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Open Access

Blockchain-envisioned unmanned aerial vehicle communications in space-air-ground integrated network: A review

School of Computer and Electronic Information and the Guangxi Key Laboratory of Multimedia Communications and Network Technology, Guangxi University, Nanning 530004, China
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Unmanned Aerial Vehicle (UAV) communications have recently entered a new period of interest, motivated by technological advances and the gradual emergence of the Space-Air-Ground Integrated Network (SAGIN). The current survey aims to capture the use of UAVs in the SAGIN while highlighting the most promising open research topics. The traditional UAV network architecture is not adequate to meet the challenges presented by the SAGIN, and an effective and secure space-air-ground integrated UAV network needs to be constructed. Given its well-distributed management and consensus mechanism, blockchain technology can make up for the deficiency of the traditional UAV network. In this work, we review the role of UAVs in the SAGIN. Then, three applications of the blockchain-envisioned UAV network are introduced through several classifications. Future challenges and the corresponding open research topics are also described.



F. X. Tang, Y. Kawamot, N. Kato, and J. J. Liu, Future intelligent and secure vehicular network toward 6G: Machine-learning approaches, Proc. IEEE, vol. 108, no. 2, pp. 292–307, 2020.


F. Boccardi, R. W. Heath, A. Lozano, T. L. Marzetta, and P. Popovski, Five disruptive technology directions for 5G, IEEE Commun. Mag., vol. 52, no. 2, pp. 74–80, 2014.


M. Agiwal, A. Roy, and N. Saxena, Next generation 5G wireless networks: A comprehensive survey, IEEE Commun. Surveys Tuts., vol. 18, no. 3, pp. 1617–1655, 2016.


R. P. Li, Z. F. Zhao, X. Zhou, G. R. Ding, Y. Chen, Z. Y. Wang, and H. G. Zhang, Intelligent 5G: When cellular networks meet artificial intelligence, IEEE Wireless Commun., vol. 24, no. 5, pp. 175–183, 2017.


J. B. Ni, X. D. Lin, and X. S. Shen, Efficient and secure service-oriented authentication supporting network slicing for 5G-enabled IoT, IEEE J. Sel. Areas Commun., vol. 36, no. 3, pp. 644–657, 2018.


B. Li, Z. S. Fei, Y. Zhang, and M. Guizani, Secure UAV communication networks over 5G, IEEE Wireless Commun., vol. 26, no. 5, pp. 114–120, 2019.


Z. Q. Zhang, Y. Xiao, Z. Ma, M. Xiao, Z. G. Ding, X. F. Lei, G. K. Karagiannidis, and P. Z. Fan, 6G wireless networks: Vision, requirements, architecture, and key technologies, IEEE Veh. Technol. Mag., vol. 14, no. 3, pp. 28–41, 2019.


B. F. Ji, Y. A. Wang, K. Song, C. G. Li, H. Wen, V. G. Menon, and S. Mumtaz, A survey of computational intelligence for 6G: Key technologies, applications and trends, IEEE Trans. Ind. Informat., vol. 17, no. 10, pp. 7145–7154, 2021.


G. Gui, M. Liu, F. X. Tang, N. Kato, and F. Adachi, 6G: Opening new horizons for integration of comfort, security and intelligence, IEEE Wireless Commun., vol. 27, no. 5, pp. 126–132, 2020.


H. Viswanathan and P. E. Mogensen, Communications in the 6G Era, IEEE Access, vol. 8, pp. 57063–57074, 2020.


T. Wild, V. Braun, and H. Viswanathan, Joint design of communication and sensing for beyond 5G and 6G systems, IEEE Access, vol. 9, pp. 30845–30857, 2021.


C. De Lima, D. Belot, R. Berkvens, A. Bourdoux, D. Dardari, M. Guillaud, M. Isomursu, E. S. Lohan, Y. Miao, A. N. Barreto, et al., Convergent communication, sensing and localization in 6G systems: An overview of technologies, opportunities and challenges, IEEE Access, vol. 9, pp. 26902–26925, 2021.


