big datasets generated by the use of extremely heterogeneous networks, diverse communication scenarios, large numbers of antennas, wide bandwidths, and new service requirements, 6G networks will enable a new range of smart applications with the aid of artificial intelligence (AI) and big data technologies. Fourth, network security will have to be strengthened when developing 6G networks. This article provides a comprehensive survey of recent advances and future trends in these four aspects. Clearly, 6G with additional technical requirements beyond those of 5G will enable faster and further communications to the extent that the boundary between physical and cyber worlds disappears.

/pdf/towards-6g-wireless-communication-networks-vision-enabling-2tj7a36yux.pdf

Towards 6G wireless communication networks: vision, enabling technologies, and new paradigm shifts

Internet of Things (IoT) is reshaping the incumbent industry to smart industry featured with data-driven decision-making. However, intrinsic features of IoT result in a number of challenges, such as decentralization, poor interoperability, privacy, and security vulnerabilities. Blockchain technology brings the opportunities in addressing the challenges of IoT. In this paper, we investigate the integration of blockchain technology with IoT. We name such synthesis of blockchain and IoT as blockchain of things (BCoT). This paper presents an in-depth survey of BCoT and discusses the insights of this new paradigm. In particular, we first briefly introduce IoT and discuss the challenges of IoT. Then, we give an overview of blockchain technology. We next concentrate on introducing the convergence of blockchain and IoT and presenting the proposal of BCoT architecture. We further discuss the issues about using blockchain for fifth generation beyond in IoT as well as industrial applications of BCoT. Finally, we outline the open research directions in this promising area.

Blockchain for Internet of Things: A Survey

Providing ubiquitous connectivity to diverse device types is the key challenge for 5G and beyond 5G (B5G). Unmanned aerial vehicles (UAVs) are expected to be an important component of the upcoming wireless networks that can potentially facilitate wireless broadcast and support high rate transmissions. Compared to the communications with fixed infrastructure, UAV has salient attributes, such as flexible deployment, strong line-of-sight connection links, and additional design degrees of freedom with the controlled mobility. In this paper, a comprehensive survey on UAV communication toward 5G/B5G wireless networks is presented. We first briefly introduce essential background and the space–air–ground integrated networks, as well as discuss related research challenges faced by the emerging integrated network architecture. We then provide an exhaustive review of various 5G techniques based on UAV platforms, which we categorize by different domains, including physical layer, network layer, and joint communication, computing, and caching. In addition, a great number of open research problems are outlined and identified as possible future research directions.

UAV Communications for 5G and Beyond: Recent Advances and Future Trends

Providing ubiquitous connectivity to diverse device types is the key challenge for 5G and beyond 5G (B5G). Unmanned aerial vehicles (UAVs) are expected to be an important component of the upcoming wireless networks that can potentially facilitate wireless broadcast and support high rate transmissions. Compared to the communications with fixed infrastructure, UAV has salient attributes, such as flexible deployment, strong line-of-sight (LoS) connection links, and additional design degrees of freedom with the controlled mobility. In this paper, a comprehensive survey on UAV communication towards 5G/B5G wireless networks is presented. We first briefly introduce essential background and the space-air-ground integrated networks, as well as discuss related research challenges faced by the emerging integrated network architecture. We then provide an exhaustive review of various 5G techniques based on UAV platforms, which we categorize by different domains including physical layer, network layer, and joint communication, computing and caching. In addition, a great number of open research problems are outlined and identified as possible future research directions.

Internet of Things (IoT) computing offloading is a challenging issue, especially in remote areas where common edge/cloud infrastructure is unavailable. In this paper, we present a space-air-ground integrated network (SAGIN) edge/cloud computing architecture for offloading the computation-intensive applications considering remote energy and computation constraints, where flying unmanned aerial vehicles (UAVs) provide near-user edge computing and satellites provide access to the cloud computing. First, for UAV edge servers, we propose a joint resource allocation and task scheduling approach to efficiently allocate the computing resources to virtual machines (VMs) and schedule the offloaded tasks. Second, we investigate the computing offloading problem in SAGIN and propose a learning-based approach to learn the optimal offloading policy from the dynamic SAGIN environments. Specifically, we formulate the offloading decision making as a Markov decision process where the system state considers the network dynamics. To cope with the system dynamics and complexity, we propose a deep reinforcement learning-based computing offloading approach to learn the optimal offloading policy on-the-fly, where we adopt the policy gradient method to handle the large action space and actor-critic method to accelerate the learning process. Simulation results show that the proposed edge VM allocation and task scheduling approach can achieve near-optimal performance with very low complexity and the proposed learning-based computing offloading algorithm not only converges fast but also achieves a lower total cost compared with other offloading approaches.

Space/Aerial-Assisted Computing Offloading for IoT Applications: A Learning-Based Approach

In this article, an aerial-ground cooperative vehicular networking architecture is proposed. Multiple unmanned aerial vehicles (UAVs), forming an aerial subnetwork, aid the ground vehicular subnetwork through air-to-air (A2A) and air-to-ground (A2G) communications. UAVs can be dispatched to areas of interest to collect information, and transmit it to ground vehicles. Moreover, UAVs can act as intermediate relays due to their flexible mobility when network partitions happen in the ground vehicular subnetwork. With the assistance of UAVs, the twolayer cooperative networking can facilitate applications such as disaster rescue and polluted area investigation. Potential research issues and challenges in multi-UAV-aided vehicular networks are presented and discussed, which can shed light on extending the applications of vehicular networks in an extreme environment.

