A hardware module for Robust and Resilient UAVs Communications

Business Intelligence expects sales of UAVs to reach $12 billion in 2021. This future growth is expected to occur across three main sectors: 1) Consumer UAV shipments which are projected to reach 29 million in 2021; 2) Enterprise UAV shipments which are projected to reach 805,000 in 2021; 3) Government UAVs for combat and surveillance. Smart UAVs will provide a unique opportunity for UAV manufacturers to utilise new technological trends to overcome the current challenges of UAV applications.

In the very near future, the number of connected mobile nodes and devices is expected to increase significantly. The demand for high throughput, safe and secure communications and interoperability with lower energy consumption drive the industry and research efforts for the development of technologies to fulfil these requirements.

The application of UAVs in support of public safety communications is shrouded by privacy concerns and a lack of comprehensive policies, regulations, and governance for UAVs. Furthermore, there are several challenges and needed future extensions to facilitate the use of UAVs in support of ITS applications. One of the important challenges is to preserve the privacy of sensitive information (e.g., location) from other vehicles and drones. Since usually there is no encryption on UAVs onboard chips, they can be hijacked and subjected to man-in-middle attacks originating up to two kilometres away. UAVs that are used to gather sensitive information might become targets for malicious software seeking to steal data.

The proposal addresses these different challenges on UAV applications by looking at diversity techniques and how these could be combined with efficient encoding schemes.

The PhD student will develop a hardware module for secure and resilient communication between multi- Unmanned Aerial Vehicle (UAV) systems. The scheme leverages state-of-the-art encoding and decoding structures and unique algorithmic processes to achieve optimal communications in high mobility scenarios for UAVs while overcomes specific challenges in existing systems. The module will be resistant to radio interference and interception attacks, can be easily deployed in a wide range of drone communication settings and is fully interoperable with existing hardware.

The candidate should have earned an MSc degree, or equivalent, in one of the following fields: wireless communications, digital communications, information theory, signal processing, applied mathematics. He/She should have a strong background in digital communications and information theory as well as in signal processing for wireless communications. The candidate should be familiar with Matlab and C/C++ language or Python. The qualified candidate should also be knowledgeable in hardware architecture design for VHDL and FPGA implementation.  Knowledge in UAVs and cybersecurity would be an advantage. Preferably full-time students, however, part-time applicants are welcome!