Z. F. Liao, J. S. Peng, J. W. Huang, J. X. Wang, J. Wang, P. K. Sharma, and U. Ghosh, Distributed probabilistic offloading in edge computing for 6G-enabled massive Internet of Things, IEEE Internet Things J., vol. 8, no. 7, pp. 5298–5308, 2021.


Y. Xiao, G. M. Shi, Y. Y. Li, W. Saad, and H. V. Poor, Toward self-learning edge intelligence in 6G, IEEE Commun. Mag., vol. 58, no. 12, pp. 34–40, 2020.


R. Shafin, L. J. Liu, V. Chandrasekhar, H. Chen, J. Reed, and J. Z. Zhang, Artificial intelligence-enabled cellular networks: A critical path to beyond-5G and 6G, IEEE Wireless Commun., vol. 27, no. 2, pp. 212–217, 2020.


T. Hong, W. T. Zhao, R. K. Liu, and M. Kadoch, Space-air-ground IoT network and related key technologies, IEEE Wireless Commun., vol. 27, no. 2, pp. 96–104, 2020.


P. Wang, J. X. Zhang, X. Zhang, Z. Yan, B. G. Evans, and W. B. Wang, Convergence of satellite and terrestrial networks: A comprehensive survey, IEEE Access, vol. 8, pp. 5550–5588, 2020.


A. Ivanov, K. Tonchev, V. Poulkov, and A. Manolova, Probabilistic spectrum sensing based on feature detection for 6G cognitive radio: A survey, IEEE Access, vol. 9, pp. 116994–117026, 2021.


H. Song, J. N. Bai, Y. Yi, J. S. Wu, and L. J. Liu, Artificial intelligence enabled Internet of Things: Network architecture and spectrum access, IEEE Comput. Intell. Mag., vol. 15, no. 1, pp. 44–51, 2020.


Y. Feng, B. L. Jiao, and L. Y. Song, Satellite-based spectrum sensing for dynamic spectrum sharing in ground-located CRNs, Wireless Pers. Commun., vol. 57, no. 1, pp. 105–117, 2011.


J. J. Liu, Y. P. Shi, Z. M. Fadlullah, and N. Kato, Space-air-ground integrated network: A survey, IEEE Commun. Surveys Tuts., vol. 20, no. 4, pp. 2714–2741, 2018.


B. M. Mao, F. X. Tang, Y. Kawamoto, and N. Kato, Optimizing computation offloading in satellite-UAV-served 6G IoT: A deep learning approach, IEEE Netw., vol. 35, no. 4, pp. 102–108, 2021.

M. Helmy, Z. E. Ankarali, M. Siala, T. Baykas, and H. Arslan, Dynamic utilization of low-altitude platforms in aerial heterogeneous cellular networks, in Proc. IEEE Wireless Microw. Technol. Conf. (WAMICON), Cocoa Beach, FL, USA, 2017, pp. 1–6.

M. Helmy and H. Arslan, Utilization of aerial heterogeneous cellular networks: Signal-to-interference ratio analysis, J. Commun. Netw., vol. 20, no. 5, pp. 484–495, 2018.

Y. Du, K. Z. Wang, K. Yang, and G. P. Zhang, Trajectory design of laser-powered multi-drone enabled data collection system for smart cities, in Proc. IEEE Global Commun. Conf.(GLOBECOM), Waikoloa, HI, USA, 2019, pp. 1–6.
Functional Architecture for Unmanned Aerial Vehicles and Unmanned Aerial Vehicle Controllers Using IMT-2020 Networks, Recommendation ITU-T Y.4421, Geneva, 2021.
U. Senol, A. Yazar, and H. Arslan, Communications scenarios and a new mixed numerology set for flying base stations in 5G and beyond, in Proc. IEEE Int. Black Sea Conf. Commun. Netw.(BlackSeaCom), Batumi, GA, USA, 2018, pp. 91–95.

M. Mozaffari, W. Saad, M. Bennis, Y. H. Nam, and M. Debbah, A tutorial on UAVs for wireless networks: Applications, challenges and open problems, IEEE Commun. Surveys Tuts., vol. 21, no. 3, pp. 2334–2360, 2019.

