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Unmanned aerial vehicles (UAVs) are playing an increasingly important role in military, public, and civilian applications. More recently, UAVs have become a topic of central research interest in the wireless communication community. For example, the 3GPP standardization body has recently worked on a study item to facilitate seamless integration of UAVs into future cellular networks.

UAVs, also referred to as drones, can be exploited in different ways to enhance cellular communications. On the one hand, dedicated UAVs can be used as airborne wireless access points or relay nodes to further improve terrestrial communications. We refer to this type of UAV applications as UAV Assisted Cellular Communications. On the other hand, UAVs may be exploited for sensing purposes by leveraging their advantages such as on-demand deployment, larger service coverage compared with the conventional fixed sensor nodes, and flexible spatial network architecture. We refer to this category of UAV applications as Cellular-Assisted UAV Sensing. Despite the many benefits due to their mobility, UAVs still suffer from some practical constraints such as limited battery power, restrictions due to no-fly zones, and safety concerns. It is therefore essential to develop new communication, signal processing, and optimization frameworks in support of high data-rate UAV communication systems assisting terrestrial cellular communications to enable ultra-reliable and real-time sensing applications in future wireless cellular networks.

While UAV assisted cellular networks are still in their early stages for supporting communication and sensing applications, they have attracted a significant amount of attention from both academic and industry researchers in the disciplinary fields of communication, control, signal processing, computer science, and information theory. In this Best Readings, we introduce several books, archival papers and special issues on the topic of UAV assisted communication and sensing applications over cellular networks.

Issued February 2020


Lingyang Song, Peking University, China
Rui Zhang, National University of Singapore, Singapore
Walid Saad, Virginia Tech, USA

Zhu Han, University of Houston, USA
Robert Schober, Friedrich-Alexander-University Erlangen-Nuremberg, Germany

Editorial Staff

Matthew C. Valenti
Editor-in-Chief, ComSoc Best Readings
West Virginia University
Morgantown, WV, USA

Xianbin Wang
Associate Editor-in-Chief, ComSoc Best Readings
Western University
London, ON, Canada


W. Saad, M. Bennis, M. Mozaffari, and X. Lin, Wireless Communications and Networking for Unmanned Aerial Vehicles, Cambridge University Press, 2020.
This book provides a comprehensive overview of wireless communication and networking with UAVs. The topics range from the fundamental physical layer, standardization efforts, and channel modeling for UAV-BSs and UAV-UEs to the performance analysis, design, and optimization of their deployment, trajectory, multiple access, resource management, and multi-antenna features.

H. Zhang, L. Song, and Z. Han, Unmanned Aerial Vehicle Applications over Cellular Networks for 5G and Beyond, Springer, 2020.
This book elaborates on UAV technologies and applications in cellular networks and carves out the role that analytical and experimental engineering has to play in UAV research and development. This is a useful guide for communication and signal processing engineers, computer and information scientists, applied mathematicians and statisticians, as well as systems engineers.

Y. Zeng, I. Guvenc, R. Zhang, G. Geraci, and D. W. Matolak (Eds), UAV Communications for 5G and Beyond, Wiley, 2020.
This book gives a comprehensive overview on the integration of UAV communications with cellular networks. It starts with some fundamentals of UAV communications, followed by a thorough treatment of the two paradigms where UAVs are integrated as new aerial users or as communication platforms, respectively. Last, the merging of UAV communications and some other advanced communication techniques are discussed. One major feature of the book is that it provides the analytical, design, and experimental perspectives from both academia and industry, and is thus a good starting reference for researchers working on relevant areas.  

K. Namuduri, S. Chaumette, J. Kim, and J. Sterbenz (Editors), UAV Networks and Communications, Cambridge University Press, 2017.
This book focuses on the communications and networking aspects of UAVs and aims to provide the fundamental knowledge needed to pursue research in the field. It covers the foundational concepts of the topic and offers detailed insights into the state of the art of UAVs and UAV networks, discussing the regulations, policies, and procedures for deployment, along with demonstrations, test-beds, and practical real-world applications in areas.

Special Issues

Unmanned Aerial Vehicles over Internet of Things,” IEEE Internet-of-Things Journal, vol. 6, no. 2, pp. 1636-1905, April 2019.