Multi-UAV-Aided Networks: Aerial-Ground Cooperative Vehicular Networking Architecture

The ever increasing mobile data demands have posed significant challenges in the current radio access networks, while the emerging computation- heavy Internet of Things applications with varied requirements demand more flexibility and resilience from the cloud/edge computing architecture. In this article, to address the issues, we propose a novel air-ground integrated mobile edge network (AGMEN), where UAVs are flexibly deployed and scheduled, and assist the communication, caching, and computing of the edge network. Specifically, we present the detailed architecture of AGMEN, and investigate the benefits and application scenarios of drone cells, and UAV-assisted edge caching and computing. Furthermore, the challenging issues in AGMEN are discussed, and potential research directions are highlighted.

Air-Ground Integrated Mobile Edge Networks: Architecture, Challenges, and Opportunities

The demand for vehicular mobile data services has increased exponentially, which necessitates alternative data pipes for vehicular users other than the cellular network and dedicated short-range communication. In this paper, we study the performance of underlaid vehicular device-to-device (V-D2D) communications, where the cellular uplink resources are reused by V-D2D communications, considering the characteristics of the vehicular network. Specifically, we model the considered urban area by a grid-like street layout, with nonhomogeneous distribution of vehicle density. We then propose to employ a joint power control and mode selection scheme for the V-D2D communications. In the scheme, we use channel inversion to control the transmit power, in order to determine transmit power based on path loss rather than instantaneous channel state information (CSI), and avoid severe interference due to excessively large transmit power; the transmission mode is selected based on the biased channel quality, where D2D mode is chosen when the biased D2D link quality is not worse than the cellular uplink quality. Under the proposed scheme, two performance metrics of V-D2D underlaid cellular networks, i.e., signal-to-interference-plus-noise outage probability and link/network throughput, are theoretically analyzed. Simulation results validate our analysis and show the impacts of design parameters on the network performance.

Performance Analysis of Vehicular Device-to-Device Underlay Communication

To satisfy the requirement of the future ocean communication and maritime transportation, in this paper, an integrated space-air-ground-sea communication control system based on mobile computing technology is proposed to rescue a water container. Specifically, unmanned surface vehicle (USV), as a flexible and lightweight intelligent device deployment integration platform, is the main tool to move towards the water container. However, how to sense the real-time navigation status information of the USV, integrate the information, and eventually distribute it to the ground control center, is still a difficult point for us. To successfully rescue the water container, three aspects of research are needed: information collection of the USV, information fusion, and data distribution to the ground control center. For the information collection part, we mainly use nine-axis, ultrasonic, global positioning system (GPS), and ultra wide band (UWB) sensors to complete the information collection for the USV. For the information fusion part, we set up a computational model to solve it. The USV computational model in previous works is mainly based on large ships, ignoring the modeling of wind, wave, and current for small underactuated USV. We use the classical Nomoto model, combined with the actual any slight wind, wave, and current forces on the USV, and finally combined with the proportion integration differentiation (PID) algorithm to model the USV. For the data distribution to the ground control center part, we have set up a communication protocol for the USV so that it can communicate normally. In addition, we wrote a Browser/Server (B/S) architecture to enable the ground control center to communicate with the host computer. Finally, our proposed control and communication schemes are carried out on actual USV. The real experiments show that the proposed schemes can reduce the ship surge and satisfy the ship navigation.

/pdf/joint-communication-and-control-for-small-underactuated-usv-537f21o988.pdf

Joint Communication and Control for Small Underactuated USV Based on Mobile Computing Technology

Data delivery in vehicular networks (VANETs) is a challenging task due to the high mobility and constant topological changes. In common routing protocols, multihop V2V communications suffer from higher network delay and lower packet delivery ratio (PDR), and excessive dependence on GPS may pose threat on individual privacy. In this paper, we propose a novel data delivery scheme for vehicular networks in urban environments, which can improve the routing performance without relying on GPS. A fuzzy-rule-based wireless transmission approach is designed to optimize the relay selection considering multiple factors comprehensively, including vehicle speed, driving direction, hop count, and connection time. Wireless V2V transmission and wired transmissions among RSUs are both utilized, since wired transmissions can reduce the delay and improve the reliability. Each RSU is equipped with a machine learning system (MLS) to make the selected relay link more reliably without GPS through predicting vehicle speed at next moment. Experiments show the validity and rationality of the proposed method.

/pdf/a-fuzzy-rule-based-data-delivery-scheme-in-vanets-with-10x42gus4h.pdf

Yi Zhou

Papers

Multi-UAV-Aided Networks: Aerial-Ground Cooperative Vehicular Networking Architecture

Air-Ground Integrated Mobile Edge Networks: Architecture, Challenges, and Opportunities

Performance Analysis of Vehicular Device-to-Device Underlay Communication

Joint Communication and Control for Small Underactuated USV Based on Mobile Computing Technology

A Fuzzy-Rule Based Data Delivery Scheme in VANETs with Intelligent Speed Prediction and Relay Selection