Beyond D2D: Full Dimension UAV-to-Everything Communications in 6G
Reads0
Chats0
TLDR
A UAV-to-Everything (U2X) networking is proposed, which enables the UAVs to adjust their communication modes full dimensionally according to the requirements of their sensing applications, and a reinforcement learning-based mathematical framework for U2X communications is proposed.Abstract:
In this paper, we consider an Internet of unmanned aerial vehicles (UAVs) over cellular networks, where UAVs work as aerial users to collect various sensory data, and send the collected data to their transmission destinations over cellular links. Unlike the terrestrial users in the conventional cellular networks, different UAVs have various communication requirements due to their sensing applications, and a more flexible communication framework is in demand. To tackle this problem, we propose a UAV-to-Everything (U2X) networking, which enables the UAVs to adjust their communication modes full dimensionally according to the requirements of their sensing applications. In this article, we first introduce the concept of U2X communications, and elaborate on its three communication modes. Afterwards, we discuss the key techniques of the U2X communications, including joint sensing and transmission protocol, UAV trajectory design, and radio resource management. A reinforcement learning-based mathematical framework for U2X communications is then proposed. Finally, the extensions of the U2X communications are presented.read more
Citations
More filters
Journal ArticleDOI
6G Internet of Things: A Comprehensive Survey
Dinh C. Nguyen,Ming Ding,Pubudu N. Pathirana,Aruna Seneviratne,Jun Li,Dusit Niyato,Octavia A. Dobre,H. Vincent Poor +7 more
TL;DR: In this paper, the authors explore the emerging opportunities brought by 6G technologies in IoT networks and applications, by conducting a holistic survey on the convergence of 6G and IoT, and highlight interesting research challenges and point out potential directions to spur further research in this promising area.
Journal ArticleDOI
Survey on 6G Frontiers: Trends, Applications, Requirements, Technologies and Future Research
Chamitha de Alwis,Anshuman Kalla,Quoc-Viet Pham,Pardeep Kumar,Kapal Dev,Won-Joo Hwang,Madhusanka Liyanage +6 more
TL;DR: In this paper, the authors provide a comprehensive survey of the current developments towards 6G and elaborate the requirements that are necessary to realize the 6G applications, and summarize lessons learned from state-of-the-art research and discuss technical challenges that would shed a new light on future research directions toward 6G.
Journal ArticleDOI
A Survey on Beyond 5G Network With the Advent of 6G: Architecture and Emerging Technologies
TL;DR: A brief overview of the added features and key performance indicators of 5G NR is presented and a next-generation wireless communication architecture that acts as the platform for migration towards beyond 5G/6G networks is proposed.
Journal ArticleDOI
6G Internet of Things: A Comprehensive Survey
TL;DR: In this paper , the authors explore the emerging opportunities brought by 6G technologies in IoT networks and applications, by conducting a holistic survey on the convergence of 6G and IoT, and highlight interesting research challenges and point out potential directions to spur further research in this promising area.
Journal ArticleDOI
A Survey on Cellular-connected UAVs: Design Challenges, Enabling 5G/B5G Innovations, and Experimental Advancements
TL;DR: In this article, the authors present an in-depth exploration of integration synergies between 5G/B5G cellular systems and UAV technology, where the UAV is integrated as a new aerial user equipment (UE) to already deployed cellular networks.
References
More filters
Book
Reinforcement Learning: An Introduction
TL;DR: This book provides a clear and simple account of the key ideas and algorithms of reinforcement learning, which ranges from the history of the field's intellectual foundations to the most recent developments and applications.
Journal ArticleDOI
Human-level control through deep reinforcement learning
Volodymyr Mnih,Koray Kavukcuoglu,David Silver,Andrei Rusu,Joel Veness,Marc G. Bellemare,Alex Graves,Martin Riedmiller,Andreas K. Fidjeland,Georg Ostrovski,Stig Petersen,Charles Beattie,Amir Sadik,Ioannis Antonoglou,Helen King,Dharshan Kumaran,Daan Wierstra,Shane Legg,Demis Hassabis +18 more
TL;DR: This work bridges the divide between high-dimensional sensory inputs and actions, resulting in the first artificial agent that is capable of learning to excel at a diverse array of challenging tasks.
Journal ArticleDOI
Technical Note : \cal Q -Learning
Chris Watkins,Peter Dayan +1 more
TL;DR: This paper presents and proves in detail a convergence theorem forQ-learning based on that outlined in Watkins (1989), showing that Q-learning converges to the optimum action-values with probability 1 so long as all actions are repeatedly sampled in all states and the action- values are represented discretely.
Journal ArticleDOI
6G Wireless Networks: Vision, Requirements, Architecture, and Key Technologies
Zhengquan Zhang,Yue Xiao,Zheng Ma,Ming Xiao,Zhiguo Ding,Xianfu Lei,George K. Karagiannidis,Pingzhi Fan +7 more
TL;DR: This article presents a large-dimensional and autonomous network architecture that integrates space, air, ground, and underwater networks to provide ubiquitous and unlimited wireless connectivity and identifies several promising technologies for the 6G ecosystem.