The information theoretical security for a cellular network in the presence of an eavesdropper is investigated in this research. The network is single-input-single-output (SISO) in nature. A small unmanned aerial vehicle (UAV) is aiding the network as a relay that follows the decode-and-forward (DF) protocol. The relay decodes the transmitted signal and retransmits it to the destination while repositioning itself if required. The allotted power of the UAV may not be enough for long-distance and long-duration travel. This article deals with the power needed for the data transmission so that the UAV can operate as a relay with less transmit power. However, the confidential data transmission between a base station and a mobile device is being intercepted by a passive eavesdropper. The security issue affects the transmit power and the outage situation. The theory of physical layer security is employed to ensure a secure wireless transmission. The secrecy parameters, namely, the secrecy capacity and the secrecy outage probability are investigated via mathematical derivations and computer programming. Additionally, optimizing the trajectory and allocation of the transmit power budget of the UAV will increase the network’s reliability. Our results show that the UAV relay can handle a secure transmission with its limited resources if a budget power allocation can be achieved along with an optimized trajectory.
Published in | American Journal of Networks and Communications (Volume 13, Issue 1) |
DOI | 10.11648/j.ajnc.20241301.15 |
Page(s) | 64-74 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
Copyright |
Copyright © The Author(s), 2024. Published by Science Publishing Group |
Power Allocation, Secrecy Capacity, Secrecy Outage Probability, Trajectory Optimization, UAV Relay
[1] | B. Li, Z. Fei and Y. Zhang. (2018). UAV Communications for 5G and Beyond: Recent Advances and Future Trends. IEEE Internet of Things Journal, pp. 1. |
[2] | S. Zeng, H. Zhang, K. Bian and L. Song. (2018). UAV relaying: Power allocation and trajectory optimization using decode-and-forward protocol. 2018 IEEE International Conference on Communications Workshops (ICC Workshops), pp. 1- 6. |
[3] | S. Zeng, H. Zhang, Q. He, K. Bian and L. Song. (2017). Joint trajectory and power optimization for UAV relay networks. IEEE Communications Letters, vol. 22, no. 1, pp. 161-164. |
[4] | Y. Zeng, R. Zhang and T. J. Lim. (2016). Throughput maximization for UAV-enabled mobile relaying systems. IEEE Transactions on Communications, vol. 64, no. 12, pp. 4983-4996. |
[5] | C. Shannon. (1949). Communication theory of secrecy systems. Bell System Technical Journal, vol. 29, pp. 656- 715. |
[6] | J. Barros and M. Rodrigues. (2006). “Secrecy capacity of wireless channels”, in Proc. IEEE Intl. Symposium on Information Theory, July, pp. 356-360. |
[7] | Z. Yuan, C. Chen, L. Bai, Y. Jin, and J. Choi. (2016). Secure relay beamforming with correlated channel models in dual-hop wireless communication networks. In Proc. of IEEE Global Commun. Conf. (GLOBECOM), December 4-8, pp. 1-6. |
[8] | Y. Jing and H. Jafarkhani (2008). Beamforming in wireless relay networks. In Proc. IEEE Inf. Theory and Applications Workshop, January 27-February 1, pp. 1-9. |
[9] | C. Masouros and T. Ratnarajah. (2012). Interference as a source of green signal power in cognitive relay- assisted co-existing MIMO wireless transmissions. IEEE Trans. on Commun., vol. 60, no. 2, pp. 525-536. |
[10] | J. E. Giti, M. Z. I. Sarkar, S. A. H. Chowdhury, M. M. Ali, and T. Ratnarajah. (2014). Secure wireless multicasting through co-existing MIMO radio systems. In Proc. of The 9thInternational Forum on Strategic Technology (IFOST), October 21-23, pp. 195-198. |
[11] | W. Liu, M. Z. I. Sarkar, T. Ratnarajah, and H. Du. (2016). Securing cognitive radio with a combined approach of beamforming and cooperative jamming. IET Commun., vol. 11, no. 1, pp. 1-9, December 22. |
[12] | Q. F. Zhou, F. C. M. Lau, and S. F. Hau. (2009). Asymptotic analysis of opportunistic relaying protocols. IEEE Trans. on Wireless Commun., vol. 8, no. 8, pp. 3915-3920. |
[13] | K. Elkhalil, M. E. Eltayeb, H. Shibli, H. R. Bahrami, and T. Y. Al-Naffouri. (2014). Opportunistic relay selection in multicast relay networks using compressive sensing. In Proc. of IEEE Global Commun. Conf. (GLOBECOM), December 8-12. |
