We are a joint research project between Lappeenranta-Lahti University of Technology (LUT) and Tampere University (TAU) funded by Jane and Aatos Erkko Foundation that aims at breaking through the current scalability limits in autonomous aerial swarming for collaborative mission-aware applications. The project started in January 2021 and ended in June 2024.
Project Coordinator: Prof. Pedro Nardelli, LUT
Co-Principal Investigator: Prof. Sergey Andreev, TAU
Co-Principal Investigator: Prof. Pertti Silventoinen, LUT
Unmanned Aerial Vehicles (UAVs) are reusable aircrafts designed to operate without on-board pilot nor passengers, which can be either piloted remotely or programmed to fly autonomously. UAVs may also be deployed to work collaboratively where multiple UAVs form a fleet named swarm to achieve a collective objective. In this case, the UAVs constituting an autonomous swarm maintain and adjust their formation to engage in collaborative missions by sharing not only their goals but also individual energy and data resources. We specifically emphasize missions related to rapid deployment and easy maintenance of flexible and on-demand radio network infrastructures that comprise multiple drone-cells and (multi-hop) UAV relays, which require efficient co-design of communication and navigation/control functionalities. In stark contrast to existing knowledge, this project will focus on understanding intelligent energy management in large UAV swarms for mission-aware communication purposes based on collaborative data acquisition with context-inference capabilities. In other words, this project seeks to integrate intelligent UAVs into an effective and robust autonomous swarm for large-scale and agile operations related to the contexts of (i) intra-swarm communication and (ii) on-demand network service provisioning. The key ambition of this project is to leap beyond the state-of-the-art in several fields of science and technology in order to reach our ultimate objective: break through the current scalability limits in autonomous aerial swarming for collaborative mission-aware applications. To achieve this trendsetting target the following scientific objectives need to be reached in concert: (a) Energy-centric collaborative UAV management in mission-specific intelligent swarming operations; (b) Communication technology co-design with collaborative flight control and UAV fleet management; (c) AI-driven data acquisition and fusion method for aerial context inference and situational awareness. Our approach will employ mathematical modeling and analysis, agent-based computer modeling and multi-agent simulations, artificial and collective intelligence methods, and a proof-of-concept testbed for experimenting with UAV swarms.
Journal papers
Dick Carrillo, Konstantin Mikhaylov, Pedro J. Nardelli, Sergey Andreev, Daniel da Costa: Understanding UAV-Based WPCN-Aided Capabilities for Offshore Monitoring Applications. IEEE Wireless Communications Magazine 28(2): 114-120 (2021)
Margarita Gapeyenko, Dmitri Moltchanov, Sergey Andreev, Robert W. Heath Jr.: Line-of-Sight Probability for mmWave-based UAV Communications in 3D Urban Grid Deployments. IEEE Transactions on Wireless Communications 20(10): 6566-6579 (2021)
Miguel Calvo-Fullana, Alexander Pyattaev, Daniel Mox, Sergey Andreev, Alejandro Ribeiro: Communications and Robotics Simulation in UAVs: A Case Study on Aerial Synthetic Aperture Antennas. IEEE Communications Magazine 59(1): 22-27 (2021)
Iuliia Tropkina, Alexander Pyattaev, Yekaterina Sadovaya, and Sergey Andreev: Modeling of SHF/EHF Radio-Wave Scattering for Curved Surfaces with Voxel Cone Tracing. IEEE Antennas and Wireless Propagation Letters 21.2 (2021): 426-430.
Narayanan, Arun, et al. “Collective Intelligence using 5G: Concepts, Applications, and Challenges in Sociotechnical Environments.” IEEE Access.
Carrillo, Dick, et al. “Optimizing UAV-based wireless connectivity via a machine-learning framework for allocation of network slices,” IEEE Access.
E. Ataeebojd, M. Rasti, H. Pedram and P. H. J. Nardelli, "Spectrum Sharing Among Multiple-Seller and Multiple-Buyer Operators of a Mobile Network: A Stochastic Geometry Approach," in IEEE Transactions on Cognitive Communications and Networking, vol. 8, no. 3, pp. 1332-1347, Sept. 2022, doi: 10.1109/TCCN.2022.3183898.
A. Termechi, and M. Rasti, “A learning approach for joint design of event-triggered control and power-efficient resource allocation,” IEEE Transactions on Vehicular Technology, vol. 71, no. 6, pp. 6322-6334, 2022.
H. Zarini, A. Khalili, H. Tabassum, M. Rasti, and W. Saad, “AlexNet classifier and support vector regressor for scheduling and power control in multimedia heterogeneous networks,” to appear in IEEE Transactions on Mobile Computing, 2022.
S. Kazemi, M. Rasti, P. H. J. Nardelli, and J. Cheng, “Blockchain function virtualization: A new approach for mobile networks beyond 5G,” to appear in IEEE Network, 2022.
M. Rasti, S. Kazemi, H. Tabassum, and E. Hossain, “Evolution toward 6G multi-band wireless networks: A resource management perspective,” IEEE Wireless Communications, 2022.