Integrating UAVs into 5G and Beyond,IEEE Wireless Communications, vol. 26, no. 1, pp. 10-71, February 2019.

Airborne Communication Networks,” IEEE Journal on Selected Areas in Communications, vol. 36, no. 9, pp. 1903-2152, September 2018.

Wireless Communications, Networking, and Positioning with Unmanned Aerial Vehicles,” IEEE Communications Magazine, vol. 54, no. 5, pp. 24-73, May 2016.  

Tutorials and Surveys

H. Zhang, L. Song, Z. Han, and H. V. Poor, “Cooperation Techniques for a Cellular Internet of Unmanned Aerial Vehicles,” IEEE Wireless Communications, vol. 26, no. 5, October 2019.
This article applies cooperation techniques to improve the Quality-of-Service (QoS) of the cellular link between the UAV and the BS in the cellular Internet of UAVs. This article first proposes a cooperative sense-and-send protocol, and then studies trajectory design and radio resource management to support the cooperative cellular Internet of UAVs. Some potential extensions of the related topics are also discussed.

A. Fotouhi, H. Qiang, M. Ding, M. Hassan, L. Giordano, A. Garcia-Rodriguez and J. Yuan, “Survey on UAV Cellular Communications: Practical Aspects, Standardization Advancements, Regulation, and Security Challenges,” IEEE Communications Surveys & Tutorials, vol. 21, no. 4, Fourth Quarter 2019.
This survey provides a comprehensive review on various studies on UAV communications in academia, industry, and standardization activities. Moreover, the deployment and operation of UAVs in cellular networks are investigated from regulations and cyber-security perspectives.

M. Mozaffari, W. Saad, M. Bennis, Y. Nam and M. Debbah, “A Tutorial on UAVs for Wireless Networks: Applications, Challenges, and Open Problems,” IEEE Communications Surveys & Tutorials, vol. 21, no. 3, pp. 2334-2360, Third Quarter 2019.
This tutorial provides a comprehensive overview on the use of UAVs as base stations and users in wireless networks. The paper identifies key challenges, opportunities, fundamental tradeoffs, and open problems associated with various use cases of UAVs in wireless networks. In addition, the paper presents an in-depth overview of mathematical tools and frameworks needed for analyzing, designing, and optimizing UAV-based wireless communication systems.

I. Bor-Yaliniz, M. Salem, G. Senerath, and H. Yanikomeroglu, “Is 5G Ready for Drones: A Look into Contemporary and Prospective Wireless Networks from a Standardization Perspective”, IEEE Wireless Communications, vol. 26, no. 1, pp. 18-27, February 2019.
This paper studies how UAV base stations and drone users can be integrated into 5G systems. The authors provide a very comprehensive overview on the challenges facing this integration. They also highlight important open issues of standardization process, either via application of current standards or by providing modifications toward further enhancements that can realize the vision of 5G-enabled drones.

W. Shi, H. Zhou, J. Li, W. Xu, N. Zhang, and X. Shen, “Drone Assisted Vehicular Networks: Architecture, Challenges and Opportunities”, IEEE Network, vol. 32, no. 3, pp. 130-137, May/June 2018.
This article introduces the drone assisted vehicular networks (DAVNs) to provide ubiquitous connections for vehicles by efficiently integrating the communication and networking technologies of drones and connected vehicles. This article first proposes a comprehensive architecture of the DAVN and then present the challenges and research opportunities of DAVNs. Finally, a case study is provided to demonstrate that the performance of vehicular networks can be significantly enhanced with the proposed DAVN architecture.

Y. Zeng, R. Zhang, and T. J. Lim, “Wireless Communications with Unmanned Aerial Vehicles: Opportunities and Challenges,” IEEE Communications Magazine, vol. 54, no. 5, pp. 36-42, May 2016.
This is one of the earliest articles that gives a comprehensive overview on UAV-assisted wireless communications. It firstly provides an insightful envision on the three typical use cases of UAV-assisted communications, followed by the discussions of basic networking architecture, main channel characteristics, key design considerations, as well as the new opportunities to be exploited.

