Secrecy Rate Maximization for Symbiotic Radio Network with Relay-Obstacle
DOI:
https://doi.org/10.22399/ijcesen.413Keywords:
Sixth generation, secrecy rate, relay, symbiotic radio networks, eavesdroppers, Wireless communications, Simulation, Performance Evaluation, OptimizationAbstract
The idea that everything can communicate with each other with high bit rate and low latency is the main goal for next generation communication systems. In this context, allocating spectrum resources and providing energy to each device that can communicate is a big problem. In order to develop different techniques in this regard, symbiotic radio networks (SRNs) have been proposed in the literature. In SRN, devices transmit information to the same receiver by using the communication infrastructure together. However, this situation may create a security problem. In this paper, SRN with relay-obstacle is proposed to test physical layer security (PLS). This model is the first approach that maximizes the secrecy rate of SRN by using the ambient radio frequency resource in the presence of relay-obstacle. There are two different clusters in the system model and each cluster contains a device, a relay and an obstacle. An eavesdropper (ED) overhearing to the signals transmitted by the relays and is blocked by a cooperative jammer. The proposed system model is mathematically modeled and the secrecy rate expression is maximized over the time parameters. In the numerical analysis, the advantages of using the channel symbiotically compared to the nonsymbiotic scenario where the energy harvest-then-transmit (HTT) protocol is used in the literature are evaluated in terms of the reflection coefficient, noise power, signal transmission power and quality of service (QoS) of the devices and its superiority is revealed.
References
Dangi, R., Choudhary, G., Dragoni, N., Lalwani, P., Khare, U., & Kundu, S. (2023, December). 6G Mobile Networks: Key Technologies, Directions, and Advances. In Telecom 4(4);836-876.
DOI: 10.3390/telecom4040037
Janjua, M. B., & Arslan, H. (2023). A survey of symbiotic radio: methodologies, applications, and future directions. Sensors, 23(5), 2511
DOI: 10.3390/s23052511
Long, R., Liang, Y. C., Guo, H., Yang, G., & Zhang, R. (2019). Symbiotic radio: A new communication paradigm for passive Internet of Things. IEEE Internet of Things Journal, 7(2), 1350-1363.
DOI: 10.1109/JIOT.2019.2954678
Liang, Y. C., Long, R., Zhang, Q., & Niyato, D. (2022). Symbiotic communications: Where marconi meets darwin.IEEE Wireless Communications, 29(1),
DOI:144-150. 10.1109/MWC.101.2100132
Akyildiz, I. F., Lee, W. Y., Vuran, M. C., & Mohanty, S. (2008). A survey on spectrum management in cognitive radio networks. IEEE Communications magazine, 46(4), 40-48.
DOI: 10.1109/MCOM.2008.4481339
Onay, M. Y. (2024). Dynamic Time Allocation Based Physical Layer Security for Jammer-Aided Symbiotic Radio Networks. Radioenginering, 33(3), 443.
DOI: 10.13164/re.2024.0442
Hoang, D. T., Niyato, D., Wang, P., Kim, D. I., & Han, Z. (2017). Ambient backscatter: A new approach to improve network performance for RF-powered cognitive radio networks. IEEE Transactions on Communications, 65(9), 3659-3674.
DOI: 10.1109/TCOMM.2017.2710338
Liu, V., Parks, A., Talla, V., Gollakota, S., Wetherall, D., & Smith, J. R. (2013). Ambient backscatter: Wireless communication out of thin air. ACM SIGCOMM computer communication review, 43(4), 39-50. DOI: 10.1145/2534169.2486015
Srivastava, A., & Kaur, G. (2023). Cooperation and energy harvesting based spectrum sensing schemes for green cognitive radio networks. Transactions on Emerging Telecommunications Technologies, 34(3), e4714. DOI: 10.1002/ett.4714
Furqan, H. M., Solaija, M. S. J., Türkmen, H., & Arslan, H. (2021). Wireless communication, sensing, and REM: A security perspective. IEEE Open Journal of the Communications Society, 2, 287-321.
DOI: 10.1109/OJCOMS.2021.3054066
Solaija, M. S. J., Salman, H., & Arslan, H. (2022). Towards a unified framework for physical layer security in 5G and beyond networks. IEEE Open Journal of Vehicular Technology, 3, 321-343.
DOI: 10.1109/OJVT.2022.3183218
Yang, H., Ding, H., Elkashlan, M., Li, H., & Xin, K. (2023). A novel symbiotic backscatter-NOMA system. IEEE Transactions on Vehicular Technology, 72(8), 11006-11011.
DOI: 10.1109/TVT.2023.3259687
Nimi, T., & Babu, A. V. On the physical layer security performance of full‐duplex cooperative NOMA system with multiple eavesdroppers, imperfect SIC and hardware imperfections. Internet Technology Letters, e513. DOI: 10.1002/itl2.513
Li, X., Jiang, J., Wang, H., Han, C., Chen, G., Du, J., ... & Mumtaz, S. (2023). Physical layer security for wireless-powered ambient backscatter cooperative communication networks. IEEE Transactions on Cognitive Communications and Networking, 9(4), 927-939.
DOI: 10.1109/TCCN.2023.3270425
Li, D. (2020). Backscatter communication via harvest-then-transmit relaying. IEEE Transactions on Vehicular Technology, 69(6), 6843-6847.
DOI: 10.1109/TVT.2020.2991227
Onay, M. Y., & Ertug, O. (2023). Ambient Backscatter Communication Based Cooperative Relaying for Heterogeneous Cognitive Radio Networks. Radioengineering, 32(2).
DOI: 10.13164/re.2023.0236
Dursun, Y., Wang, K., & Ding, Z. (2022). Secrecy sum rate maximization for a MIMO-NOMA uplink transmission in 6G networks. