This project involves the following two aspects of wireless communication:

a) Backscatter communication (BSC) systems that comprise a power-unlimited reader and low-power tags. This technology thrives on its capability to use low-power and passive devices like envelope detectors, dividers, comparators, and impedance controllers, instead of more costly and bulkier conventional radio frequency (RF) chain components such as local oscillators, mixers, and converters. The BSC systems generally comprise a power-unlimited reader and low-power tags. As passive tags do not have transmission circuitry, they rely on carrier transmission from the emitter to power itself and backscatter its data to the reader by appending information to the backscattered carrier.

b) Unmanned Aerial Vehicle (UAV) networks: The growing demand for a higher data rate has presented a considerable challenge to the traditional cellular and IoT networks. UAVs are considered the next-generation systems to enhance current coverage because, owing to the aerial nature of UAVs, they can maintain line-of-sight (LoS) connection with the ground users leading to enhanced coverage and efficiency. Therefore, using UAVs as an aerial access point is desirable to improve wireless services and coverage in hotspot areas.


Electrical Engineering and Telecommunications

Research Area

Electrical engineering | Wireless communications | Signal processing | Computer communications networks | Optimisation | Machine learning | Vehicular technology and networks

Considering no prior knowledge of crucial system parameters like tags' location & channel statistics, the underlying different channel, location & mobility related parameters will be learned to present a distributed algorithm based on the deep reinforcement learning approach to be implemented at the UAV while getting the desired cooperation of the BSC tags. This will be a software simulation-based task so that it can be implemented with the help of an undergraduate student under my guidance over two months, as it will not require a complex mathematical framework.

The interested student needs to be good in MATLAB programming along with having basic knowledge of wireless communications and Machine Learning. I will be providing the lectures myself to teach the student about the advanced concepts that will be used as a part of his/her training for this project.

  1. One short paper in tier-1 IEEE communication conference with the undergraduate student. A poster presentation and a brief video highlighting the main findings will also be provided.
  2. One full transaction-type journal paper based on the extension of the conference paper to be led by me within two months after the end of this project.
  3. Training of an undergraduate student, motivating him to join higher degree research as HDR or PhD student later.
Senior Lecturer, ARC DECRA Fellow Deepak Mishra
Senior Lecturer, ARC DECRA Fellow
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  1. Y. -C. Liang, Q. Zhang, J. Wang, R. Long, H. Zhou and G. Yang, ""Backscatter Communication Assisted by Reconfigurable Intelligent Surfaces,"" in Proceedings of the IEEE, vol. 110, no. 9, pp. 1339-1357, Sept. 2022.
  2. M. Mozaffari, W. Saad, M. Bennis, Y. 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, Mar. 2019.
  3. N. Gupta, D. Mishra, and S. Agarwal, “Energy-aware trajectory design for outage minimization in UAV-assisted communication systems,” IEEE Transactions on Green Communications and Networking, vol. 6, no. 3, pp. 1751-1763, Jan. 2022.
  4. A. Agarwal and D. Mishra, “Altitude Optimization for DF Relaying Trajectory of UAV in Cooperative FANET,” in Proc. IEEE Global Communications (GLOBECOM), Taipei, Taiwan, December 2020, pp. 1-6.
  5. D. Mishra and E. G. Larsson, “Sum Throughput Maximization in Multi-Tag Backscattering to Multiantenna Reader,” IEEE Transactions on Communications, vol. 67, no. 8, pp 5689-5705, August 2019.
  6. P. Lohan and D. Mishra, “Utility-Aware Optimal Resource Allocation Protocol for UAV-Assisted Small Cells with Heterogeneous Coverage Demands,” IEEE Trans. Wireless Communications, vol. 19, no. 2, pp 1221-1236, Feb 2020.
  7. G. Prasad and D. Mishra, “Deep Learning Based Integrated Information and Energy Relaying in RF Powered Communication,” in Proc. IEEE ICC Workshop - SAGE: Green Solutions for Smart Environment, Montreal (Virtual), June 2021, pp. 1-6.
  8. D. Mishra and E. G. Larsson, “Optimal Channel Estimation for Reciprocity-Based Backscattering with a Full-Duplex MIMO Reader,” IEEE Transactions on Signal Processing, vol. 67, no. 6, pp. 1662-1677, March 2019.
  9. D. Mishra and E. G. Larsson, “Multi-Tag Backscattering to MIMO Reader: Channel Estimation and Throughput Fairness,” IEEE Transactions on Wireless Communications, vol. 18, no. 12, pp 5584-5599, December 2019.
  10. A. Agarwal and D. Mishra, “Hovering Localization and Power Allocation for UAV assisted DF Relaying Ad Hoc Network,” in Proc. IEEE ICC Workshop on Integrating UAVs into 5G and Beyond, Dublin, Ireland, June 2020, pp. 1-6.