1. H. Shakhatreh et al., "Unmanned Aerial Vehicles (UAVs): A Survey on Civil Applications and Key Research Challenges," in IEEE Access, vol. 7, pp. 48572-48634, 2019, doi: 10.1109/ACCESS.2019.2909530.
2. Hildmann, H.; Kovacs, E. Review: Using Unmanned Aerial Vehicles (UAVs) as Mobile Sensing Platforms (MSPs) for Disaster Response, Civil Security and Public Safety. Drones 2019, 3, 59.
3. F. Mohammed, A. Idries, N. Mohamed, J. Al-Jaroodi and I. Jawhar, "UAVs for smart cities: Opportunities and challenges," 2014 International Conference on Unmanned Aircraft Systems (ICUAS), Orlando, FL, 2014, pp. 267-273, doi: 10.1109/ICUAS.2014.6842265.
4. Kbaier Ben Ismail, D., Douillard, C. & Kerouédan, S. Analysis of three-dimensional turbo codes. Ann. Telecommun. 67, 257–268 (2012). https://doi.org/10.1007/s12243-011-0270-y.
5. Q. Yan, H. Zeng, T. Jiang, M. Li, W. Lou and Y. T. Hou, "MIMO-based jamming resilient communication in wireless networks," IEEE INFOCOM 2014 - IEEE Conference on Computer Communications, Toronto, ON, 2014, pp. 2697-2706, doi: 10.1109/INFOCOM.2014.6848218.
6. P. Chandhar and E. G. Larsson, "Massive MIMO for Connectivity With Drones: Case Studies and Future Directions," in IEEE Access, vol. 7, pp. 94676-94691, 2019, doi: 10.1109/ACCESS.2019.2928764.
7. C. Yan, L. Fu, J. Zhang and J. Wang, "A Comprehensive Survey on UAV Communication Channel Modeling," in IEEE Access, vol. 7, pp. 107769-107792, 2019, doi: 10.1109/ACCESS.2019.2933173.
8. P. Chandhar, D. Danev and E. G. Larsson, "Massive MIMO as enabler for communications with drone swarms," 2016 International Conference on Unmanned Aircraft Systems (ICUAS), Arlington, VA, 2016, pp. 347-354, doi: 10.1109/ICUAS.2016.7502655.
9. Berrou C, Graell-i-Amat A, Ould-Cheikh-Mouhamedou Y, Douillard C, Saouter Y: Adding a rate-1 third dimension to turbo codes. In Proc. IEEE Inform. Theory Workshop. Lake Tahoe; 2007:156-161.
10. Berrou C, Graell-i-Amat A, Ould-Cheikh-Mouhamedou Y, Saouter Y: Improving the distance properties of turbo codes using a third component code: 3D turbo codes. IEEE Trans Commun 2009, 57(9):2505-2509.
11. Kbaier, D., Douillard, C. & Kerouédan, S. A survey of three-dimensional turbo codes and recent performance enhancements. J Wireless Com Network 2013, 115 (2013). https://doi.org/10.1186/1687-1499-2013-115.
12. P. Golani, G. D. Dimou, M. Prakash and P. A. Beerel, "Design of a High-Speed Asynchronous Turbo Decoder," 13th IEEE International Symposium on Asynchronous Circuits and Systems (ASYNC'07), Berkeley, CA, 2007, pp. 49-59, doi: 10.1109/ASYNC.2007.16.
13. Y. Zeng, R. Zhang and T. J. Lim, "Wireless communications with unmanned aerial vehicles: opportunities and challenges," in IEEE Communications Magazine, vol. 54, no. 5, pp. 36-42, May 2016, doi: 10.1109/MCOM.2016.7470933.
14. M. Mozaffari, W. Saad, M. Bennis, Y. Nam and M. Debbah, "A Tutorial on UAVs for Wireless Networks: Applications, Challenges, and Open Problems," in IEEE Communications Surveys & Tutorials, vol. 21, no. 3, pp. 2334-2360, thirdquarter 2019, doi: 10.1109/COMST.2019.2902862.
15. T. Izydorczyk, G. Berardinelli, P. Mogensen, M. M. Ginard, J. Wigard and I. Z. Kovács, "Achieving High UAV Uplink Throughput by Using Beamforming on Board," in IEEE Access, vol. 8, pp. 82528-82538, 2020, doi: 10.1109/ACCESS.2020.2991658.
16. J. P. Yaacoub, H. Noura, O. Salman, A. Chehab, “Security analysis of drones systems: Attacks, limitations, and recommendations,” in Internet of Things, Volume 11, 2020, https://doi.org/10.1016/j.iot.2020.100218.
17. C. Berrou and A. Glavieux. Reflections on the Prize Paper: Near optimum errorcorrecting coding and decoding: Turbo-Codes. IEEE Information Theory SocietyNewsletter, 48(2):24-31, June 1998.
18. S. Haykin, M. Sellathurai, Y. de Jong and T. Willink, "Turbo-MIMO for wireless communications," in IEEE Communications Magazine, vol. 42, no. 10, pp. 48-53, Oct. 2004, doi: 10.1109/MCOM.2004.1341260.
19. C. Berrou, G. i Amat, and Y. Saouter. Improving the distance properties of turbocodes using a third component code: 3D turbo codes. IEEE Transactions on Communications,57(9):2505-2509, September 2009.
20. Banerjee, S., Chattopadhyay, S. Performance Analysis of Four Dimensional Turbo Code (4D-TC) Using Moment Based Simplified Augmented State Diagram (MSASD) Approach: Extension to LTE System. Wireless Pers Commun 108, 2077–2102 (2019). https://doi.org/10.1007/s11277-019-06510-y
21. A. A. Khuwaja, Y. Chen, N. Zhao, M. Alouini and P. Dobbins, "A Survey of Channel Modeling for UAV Communications," in IEEE Communications Surveys & Tutorials, vol. 20, no. 4, pp. 2804-2821, Fourthquarter 2018, doi: 10.1109/COMST.2018.2856587.

Contact

Dr Dhouha Kbaier