Standards-Related Articles

G. Geraci, A. G.-Rodriguez, L. G. Giordano, D. López-Pérez, and E. Björnson, “Understanding UAV Cellular Communications: From Existing Networks to Massive MIMO,” IEEE Access, vol. 6, pp. 67853-67865, November 2018.
This paper analyzes UAV cellular communications by following the recent trends from the industry, academia, and the standardization fora. Through a realistic side-by-side comparison of a present-day cellular network and a next-generation massive MIMO system, the authors evaluate the capability and reliability of the downlink command and control channel and discuss how to further enhance UAV cellular communications.

X. Lin, V. Yajnanarayana, S. D. Muruganathan, S. Gao, H. Asplund, H.-L. Maattanen, M. Bergstrom, S. Euler, and Y.-P. E. Wang, “The Sky Is Not the Limit: LTE for Unmanned Aerial Vehicles,” IEEE Communications Magazine, vol. 56, no. 4, pp. 204-210, April 2018.
This article gives a comprehensive overview of the LTE connectivity for low-altitude small UAVs. This article first introduces the different propagation conditions for UAVs and mobiles on the ground with measurement and ray tracing results, and then sheds light on the feasibility of providing connectivity for UAVs. At the end of this article, several ideas to improve LTE connectivity are presented.

H. C. Nguyen, R. Amorim, J. Wigard, I. Z. Kovács, T. B. Sørensen, and P. E. Mogensen, “How to Ensure Reliable Connectivity for Aerial Vehicles Over Cellular Networks,” IEEE Access, vol. 6, pp. 12304-12317, February 2018.
To enable the coexistence of both aerial and terrestrial users, this paper analyzes two interference mitigation solutions in current LTE networks: interference cancellation and antenna beam selection, and shows that each of these can obtain up to 30% throughput gain and above 99% radio connectivity. This paper also proposes an inter-cell interference mechanism for aerial command and control traffic.

B. V. D. Bergh, A. Chiumento, and S. Pollin, “LTE in the Sky: Trading Off Propagation Benefits with Interference Costs for Aerial Nodes,” IEEE Communications Magazine, vol. 54, no. 5, pp. 44-50, May 2016.
This article utilizes LTE for downlink data and uplink control of UAVs. Two scenarios are considered in which UAVs act as base station transmitting in the downlink or UEs transmitting in the uplink. The paper highlights the fact that the current LTE networks require significant modifications for a smooth integration of LTE-enabled UAVs.

Topic: Channel Measurement and Modeling

A. A. Khuwaja, Y. Chen, N. Zhao, M.-S. Alouini, and P. Dobbins, “A Survey of Channel Modeling for UAV Communications,” IEEE Communications Survey & Tutorials, vol. 20, no. 4, pp. 2804-2821, Fourth Quarter 2018.
This is an extensive survey of channel measurement methods for UAV communications. It also discusses various important UAV channel characteristics and outlines future research challenges in this domain.

R. Amorim, H. Nguyen, P. Mogensen, I. Z. Kovács, J. Wigard, and T. B. Sørensen, “Radio Channel Modeling for UAV Communication Over Cellular Networks,IEEE Wireless Communications Letters, vol. 6, no. 4, pp. 514-517, August 2017.
This letter investigates the radio propagation characteristics of ground-to-air channels. Field measurements are conducted in live LTE networks in the 800 MHz frequency band with a commercial UAV, and the analysis results show that a height-dependent parameter is necessary to describe the channel for UAVs at different altitudes.

T. J. Willink, C. C. Squires, G. W. K. Colman, and M. T. Muccio, “Measurement and Characterization of Low-Altitude Air-to-Ground MIMO Channels,” IEEE Transactions on Vehicular Technology, vol. 65, no. 4, pp. 2637-2648, April 2016.
This paper reports a measurement of air-to-ground MIMO channels at 915 MHz. The analysis shows that spatial diversity is significant due to the near-field scattering by the airframe of the UAV, despite the sparse multipath environment.