X. N. Zhu, Analysis of military application of UAV swarm technology, in Proc. 3rd International Conference On Unmanned Systems(ICUS), Harbin, China, 2020, pp. 1200–1204.

M. Alwateer, S. W. Loke, and A. M. Zuchowicz, Drone services: Issues in drones for location-based services from human-drone interaction to information processing, J. Location Based Serv., vol. 13, no. 2, pp. 94–127, 2019.


H. Shakhatreh, A. H. Sawalmeh, A. Al-Fuqaha, Z. C. Dou, E. Almaita, I. Khalil, N. S. Othman, A. Khreishah, and M. Guizani, Unmanned aerial vehicles (UAVs): A survey on civil applications and key research challenges, IEEE Access, vol. 7, pp. 48572–48634, 2019.


V. Mazzia, L. Comba, A. Khaliq, M. Chiaberge, and P. Gay, UAV and machine learning based refinement of a satellite-driven vegetation index for precision agriculture, Sensors, vol. 20, no. 9, p. 2530, 2020.


P. K. R. Maddikunta, S. Hakak, M. Alazab, S. Bhattacharya, T. R. Gadekallu, W. Z. Khan, and Q. V. Pham, Unmanned aerial vehicles in smart agriculture: Applications, requirements, and challenges, IEEE Sensors J., vol. 21, no. 16, pp. 17608–17619, 2021.


C. A. Thiels, J. M. Aho, S. P. Zietlow, and D. H. Jenkins, Use of unmanned aerial vehicles for medical product transport, Air Med. J., vol. 34, no. 2, pp. 104–108, 2015.


S. Sudhakar, V. Vijayakumar, C. S. Kumar, V. Priya, L. Ravi, and V. Subramaniyaswamy, Unmanned aerial vehicle (UAV) based forest fire detection and monitoring for reducing false alarms in forest-fires, Comput. Commun., vol. 149, pp. 1–16, 2020.


H. Zhang, L. H. Dou, B. Xin, J. Chen, M. G. Gan, and Y. L. Ding, Data collection task planning of a fixed-wing unmanned aerial vehicle in forest fire monitoring, IEEE Access, vol. 9, pp. 109847–109864, 2021.


L. Gupta, R. Jain, and G. Vaszkun, Survey of important issues in UAV communication networks, IEEE Commun. Surveys Tuts., vol. 18, no. 2, pp. 1123–1152, 2016.


A. Fotouhi, H. R. Qiang, M. Ding, M. Hassan, L. G. Giordano, A. Garcia-Rodriguez, and J. H. Yuan, Survey on UAV cellular communications: Practical aspects, standardization advancements, regulation, and security challenges, IEEE Commun. Surveys Tuts., vol. 21, no. 4, pp. 3417–3442, 2019.


P. K. Sharma and D. I. Kim, Secure 3D mobile UAV relaying for hybrid satellite-terrestrial networks, IEEE Trans. Wireless Commun., vol. 19, no. 4, pp. 2770–2784, 2020.


N. N. Dao, Q. V. Pham, N. H. Tu, T. T. Thanh, V. N. Q. Bao, D. S. Lakew, and S. Cho, Survey on aerial radio access networks: Toward a comprehensive 6G access infrastructure, IEEE Commun. Surveys Tuts., vol. 23, no. 2, pp. 1193–1225, 2021.


Q. Q. Wu, J. Xu, Y. Zeng, D. W. K. Ng, N. Al-Dhahir, R. Schober, and A. L. Swindlehurst, A comprehensive overview on 5G-and-beyond networks with UAVs: From communications to sensing and intelligence, IEEE J. Sel. Areas Commun., vol. 39, no. 10, pp. 2912–2945, 2021.


G. C. Zhang, Q. Q. Wu, M. Cui, and R. Zhang, Securing UAV communications via joint trajectory and power control, IEEE Trans. Wireless Commun., vol. 18, no. 2, pp. 1376–1389, 2019.


M. Cui, G. C. Zhang, Q. Q. Wu, and D. W. K. Ng, Robust trajectory and transmit power design for secure UAV communications, IEEE Trans. Veh. Technol., vol. 67, no. 9, pp. 9042–9046, 2018.