[14] | L. Dong, Z. Han, A. P. Petropulu, and H. V. Poor. (2009). Cooperative jamming for wireless physical layer security. In Proceedings of IEEE/SP 15thWorkshop on Statistical Signal Processing, 2009 (SSP’09), Cardiff, Wales, UK, 31 Aug.-03 Sept., pp. 417- 420. |
[15] | H.-M. Wang, M. Luo, X.-G. Xia, and Q. Yin (2013), Joint cooperative beamforming and jamming to secure AF relay systems with individual power constraint and no eavesdropper’s CSI. IEEE Signal Processing Letters, vol. 20, no. 1, pp. 39-42. |
[16] | X. Guan, Y. Cai, Y. Wang, and W. Yang. (2011). Increasing secrecy capacity via joint design of cooperative beamforming and jamming. In Proc. of the 22ndAnnual IEEE International Sym. on Personal, Indoor and Mobile Radio Commun. (PIMRC): Fundamentals and PHY, September 11-14. |
[17] | E. R. Alotaibi and K. A. Hamdi. (2015). Optimal cooperative relaying and jamming for secure communication. IEEE Wireless Commun. Letts., vol. 4, no. 6, pp. 689-692. |
[18] | J. E. Giti, A. Sakzad, B. Srinivasan, J. Kamruzzaman, and R. Gaire. (2020). Friendly jammer against an adaptive eavesdropper in a relay-aided network. In Proc. 2020 International Wireless Communications and Mobile Computing (IWCMC), June 15-19, pp. 1707-1712. |
[19] | J. E. Giti, S. A. H. Chowdhury, and M. M. Ali. (2015). Enhancingsecurityinwirelessmulticastingwithselective precoding. International Journal of Systems, Control and Commun., vol. 6, no. 3. |
[20] | A. Kuhestani, A. Mohammadi, and M. Mohammadi. (2018). Joint relay selection and power allocation in large-scale MIMO systems with untrusted relays and passive eavesdroppers. IEEE Trans. on. Inf. Forensic. Sec., vol. 13, no. 2, pp. 341-355. |
[21] | W. Liu, M. Sarkar, and T. Ratnarajah. (2014). On the security of cognitive radio networks: Cooperative jamming with relay selection. In Proc. of European Conf. on Netw. and Commun. (EuCNC), June 23-26. |
[22] | J. E. Giti, B. Srinivasan, and J. Kamruzzaman. (2017). Impact of friendly jammers on secrecy multicast capacity in presence of adaptive eavesdroppers. In Proc. IEEE GLOBECOM Workshops (GC Wkshps), December 4-8, pp. 1-6. |
[23] | A. Ayyagari, J. Harrang, and S. Ray. (1996). Airborne information and reconnaissance network. In Proc. of IEEE Military Commun. Conf. (MILCOM), December 1-3, pp. 230-234. |
[24] | D. H. Choi, S. H. Kim, and D. K. Sung. (2014). Energy- efficient maneuvering and communication of a single UAV-based relay. IEEE Transactions on Aerospace and Electronic Systems, vol. 50, no. 3, pp. 2320-2327. |
[25] | A. Merwaday and I. Guvenc. (2015). UAV assisted heterogeneous networks for public safety communications. In proceedings of 2015 IEEE wireless communications and networking conference workshops (WCNCW), pp. 329-334. |
[26] | F. Cheng, S. Zhang, Z. Li, Y. Chen, N. Zhao, F. R. Yu, and V. C. M. Leung. (2018). UAV trajectory optimization for data offloading at the edge of multiple cells. IEEE Transactions on Vehicular Technology, vol. 67, no. 7, pp. 6732-6736. |
[27] | Y. Liang, L. Xiao, D. Yang and K. Lu. (2020). Joint trajectory and resource allocation optimization for two-way UAV-aided relaying network. In Proceedings of 2020 International Conference on Wireless Communications and Signal Processing (WCSP), pp. 376-381. |
[28] | T. M. Hoang, N. M. Nguyen, and T. Q. Duong. (2020). Detection of eavesdropping attack in UAV- aided wireless systems: Unsupervised learning with one- class SVM and K-means clustering. IEEE Wireless Commun. Letts., vol. 9, no. 2, pp.139-142. |
[29] | G. Sun, J. Li, A. Wang, Q. Wu, Z. Sun, and Y. Liu. (2022). Secure and energy-efficient UAV relay communications exploiting collaborative beamforming. IEEE Trans. on Commun., vol. 70, no. 8, pp. 5401-5416. |
[30] | X. Shi, A. Wang, G. Sun, J. Li, and X. Zheng. (2022). Air to air communications based on UAV-enabled virtual antenna arrays: A multi-objective optimization approach. in 2022 IEEE Wireless Communications and Networking Conference (WCNC), pp. 878-883. |
[31] | S. Elouarouar and H. Medromi. (2022). Multi-rotors unmanned aerial vehicles power supply and energy management. E3S Web Conf., vol. 336, p. 00068. |
[32] | L. Cwojdzi´ nski and M. Adamski. (2014). Power units and power supply systems in UAV. Aviation, vol. 18, no. 1, pp. 1-8. |
[33] | S. P. Boyd and L. Vandenberghe. (2004). Convex optimization. Cambridge University Press. |
[34] | D. P. Bertsekas. (1997). Nonlinear programming. Journal of the Operational Research Society, Taylor & Francis, vol. 48, no. 3, pp. 334-334. |
APA Style