Topic: Network Architectures, Communication Protocols and Economic Frameworks

L. Liu, S. Zhang, and R. Zhang, “CoMP in the Sky: UAV Placement and Movement Optimization for Multi-user Communications,” IEEE Transactions on Communications, vol. 67, no. 8, pp. 5645-5658, August 2019.
This paper proposes a new coordinate multipoint (CoMP) based network architecture  for UAV-assisted wireless communications, which harnesses both the benefits of interference mitigation via CoMP and high mobility of UAVs to achieve effective multi-UAV multi-user communications. The paper first derives the closed-form upper and lower bounds for the achievable rate of the ground users by using random matrix theory, based on which the UAV placement and movement are optimized to maximize the minimum of the users’ average rate. Some insightful results are observed based on the optimized solution, which are further validated by numerical simulations. 

M. E. Mkiramweni, C. Yang, J. Li, and Z. Han, “Game-Theoretic Approaches for Wireless Communications with Unmanned Aerial Vehicles,” IEEE Wireless Communications, vol. 25, no. 6, pp. 104-112, December 2018.
This article presents game-theoretic approaches to address the challenges in UAV networks. This article first gives an overview of the existing game-theoretic solutions and identifies the corresponding problems in UAV communications. Then, the shortcomings of existing game-theoretic approaches are discussed and a mean-field game is proposed to solve the interference management problem in massive UAV networks.

M. Gapeyenko, V. Petrov, D. Moltchanov, S. Andreev, N. Himayat, and Y. Koucheryavy, “Flexible and Reliable UAV-Assisted Backhaul Operation in 5G mmWave Cellular Networks,” IEEE Journal on Selected Areas in Communications, vol. 36, no. 11, pp. 2486-2496, November 2018.
This paper proposes using UAV relays to offer significant benefits for mmWave backhauling. The authors propose an analytical framework which takes the dynamic blockage and the heterogeneous mobility of blockers into account to quantify the benefits.

F. Tang, Z. M. Fadlullah, N. Kato, F. Ono, and F. Miura, “AC-POCA: Anticoordination Game Based Partially Overlapping Channels Assignment in Combined UAV and D2D-Based Networks”, IEEE Transactions on Vehicular Technology, vol. 67, no. 2, pp. 1672-1683, February 2018.
In this paper, UAVs are utilized to promptly construct the device-to-device (D2D) enabled wireless network. To alleviate the interference, a distributed anticoordination game based partially overlapping channel assignment algorithm referred to as AC-POCA is proposed. The upper bound of AC-POCA (i.e., price of anarchy) is analytically evaluated, which is corroborated by simulation results.

Topic: Multiple Access Schemes

Y. Liu, Z. Qin, Y. Cai, Y. Gao, G. Y. Li, and A. Nallanathan, “UAV Communications Based on Non-Orthogonal Multiple Access,” IEEE Wireless Communications, vol. 26, no. 1, pp. 52-57, February 2019.
This article develops a novel framework for UAV networks with massive access capability supported by Non-Orthogonal Multiple Access (NOMA) and elaborates on three cases studies on NOMA-enabled UAV networks.

P. Chandhar, D. Danev, and E. G. Larsson, “Massive MIMO for Communications With Drone Swarms,” IEEE Transactions on Wireless Communications, vol. 17, no. 3, pp. 1604-1629, March 2018.
This paper exploits Massive MIMO for the communication between a ground station with an antenna array and a swarm of UAVs with a single antenna. The achievable uplink capacity is derived and the antenna spacing is also optimized to maximize the capacity.

Q. Wu, Y. Zeng, and R. Zhang, “Joint Trajectory and Communication Design for Multi-UAV Enabled Wireless Networks,” IEEE Transactions on Wireless Communications, vol. 17, no. 3, pp. 2109-2121, March 2018.
This paper uses multiple UAV base stations to serve a group of users on the ground. To achieve fairness among the users, this paper maximizes the minimum downlink throughput over all ground users by optimizing the multiuser communication scheduling and user association jointly with the UAV’s trajectory and power control.

Topic: Interference Mitigation and Drone Deployment

L. Li, Y. Xu, Z. Zhang, J. Yin, W. Chen, and Z. Han, “A Prediction-Based Charging Policy and Interference Mitigation Approach in the Wireless Powered Internet of Things,” IEEE Journal on Selected Areas in Communications, vol. 37, no. 2, pp. 439-451, February 2019.
This paper develops a novel wireless power transmission (WPT) system, where a UAV is employed to charge IoT devices. In order to improve the energy efficiency of the WP-IoT system, the interference mitigation problem is modeled as a mean field game to analyze the performance for a large number of IoT devices.