M. T. Mamaghani and Y. Hong, Joint trajectory and power allocation design for secure artificial noise aided UAV communications, IEEE Trans. Veh. Technol., vol. 70, no. 3, pp. 2850–2855, 2021.


B. Yang, T. Taleb, Z. Q. Wu, and L. S. Ma, Spectrum sharing for secrecy performance enhancement in D2D-enabled UAV networks, IEEE Netw., vol. 34, no. 6, pp. 156–163, 2020.


S. Aggarwal, R. Chaudhary, G. S. Aujla, N. Kumar, K. K. R. Choo, and A. Y. Zomaya, Blockchain for smart communities: Applications, challenges and opportunities, J. Netw. Comput. Appl., vol. 144, pp. 13–48, 2019.


I. Garcia-Magarino, R. Lacuest, M. Rajarajan, and J. Lloret, Security in networks of unmanned aerial vehicles for surveillance with an agent-based approach inspired by the principles of blockchain, Ad Hoc Netw., vol. 86, pp. 72–82, 2019.


T. M. Fernandez-Carames, O. Blanco-Novoa, I. Froiz-Miguez, and P. Fraga-Lamas, Towards an autonomous industry 4.0 warehouse: A UAV and blockchain-based system for inventory and traceability applications in big data-driven supply chain management, Sensors, vol. 19, no. 10, p. 2394, 2019.

R. Gupta, A. Shukla, P. Mehta, P. Bhattachaya, and N. Kumar, VAHAK: A blockchain-based outdoor delivery scheme using UAV for healthcare 4.0 services, in Proc. IEEE Conf. Comput. Commun. Workshops(INFOCOM WKSHPS), Toronto, Canada, 2020, pp. 255–260.

S. Tanwar, Q. Bhatia, P. Patel, A. Kumari, P. K. Singh, and W. C. Hong, Machine learning adoption in blockchain-based smart applications: The challenges, and a way forward, IEEE Access, vol. 8, pp. 474–488, 2020.


Apoorva, S. Bitragunta, and S. Nitundil, Best beam selection and PHY switching policy for hybrid FSO/RF inter-satellite communication link, IET Commun., vol. 14, no. 19, pp. 3350–3362, 2020.


J. D. Yu, X. L. Liu, Y. Gao, and X. M. Shen, 3D channel tracking for UAV-satellite communications in space-air-ground integrated networks, IEEE J. Sel. Areas Commun., vol. 38, no. 12, pp. 2810–2823, 2020.


J. Liu, X. Q. Du, J. H. Cui, M. Pan, and D. B. Wei, Task-oriented intelligent networking architecture for the space-air-ground-aqua integrated network, IEEE Internet Things J., vol. 7, no. 6, pp. 5345–5358, 2020.

N. Hosseini, H. Jamal, D. W. Matolak, J. Haque, and T. Magesacher, UAV command and control, navigation and surveillance: A review of potential 5G and satellite systems, in Proc. IEEE Aerosp. Conf., Big Sky, MT, USA, 2019, pp. 1–10.

P. Zhou, X. M. Fang, Y. G. Fang, R. He, Y. Long, and G. Y. Huang, Beam management and self-healing for mmwave UAV mesh networks, IEEE Trans. Veh. Technol., vol. 68, no. 2, pp. 1718–1732, 2019.


R. Swaminathan, S. Sharma, N. Vishwakarma, and A. S. Madhukumar, HAPS-based relaying for integrated space-air-ground networks with hybrid FSO/RF communication: A performance analysis, IEEE Trans. Aerosp. Electron. Syst., vol. 57, no. 3, pp. 1581–1599, 2021.


J. Kim, J. Lee, and I. Lee, Antenna tracking techniques for long range air-to-ground communication systems using a monopulse method, IEEE Access, vol. 8, pp. 166442–166449, 2020.


Y. Shibata, N. Kanazawa, M. Konishi, K. Hoshino, Y. Ohta, and A. Nagate, System design of Gigabit HAPS mobile communications, IEEE Access, vol. 8, pp. 157995–158007, 2020.