Olga Chukhno, Nadezhda Chukhno, Olga Galinina, Sergey Andreev, Yuliya Gaidamaka, Konstantin Samouylov, Giuseppe Araniti: A Holistic Assessment of Directional Deafness in mmWave-based Distributed 3D Networks. IEEE Transactions on Wireless Communications 21(9): 7491-7505 (2022)
Joonas Säe, Perttu Kurvi, Sergey Andreev, Mikko Valkama: Agile 5G Network Measurements: Operator Benefits of Employing Aerial Mobility. IEEE Internet of Things Magazine 5(2): 114-119 (2022)
Iuliia Tropkina, Bo Sun, Dmitri Moltchanov, Alexander Pyattaev, Bo Tan, Rui Dinis, Sergey Andreev: Distributed Communication and Sensing System Co-Design for Improved UAV Network Resilience. IEEE Transactions on Vehicular Technology 72(1): 924-939 (2023)
Ikonen, Jouni; Nelimarkka, Niklas; Nardelli, Pedro HJ; Mattila, Niko; Carrillo, Dick; ,Experimental Evaluation of End-to-End Delay in a Sigfox Network, IEEE Networking Letters, 2022
Silva, Pedro E. Gória, et al. "Enabling Semantic-Functional Communications for Multiuser Event Transmissions via Wireless Power Transfer." Sensors 23.5 (2023): 2707.
Salwa Saafi, Olga Vikhrova, Gabor Fodor, Jiri Hosek, Sergey Andreev: Cost- and Delay-Efficient Backhaul Selection for Time-Sensitive Maritime Communications. IEEE Communications Letters 27(4): 1235-1239 (2023)
Hosein Zarini, Mohammad R. Mili, Mehdi Rasti, Sergey Andreev, Pedro J. Nardelli, Mehdi Bennis: Intelligent Analog Beam Selection and Beamspace Channel Tracking in THz Massive MIMO with Lens Antenna Array. IEEE Transactions on Cognitive Communications and Networking 9(3): 629-646 (2023)
Nikita Tafintsev, Dmitri Moltchanov, Alessandro Chiumento, Mikko Valkama, Sergey Andreev: Airborne Integrated Access and Backhaul Systems: Learning-Aided Modeling and Optimization. IEEE Transactions on Vehicular Technology, early access (2023)
A. K. Shukla, J. M. Moualeu, P. K. Upadhyay, F. Takawira and P. H. J. Nardelli, "On the Performance of Cache- and Energy Harvesting-Assisted NOMA in D2D Communications With Hardware Impairments," in IEEE Sensors Letters, vol. 7, no. 11, pp. 1-4, Nov. 2023
Korium, M. et al. “Generalized intrusion detection system (G-IDS) algorithm model to detect Internet of Vehicles (IoV) attacks,” Ad Hoc Networks, 2023.
Silva, Pedro E. Goria, et al. "Semantic-Functional Communications in Cyber-Physical Systems." IEEE Network, 2023
Narayanan, Arun, et al. “Collective Intelligence for Package Deliveries using Unmanned Aerial Vehicles,” IEEE Intelligent Systems, 2024
Korium, Mohamed Selim, et al. "Image-based intrusion detection system for GPS spoofing cyberattacks in unmanned aerial vehicles." Ad Hoc Networks 163 (2024): 103597.
Silva, Pedro E. Gória, et al. "A novel semantic-functional approach for multiuser event-trigger communication." Ad Hoc Networks 159 (2024): 103496.
Conference papers
Azizi, Farzad; Teymuri, Benyamin; Aslani, Rojin; Rasti, Mehdi; Tolvanen, Jesse; Nardelli, Pedro HJ; MIX-MAB: Reinforcement Learning-based Resource Allocation Algorithm for LoRaWAN, 2022 IEEE 95th Vehicular Technology Conference:(VTC2022-Spring), 2022
Goharfar, Ashkan; Babaki, Jaber; Rasti, Mehdi; Nardelli, Pedro HJ; Indoor Positioning via Gradient Boosting Enhanced with Feature Augmentation using Deep Learning, 2022 IEEE 95th Vehicular Technology Conference:(VTC2022-Spring), 2022
Zarini, Hosein; Mili, Mohammad Robat; Rasti, Mehdi; Andreev, Sergey; Nardelli, Pedro HJ; Swish-Driven GoogleNet for Intelligent Analog Beam Selection in Terahertz Beamspace MIMO, 2022 IEEE 95th Vehicular Technology Conference:(VTC2022-Spring), 2022
H. Zarini, M. R. Mili, M. Rasti, P. H. J. Nardelli and M. Bennis, "Xavier-Enabled Extreme Reservoir Machine for Millimeter-Wave Beamspace Channel Tracking," in 2022 IEEE Wireless Communications and Networking Conference (WCNC), 2022.
E. Ataeebojd, M. Rasti, H. Pedram, and P. H. J. Nardelli, “Stochastic geometry analysis of spectrum sharing among multiple seller and buyer mobile operators,” in 2022 IEEE Wireless Communications and Networking Conference (WCNC), 2022.
S. Kazemi, M. Rasti, and P. H. J. Nardelli, “Minimizing energy consumption for end-to-end slicing in 5G wireless networks and beyond,” in 2022 IEEE Wireless Communications and Networking Conference (WCNC), 2022.
A. Narayanan, E. Pournaras and P. H. J. Nardelli, "Collective Learning for Energy-centric Flexible Job Shop Scheduling," 2023 IEEE 32nd International Symposium on Industrial Electronics (ISIE), Helsinki, Finland, 2023, pp. 1-6, doi: 10.1109/ISIE51358.2023.10228029.
Nikita Tafintsev, Dmitri Moltchanov, Shu-ping Yeh, Hosein Nikopour, Wei Mao, Oner Orhan, Shilpa Talwar, Mikko Valkama, Sergey Andreev: Joint Path Selection and Resource Allocation in Multi-Hop mmWave-based IAB Systems. IEEE International Conference on Communications (ICC), 2023.
Nikita Tafintsev, Alessandro Chiumento, Olga Vikhrova, Mikko Valkama, Sergey Andreev: Utilization of UAVs as Flying Base Stations in Urban Environments. International Congress on Ultra Modern Telecommunications and Control Systems (ICUMT), 2023.