I. Bor-Yaliniz, S. S. Szyszkowicz, and H. Yanikomeroglu, “Environment Aware Drone-Base-Station Placements in Modern Metropolitans,” IEEE Wireless Communications Letters, vol. 7, no. 3, pp. 372-375, June 2018.
This paper studies the problem of optimized drone base station deployment for providing on-demand capacity to ground networks. The authors develop a new approach to deploy the drones in an urban area. The proposed approach relies on an ITU channel model utilizing important information about the environment, such as the shapes of the buildings. The developed solution can effectively optimize the parameters of the selected ITU model, so that it can be used for altitudes both strictly lower and higher than building roof-tops.

M. Mozaffari, W. Saad, M. Bennis, and M. Debbah, “Unmanned Aerial Vehicle With Underlaid Device-to-Device Communications: Performance and Tradeoffs,” IEEE Transactions on Wireless Communications, vol. 15, no. 6, pp. 3949-3963, June 2016.
This paper analyzes the performance of a wireless network in which a UAV base station provides wireless communications to ground users in coexistence with a device-to-device (D2D) communication network. A tractable analytical framework for the coverage and rate analysis is derived. Analytical results show that: 1) there exists an optimal UAV altitude that maximizes the system performance, and 2) there exists a fundamental tradeoff between coverage and delay.

V. Sharma, M. Bennis, and R. Kumar, “UAV-Assisted Heterogeneous Networks for Capacity Enhancement,” IEEE Communications Letters, vol. 20, no. 6, pp. 1207-1210, June 2016.
This letter investigates the UAV assignment problem over geographical areas subject to data traffic demands. A mapping algorithm is developed to maintain the overall network connectivity, in which UAVs are matched to a particular geographical area. It is shown that the proposed scheme can provide a higher capacity and prolonged connectivity.

Topic: Trajectory and Resource Management

W. Shi, J. Li, N. Cheng, F. Lyu, S. Zhang, H. Zhou, and X. Shen, “Multi-Drone 3D Trajectory Planning and Scheduling in Drone Assisted Radio Access Networks”, IEEE Transactions on Vehicular Technology, vol. 68, no. 8, pp. 8145-8158, August  2019.
To improve user fairness and network performance, this paper designs 3D trajectories of multiple drone base stations (DBSs) in the drone-assisted radio access networks. With the objective of minimizing the average DBS-to-user pathloss, a multi-DBS 3D trajectory planning and scheduling algorithm is developed. Compared with the static DBS deployment, the proposed trajectory planning algorithm can significantly improve network performance and user fairness.

Y. Sun, D. Xu, D.W. K. Ng, and R. Schober, “Optimal 3D-Trajectory Design and Resource Allocation for Solar-Powered UAV Communication Systems,” IEEE Transactions on Communications, vol. 67, no. 6, pp. 4281-4298, June 2019.
This paper studies a solar-powered UAV communication system serving multiple ground users. Offline and online algorithms for joint 3D aerial trajectory and wireless resource allocation are developed to maximize the system sum throughput over a given time period.

S. Zhang, H. Zhang, Q. He, K. Bian, and L. Song, “Joint Trajectory and Power Optimization for UAV Relay Networks,” IEEE Communications Letters, vol. 22, no. 1, pp. 161-164, January 2018.
The goal of this letter is to optimize the 3D trajectory of the UAV relay and the transmit powers of the UAV and the mobile device for minimization of the outage probability of the relay network. An analytical expression for the outage probability is derived first, and then an iterative low-complexity algorithm is proposed to solve the optimization problem. The letter confirms that the 3D trajectory design can obtain a better outage probability than the fixed trajectory schemes.