A. V. Savkin, H. L. Huang, and W. Ni, Securing UAV communication in the presence of stationary or mobile eavesdroppers via online 3D trajectory planning, IEEE Wireless Commun. Lett., vol. 9, no. 8, pp. 1211–1215, 2020.


G. J. Hu, Y. M. Cai, and Y. L. Cai, Joint optimization of position and jamming power for UAV-aided proactive eavesdropping over multiple suspicious communication links, IEEE Wireless Commun. Lett., vol. 9, no. 12, pp. 2093–2097, 2020.

X. S. Gan, Y. R. Wu, P. N. Li, and Q. Wang, Dynamic collision avoidance zone modeling method based on UAV emergency collision avoidance trajectory, in Proc. IEEE Int. Conf. Artif. Intell. Inf. Syst.(ICAⅡS), Dalian, China, 2020, pp. 693–696.

X. Yu, X. B. Zhou, and Y. M. Zhang, Collision-free trajectory generation and tracking for UAVs using markov decision process in a cluttered environment, J. Intell. Robot. Syst., vol. 93, nos. 1&2, pp. 17–32, 2019.

T. Baca, D. Hert, G. Loianno, M. Saska, and V. Kumar, Model predictive trajectory tracking and collision avoidance for reliable outdoor deployment of unmanned aerial vehicles, in Proc. IEEE/RSJ Int. Conf. Intell. Robots Syst.(IROS), Madrid, Spain, 2018, pp. 6753–6760.

P. K. Sharma, D. Deepthi, and D. I. Kim, Outage probability of 3-D mobile UAV relaying for hybrid satellite-terrestrial networks, IEEE Commun. Lett., vol. 24, no. 2, pp. 418–422, 2020.


T. Zhang, G. L. Liu, H. J. Zhang, W. J. Kang, G. K. Karagiannidis, and A. Nallanathan, Energy-efficient resource allocation and trajectory design for UAV relaying systems, IEEE Trans. Commun., vol. 68, no. 10, pp. 6483–6498, 2020.

S. A. Hoseini, J. Hassan, A. Bokani, and S. S. Kanhere, Trajectory optimization of flying energy sources using Q-learning to recharge hotspot UAVs, in Proc. IEEE Conf. Comput. Commun. Workshops(INFOCOM WKSHPS), Toronto, Canada, 2020, pp. 683–688.

Y. J. Jin, H. L. Zhang, S. H. Zhang, Z. Han, and L. Y. Song, Sense-store-send: Trajectory optimization for a buffer-aided Internet of UAVs, IEEE Commun. Lett., vol. 24, no. 12, pp. 2888–2892, 2020.

M. Alzenad and H. Yanikomeroglu, Coverage and rate analysis for unmanned aerial vehicle base stations with LoS/NLoS propagation, in Proc. IEEE Globecom Workshops(GC Wkshps), Abu Dhabi, the United Arab Emirates, 2018, pp. 1–7.

W. D. Mei and R. Zhang, UAV-sensing-assisted cellular interference coordination: A cognitive radio approach, IEEE Wireless Commun. Lett., vol. 9, no. 6, pp. 799–803, 2020.


M. Hua, Y. Wang, M. Lin, C. G. Li, Y. M. Huang, and L. X. Yang, Joint CoMP transmission for UAV-aided cognitive satellite terrestrial networks, IEEE Access, vol. 7, pp. 14959–14968, 2019.


Y. W. Huang, W. D. Mei, J. Xu, L. Qiu, and R. Zhang, Cognitive UAV communication via joint maneuver and power control, IEEE Trans. Commun., vol. 67, no. 11, pp. 7872–7888, 2019.


A. V. Savkin and H. L. Huang, Deployment of unmanned aerial vehicle base stations for optimal quality of coverage, IEEE Wireless Commun. Lett., vol. 8, no. 1, pp. 321–324, 2019.


S. Arabi, E. Sabir, H. Elbiaze, and M. Sadik, Data gathering and energy transfer dilemma in UAV-assisted flying access network for IoT, Sensors, vol. 18, no. 5, p. 1519, 2018.


