Sensor-Assisted Global Motion Estimation for Efficient UAV Video Coding

This is the author accepted manuscript. The final version is available from IEEE via the DOI in this record.In this paper, we propose a novel video coding scheme to significantly reduce the coding complexity and enhance overall coding efficiency in videos acquired by high mobility devices such as unmanned aerial vehicles (UAVs). In order to reduce the encoded data bits and encoding time to facilitate real-time data transmission, as well as minimize the image distortion caused by the jitter of onboard camera, a sensor-assisted global motion estimation (GMV) algorithm is designed to calculate perspective transformation model and global motion vectors, which are used in both the inter-frame coding to improve the coding efficiency and intra-frame coding to reduce block search complexity. We conducted comprehensive simulation experiments on official HM-16.10 codec and the performance results show the proposed method can achieve faster block search by 50% to 60% speedup and lower bitrate by 15% to 30% compared with standard HEVC coding software

Optimization and Communication in UAV Networks

UAVs are becoming a reality and attract increasing attention. They can be remotely controlled or completely autonomous and be used alone or as a fleet and in a large set of applications. They are constrained by hardware since they cannot be too heavy and rely on batteries. Their use still raises a large set of exciting new challenges in terms of trajectory optimization and positioning when they are used alone or in cooperation, and communication when they evolve in swarm, to name but a few examples. This book presents some new original contributions regarding UAV or UAV swarm optimization and communication aspects

Accuracy Assessment of Low Cost UAV Based City Modelling for Urban Planning

This paper presents an Unmanned Aerial Vehicles (UAV) based 3D city modelling approach to be used in managing and planning urban areas. While the urban growth is rapidly increasing in many places of the world, the conventional techniques do not respond to the changing environment simultaneously. For effective planning, high-resolution remote sensing is a tool for the production of 3D digital city models. In this study, it is aimed at designing the remote sensing by UAV through urban terrain. Using all the information produced from UAV imagery, high-accurate 3D city models are obtained. The analysis of XYZ data of the derived from 3D model using UAV photogrammetry revealed similar products as the terrestrial surveys which are commonly used for the last development plans and city maps. The experimental results show the effectiveness of the UAV-based 3D city modelling. The assessed accuracy of the UAV photogrammetry proved that urban planners can use it as the main tool of data collection for boundary mapping, changes monitoring and topographical surveying instead of GPS/GNSS surveying

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

Cellular, Wide-Area, and Non-Terrestrial IoT: A Survey on 5G Advances and the Road Towards 6G

The next wave of wireless technologies is proliferating in connecting things among themselves as well as to humans. In the era of the Internet of things (IoT), billions of sensors, machines, vehicles, drones, and robots will be connected, making the world around us smarter. The IoT will encompass devices that must wirelessly communicate a diverse set of data gathered from the environment for myriad new applications. The ultimate goal is to extract insights from this data and develop solutions that improve quality of life and generate new revenue. Providing large-scale, long-lasting, reliable, and near real-time connectivity is the major challenge in enabling a smart connected world. This paper provides a comprehensive survey on existing and emerging communication solutions for serving IoT applications in the context of cellular, wide-area, as well as non-terrestrial networks. Specifically, wireless technology enhancements for providing IoT access in fifth-generation (5G) and beyond cellular networks, and communication networks over the unlicensed spectrum are presented. Aligned with the main key performance indicators of 5G and beyond 5G networks, we investigate solutions and standards that enable energy efficiency, reliability, low latency, and scalability (connection density) of current and future IoT networks. The solutions include grant-free access and channel coding for short-packet communications, non-orthogonal multiple access, and on-device intelligence. Further, a vision of new paradigm shifts in communication networks in the 2030s is provided, and the integration of the associated new technologies like artificial intelligence, non-terrestrial networks, and new spectra is elaborated. Finally, future research directions toward beyond 5G IoT networks are pointed out.Comment: Submitted for review to IEEE CS&