Y. Zeng and R. Zhang, “Energy-Efficient UAV Communication With Trajectory Optimization,” IEEE Transactions on Wireless Communications, vol. 16, no. 6, pp. 3747-3760, March 2017.
This paper focuses on the issue of limited onboard energy for UAV communications. A novel energy-efficient communication framework is proposed to maximize the energy efficiency of UAV, by considering the unique UAV propulsion power consumption that does not exist in the conventional terrestrial communication systems. To this end, the paper derives a rigorous mathematical model for the propulsion power consumption of fixed-wing UAVs as a function of both the UAV velocity and acceleration.

Y. Zeng, R. Zhang, and T. J. Lim, “Throughput Maximization for UAV-Enabled Mobile Relaying Systems,” IEEE Transactions on Communications, vol. 64, no. 12, pp. 4983-4996, December 2016.
This paper proposes a mobile relaying system by employing UAVs. By exploiting the fully controllable high mobility of UAV, the paper proposes a novel framework to jointly design the communication resource allocation and UAV trajectory. For the non-convex trajectory optimization sub-problem, a successive convex approximation technique is first proposed to find high-quality efficient solutions.

Topic: Internet of UAVs

S. Zhang, J. Yang, H. Zhang, and L. Song, “Dual Trajectory Optimization for a Cooperative Internet of UAVs,” IEEE Communications Letter, vol. 23, no. 6, pp. 1093-1096, June 2019.
This letter investigates trajectory design for a cooperative Internet of UAVs in which one UAV can work as a relay to help other UAVs to transmit sensory data to the base station (BS) for further processing. As the trajectory of these two UAVs are coupled, the authors propose a dual trajectory optimization algorithm to minimize the completion time for the sensing tasks. It is shown that the cooperation gains will be more significant when the signal-to-noise ratio (SNR) requirement is higher.

S. Zhang, H. Zhang, B. Di, and L. Song, “Cellular UAV-to-X Communications: Design and Optimization for Multi-UAV Networks,” IEEE Transactions on Wireless Communications, vol. 18, no. 2, pp. 1346-1359, January 2019.
This paper proposes cellular U2V-to-X communications in an OFDMA Internet of UAVs to improve the Quality-of-Service (QoS) by utilizing an intermediate UAV as the relay. A cooperative UAV sense-and-send protocol is first proposed to enable the UAV-to-X communications. Then, a joint resource allocation and speed optimization problem is addressed to maximize the uplink sum-rate.

M. Mozaffari, W. Saad, M. Bennis, and M. Debbah, “Mobile Unmanned Aerial Vehicles (UAVs) for Energy-Efficient Internet of Things Communications,” IEEE Transactions on Wireless Communications, vol. 16, no. 11, pp. 7574-7589, November 2017.
This paper investigates the use of mobile UAVs for energy-efficient data collection in a static and time-varying Internet of Things (IoT) network. The proposed framework minimizes the total transmit power of the IoT devices, while providing sustainable connectivity, by jointly optimizing the 3D locations of UAVs, device-UAV associations, and transmit power of each IoT device.

N. H. Motlagh, T. Taleb, and O. Arouk, “Low-Altitude Unmanned Aerial Vehicles-Based Internet of Things Services: Comprehensive Survey and Future Perspectives,” IEEE Internet of Things Journal, vol. 3, no. 6, pp. 899-922, December 2016.
This paper gives a comprehensive survey on the UAV-based Internet of Things services and presents the relevant key challenges and requirements. These challenges comprise not only technical issues, such as physical collision and communications, but also regulation issues.

M. Gharibi, R. Boutaba, and S. L. Waslander, “Internet of Drones,” IEEE Access, vol. 4, pp. 1148-1162, March 2016.
This paper presents a protype of the Internet of UAVs. The authors propose a layered network control architecture called Internet of Drones (IoD) to coordinate the access of UAVs for various applications. This paper also presents how such an architecture can be organized and addresses two main problems: airspace navigation and coordination. A simulation platform for IoD is implemented to verify the feasibility.

Topic: Machine Learning for UAVs

U. Challita, W. Saad, and C. Bettstetter, “Interference Management for Cellular-Connected UAVs: A Deep Reinforcement Learning Approach,” IEEE Transactions on Wireless Communications, vol. 18, no.4, pp. 2125-2140, April 2019.
This paper develops a deep reinforcement learning algorithm that uses echo state networks to jointly optimize the trajectory of cellular-connected UAV user equipment (UAV-UE) along with their associated resource management. The proposed solution balances the tradeoff between UAV mission time, transmission delay, and interference on the ground UEs caused by UAV transmissions.