W. Q. Huang, D. M. Kim, W. R. Ding, and P. Popovski, Joint optimization of altitude and transmission direction in UAV-based two-way communication, IEEE Wireless Commun. Lett., vol. 8, no. 4, pp. 984–987, 2019.


W. D. Mei, Q. Q. Wu, and R. Zhang, Cellular-connected UAV: Uplink association, power control and interference coordination, IEEE Trans. Wireless Commun., vol. 18, no. 11, pp. 5380–5393, 2019.


C. Caillouet and N. Mitton, Optimization and communication in UAV networks, Sensors, vol. 20, no. 18, p. 5036, 2020.


S. Aggarwal, N. Kumar, and S. Tanwar, Blockchain-envisioned UAV communication using 6G networks: Open issues, use cases, and future directions, IEEE Internet Things J., vol. 8, no. 7, pp. 5416–5441, 2021.


R. Shrestha, R. Bajracharya, and S. Kim, 6G enabled unmanned aerial vehicle traffic management: A perspective, IEEE Access, vol. 9, pp. 91119–91136, 2021.


F. Noor, M. A. Khan, A. Al-Zahrani, I. Ullah, and K. A. Al-Dhlan, A review on communications perspective of flying ad-hoc networks: Key enabling wireless technologies, applications, challenges and open research topics, Drones, vol. 4, no. 4, p. 65, 2020.

I. J. Jensen, D. F. Selvaraj, and P. Ranganathan, Blockchain technology for networked swarms of unmanned aerial vehicles (UAVs), in Proc. IEEE 20th Int. Symp. World Wireless, Mobile Multimedia Netw.(WoWMoM), Washington, DC, USA, 2019, pp. 1–7.

A. S. Khan, G. J. Chen, Y. Rahulamathavan, G. Zheng, B. Assadhan, and S. Lambotharan, Trusted UAV network coverage using blockchain, machine learning, and auction mechanisms, IEEE Access, vol. 8, pp. 118219–118234, 2020.


M. Keshavarz, M. Gharib, F. Afghah, and J. D. Ashdown, UASTrustChain: A decentralized blockchain-based trust monitoring framework for autonomous unmanned aerial systems, IEEE Access, vol. 8, pp. 226074–226088, 2020.


C. P. Ge, X. S. Ma, and Z. Liu, A semi-autonomous distributed blockchain-based framework for UAVs system, J. Syst. Archit., vol. 107, p. 101728, 2020.


V. Hassija, V. Chamola, D. N. G. Krishna, and M. Guizani, A distributed framework for energy trading between UAVs and charging stations for critical applications, IEEE Trans. Veh. Technol., vol. 69, no. 5, pp. 5391–5402, 2020.

I. Cermakova and J. Komarkova, Modelling a process of UAV data collection and processing, in Proc. IEEE Int. Conf. Inf. Soc.(i-Society), Dublin, Ireland, 2016, pp. 161–164.

X. B. Xu, H. Zhao, H. P. Yao, and S. G. Wang, A blockchain-enabled energy-efficient data collection system for UAV-assisted IoT, IEEE Internet Things J., vol. 8, no. 4, pp. 2431–2443, 2021.


A. Islam and S. Y. Shin, BUS: A blockchain-enabled data acquisition scheme with the assistance of UAV swarm in Internet of Things, IEEE Access, vol. 7, pp. 103231–103249, 2019.


Z. G. Ding, Y. W. Liu, J. Choi, Q. Sun, M. Elkashlan, C. L. I, and H. V. Poor, Application of non-orthogonal multiple access in LTE and 5G networks, IEEE Commun. Mag., vol. 55, no. 2, pp. 185–191, 2017.


W. C. Chen, S. J. Zhao, R. Q. Zhang, Y. Chen, and L. Q. Yang, UAV-assisted data collection with nonorthogonal multiple access, IEEE Internet Things J., vol. 8, no. 1, pp. 501–511, 2021.


J. W. Zhao, Y. Wang, Z. X. Fei, X. Wang, and Z. Y. Miao, NOMA-aided UAV data collection system: Trajectory optimization and communication design, IEEE Access, vol. 8, pp. 155843–155858, 2020.