Giti, J. E., Chowdhury, S. A. H., Moon, A. (2024). Trajectory Optimization and Power Allocation Scheme for a UAV Relay-aided Network in the Presence of an Eavesdropper. American Journal of Networks and Communications, 13(1), 64-74. https://doi.org/10.11648/j.ajnc.20241301.15
ACS Style
Giti, J. E.; Chowdhury, S. A. H.; Moon, A. Trajectory Optimization and Power Allocation Scheme for a UAV Relay-aided Network in the Presence of an Eavesdropper. Am. J. Netw. Commun. 2024, 13(1), 64-74. doi: 10.11648/j.ajnc.20241301.15
@article{10.11648/j.ajnc.20241301.15, author = {Jishan E Giti and Shah Ariful Hoque Chowdhury and Al-Hadith Moon}, title = {Trajectory Optimization and Power Allocation Scheme for a UAV Relay-aided Network in the Presence of an Eavesdropper}, journal = {American Journal of Networks and Communications}, volume = {13}, number = {1}, pages = {64-74}, doi = {10.11648/j.ajnc.20241301.15}, url = {https://doi.org/10.11648/j.ajnc.20241301.15}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajnc.20241301.15}, abstract = {The information theoretical security for a cellular network in the presence of an eavesdropper is investigated in this research. The network is single-input-single-output (SISO) in nature. A small unmanned aerial vehicle (UAV) is aiding the network as a relay that follows the decode-and-forward (DF) protocol. The relay decodes the transmitted signal and retransmits it to the destination while repositioning itself if required. The allotted power of the UAV may not be enough for long-distance and long-duration travel. This article deals with the power needed for the data transmission so that the UAV can operate as a relay with less transmit power. However, the confidential data transmission between a base station and a mobile device is being intercepted by a passive eavesdropper. The security issue affects the transmit power and the outage situation. The theory of physical layer security is employed to ensure a secure wireless transmission. The secrecy parameters, namely, the secrecy capacity and the secrecy outage probability are investigated via mathematical derivations and computer programming. Additionally, optimizing the trajectory and allocation of the transmit power budget of the UAV will increase the network’s reliability. Our results show that the UAV relay can handle a secure transmission with its limited resources if a budget power allocation can be achieved along with an optimized trajectory.}, year = {2024} }
TY - JOUR T1 - Trajectory Optimization and Power Allocation Scheme for a UAV Relay-aided Network in the Presence of an Eavesdropper AU - Jishan E Giti AU - Shah Ariful Hoque Chowdhury AU - Al-Hadith Moon Y1 - 2024/05/27 PY - 2024 N1 - https://doi.org/10.11648/j.ajnc.20241301.15 DO - 10.11648/j.ajnc.20241301.15 T2 - American Journal of Networks and Communications JF - American Journal of Networks and Communications JO - American Journal of Networks and Communications SP - 64 EP - 74 PB - Science Publishing Group SN - 2326-8964 UR - https://doi.org/10.11648/j.ajnc.20241301.15 AB - The information theoretical security for a cellular network in the presence of an eavesdropper is investigated in this research. The network is single-input-single-output (SISO) in nature. A small unmanned aerial vehicle (UAV) is aiding the network as a relay that follows the decode-and-forward (DF) protocol. The relay decodes the transmitted signal and retransmits it to the destination while repositioning itself if required. The allotted power of the UAV may not be enough for long-distance and long-duration travel. This article deals with the power needed for the data transmission so that the UAV can operate as a relay with less transmit power. However, the confidential data transmission between a base station and a mobile device is being intercepted by a passive eavesdropper. The security issue affects the transmit power and the outage situation. The theory of physical layer security is employed to ensure a secure wireless transmission. The secrecy parameters, namely, the secrecy capacity and the secrecy outage probability are investigated via mathematical derivations and computer programming. Additionally, optimizing the trajectory and allocation of the transmit power budget of the UAV will increase the network’s reliability. Our results show that the UAV relay can handle a secure transmission with its limited resources if a budget power allocation can be achieved along with an optimized trajectory. VL - 13 IS - 1 ER -