L. Xiao, X. Lu, D. Xu, Y. Tang, L. Wang, and W. Zhuang, “UAV Relay in VANETs Against Smart Jamming With Reinforcement Learning,” IEEE Transactions on Vehicular Technology, vol. 67, no. 5, pp. 4087-4097, May 2018.
This paper uses UAVs to relay the message of VANETs against smart jammers. The interactions between a UAV and a jammer can be formulated as a dynamic game, and a policy hill climbing algorithm is proposed to help the VANET resist jamming without being aware of the exact models. Simulation results show that the proposed algorithm can efficiently increase the utility of the VANET compared with a Q-learning-based scheme.

M. Chen, M. Mozaffari, W. Saad, C. Yin, M. Debbah, and C. S. Hong, “Caching in the Sky: Proactive Deployment of Cache-Enabled Unmanned Aerial Vehicles for Optimized Quality-of-Experience,” IEEE Journal on Selected Areas in Communications, vol. 35, no. 5, pp. 1046-1061, May 2017.
This paper studies the proactive deployment of cache-enabled UAVs to improve the quality-of-experience (QoE) of wireless devices in a cloud radio access network. A machine learning algorithm based on the echo state networks (ESNs) is proposed to effectively predict each user’s content request distribution and its mobility pattern, and then the optimal locations of UAVs as well as the content to cache at UAVs are derived.

Topic: Experiments, Prototyping, Field-tests and Applications

Y. Yang, Z. Zheng, K. Bian, L. Song, and Z. Han, “Real-Time Profiling of Fine-Grained Air Quality Index Distribution Using UAV Sensing,” IEEE Internet of Things Journal, vol. 5, no. 1, pp. 186-198, February 2018.
This paper designs a mobile air quality index (AQI) monitoring system mounted on a UAV for real-time fine-grained AQI map generation. A Gaussian plume model on the basis of the neural network (GPM-NN) is proposed to physically characterize the particle dispersion in the air. Based on GPM-NN, a battery efficient and adaptive monitoring algorithm is then proposed to construct an accurate AQI map with the sensed data. The experimental results demonstrate that the designed system can provide a higher prediction accuracy than other existing models, while greatly reducing the power consumption with the adaptive monitoring algorithm.

H. Menouar, I. Guvenc, K. Akkaya, A. S. Uluagac, A. Kadri, and A. Tuncer, “UAV-Enabled Intelligent Transportation Systems for the Smart City: Applications and Challenges, ” IEEE Communications Magazine, vol. 55, no. 3, pp. 22-28, March 2017.
This article studies the applications of UAVs in Intelligent Transportation Systems (ITS) scenarios to provide a reliable and efficient transportation system. Different aspects for ITS applications of UAVs including deployment optimization, data routing, and cybersecurity and privacy are discussed.

N. H. Motlagh, M. Bagaa, and T. Taleb, “UAV-Based IoT Platform: A Crowd Surveillance Use Case,” IEEE Communications Magazine, vol. 55, no. 2, pp. 128-134, February 2017.
This article presents a high-level view of a UAV-based integrative IoT platform for the delivery of IoT services from the sky. As an envisioned use case, the article demonstrates how UAVs can be used for crowd surveillance based on face recognition, and studies the offloading of video data processing to a mobile edge computing (MEC) node. A testbed is also developed which verifies the efficiency of the MEC-based offloading approach.

A. Merwaday, A. Tuncer, A. Kumbhar, and I. Guvenc, “Improved Throughput Coverage in Natural Disasters: Unmanned Aerial Base Stations for Public-Safety Communications,” IEEE Vehicular Technology Magazine, vol.11, no. 4, pp. 53-60, December 2016.
This paper discusses the use of UAV base stations (BSs) in public-safety communications. Two scenarios along with the key techniques are presented. The results show that public-safety communications can significantly benefit from deploying UAV BSs in the event of any damage to the network infrastructure from natural calamities or malevolent attacks.