X. D. Mu, Y. W. Liu, L. Guo, J. R. Lin, and Z. G. Ding, Energy-constrained UAV data collection systems: NOMA and OMA, IEEE Trans. Veh. Technol., vol. 70, no. 7, pp. 6898–6912, 2021.

W. D. Ye, W. J. Wu, F. Shan, M. Yang, and J. Z. Luo, Energy-efficient trajectory planning and speed scheduling for UAV-assisted data collection, in Proc. 2020 16th International Conference on Mobility, Sensing and Networking(MSN), Tokyo, Japan, 2020, pp. 190–197.

S. Z. Yang, Y. S. Deng, X. X. Tang, Y. Ding, and J. M. Zhou, Energy efficiency optimization for UAV-assisted backscatter communications, IEEE Commun. Lett., vol. 23, no. 11, pp. 2041–2045, 2019.


S. Fu, Y. J. Tang, Y. Wu, N. Zhang, H. X. Gu, C. Chen, and M. Liu, Energy-efficient UAV-enabled data collection via wireless charging: A reinforcement learning approach, IEEE Internet Things J., vol. 8, no. 12, pp. 10209–10219, 2021.

S. Kaul, R. Yates, and M. Gruteser, Real-time status: How often should one update? in Proc. IEEE INFOCOM, Orlando, FL, USA, 2012, pp. 2731–2735.

S. H. Zhang, H. L. Zhang, Z. Han, H. V. Poor, and L. Y. Song, Age of information in a cellular Internet of UAVs: Sensing and communication trade-off design, IEEE Trans. Wireless Commun., vol. 19, no. 10, pp. 6578–6592, 2020.


J. Liu, P. Tong, X. J. Wang, B. Bai, and H. Y. Dai, UAV-aided data collection for information freshness in wireless sensor networks, IEEE Trans. Wireless Commun., vol. 20, no. 4, pp. 2368–2382, 2021.


M. A. Abd-Elmagid and H. S. Dhillon, Average peak age-of-information minimization in UAV-assisted IoT networks, IEEE Trans. Veh. Technol., vol. 68, no. 2, pp. 2003–2008, 2019.


G. Ahani, D. Yuan, and Y. X. Zhao, Age-optimal UAV scheduling for data collection with battery recharging, IEEE Commun. Lett., vol. 25, no. 4, pp. 1254–1258, 2021.


J. F. Qiu, D. Grace, G. R. Ding, J. N. Yao, and Q. H. Wu, Blockchain-based secure spectrum trading for unmanned-aerial-vehicle-assisted cellular networks: An operator's perspective, IEEE Internet Things J., vol. 7, no. 1, pp. 451–466, 2020.


B. D. Shang, V. Marojevic, Y. Yi, A. S. Abdalla, and L. J. Liu, Spectrum sharing for UAV communications: Spatial spectrum sensing and open issues, IEEE Veh. Technol. Mag., vol. 15, no. 2, pp. 104–112, 2020.


B. D. Shang, L. J. Liu, R. M. Rao, V. Marojevic, and J. H. Reed, 3D spectrum sharing for hybrid D2D and UAV networks, IEEE Trans. Commun., vol. 68, no. 9, pp. 5375–5389, 2020.


F. Shen, G. R. Ding, Z. Wang, and Q. H. Wu, UAV-based 3D spectrum sensing in spectrum-heterogeneous networks, IEEE Trans. Veh. Technol., vol. 68, no. 6, pp. 5711–5722, 2019.


W. B. Xu, S. Wang, S. Yan, and J. H. He, An efficient wideband spectrum sensing algorithm for unmanned aerial vehicle communication networks, IEEE Internet Things J., vol. 6, no. 2, pp. 1768–1780, 2019.


Y. P. Li, R. Q. Zhang, J. H. Zhang, and L. Q. Yang, Cooperative jamming via spectrum sharing for secure UAV communications, IEEE Wireless Commun. Lett., vol. 9, no. 3, pp. 326–330, 2020.


N. Tang, H. Y. Tang, B. Q. Li, and X. B. Yuan, Cognitive NOMA for UAV-enabled secure communications: Joint 3D trajectory design and power allocation, IEEE Access, vol. 8, pp. 159965–159978, 2020.


A. Islam and S. Y. Shin, BUAV: A blockchain based secure UAV-assisted data acquisition scheme in Internet of Things, J. Commun. Netw., vol. 21, no. 5, pp. 491–502, 2019.


Z. Y. Guan, H. Z. Lyu, D. W. Li, Y. M. Hei, and T. C. Wang, Blockchain: A distributed solution to UAV-enabled mobile edge computing, IET Commun., vol. 14, no. 15, pp. 2420–2426, 2020.


V. Sharma, I. You, D. N. K. Jayakody, D. G. Reina, and K. K. R. Choo, Neural-blockchain-based ultrareliable caching for edge-enabled UAV networks, IEEE Trans. Ind. Informat., vol. 15, no. 10, pp. 5723–5736, 2019.


B. Q. Wang, J. F. Xie, S. W. Li, Y. Wan, Y. X. Gu, S. L. Fu, and K. J. Lu, Computing in the air: An open airborne computing platform, IET Commun., vol. 14, no. 15, pp. 2410–2419, 2020.


G. Faraci, C. Grasso, and G. Schembra, Design of a 5G network slice extension with MEC UAVs managed with reinforcement learning, IEEE J. Sel. Areas Commun., vol. 38, no. 10, pp. 2356–2371, 2020.

ITU, Studies on frequency-related matters, including possible additional allocations, for the possible introduction of new non-safety aeronautical mobile applications, presented at World Radiocommunication Conference, document Resolution 430, 2019.

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 Things J., vol. 3, no. 6, pp. 899–922, 2016.

O. Anicho, P. B. Charlesworth, G. S. Baicher, and A. Nagar, Situation awareness and routing challenges in unmanned HAPS/UAV based communications networks, in Proc. 2020 International conference on unmanned aircraft systems(ICUAS), Athens, Greece, 2020, pp. 1175–1182.

Z. H. Wang, J. Z. Li, H. Q. Chen, and T. F. Qin, A novel divergence measure-based routing algorithm in large-scale satellite networks, IET Commun., vol. 15, no. 5, pp. 708–722, 2021.

M. Q. Vu, T. V. Pham, N. T. Dang, and A. T. Pham, Outage performance of HAP-UAV FSO links with Gaussian beam and UAV hovering, in Proc. 2020 IEEE 92nd Vehicular Technology Conference(VTC2020-Fall), Victoria, Canada, 2020, pp. 1–5.

E. H. S. Cardoso, J. P. L. De Araujo, S. V. De Carvalho, N. Vijaykumar, and C. R. L. Frances, Novel multilayered cellular automata for flying cells positioning on 5G cellular self-organising networks, IEEE Access, vol. 8, pp. 227076–227099, 2020.


H. C. Wang, G. C. Ren, J. Chen, G. R. Ding, and Y. J. Yang, Unmanned aerial vehicle-aided communications: Joint transmit power and trajectory optimization, IEEE Wireless Commun. Lett., vol. 7, no. 4, pp. 522–525, 2018.


Y. J. Qin, M. A. Kishk, and M. S. Alouini, Performance evaluation of UAV-enabled cellular networks with battery-limited drones, IEEE Commun. Lett., vol. 24, no. 12, pp. 2664–2668, 2020.


H. V. Abeywickrama, B. A. Jayawickrama, Y. He, and E. Dutkiewicz, Comprehensive energy consumption model for unmanned aerial vehicles, based on empirical studies of battery performance, IEEE Access, vol. 6, pp. 58383–58394, 2018.

Intelligent and Converged Networks
Pages 277-294
Cite this article:
Wang Z, Zhang F, Yu Q, et al. Blockchain-envisioned unmanned aerial vehicle communications in space-air-ground integrated network: A review. Intelligent and Converged Networks, 2021, 2(4): 277-294.










Received: 17 October 2021
Accepted: 05 November 2021
Published: 30 December 2021
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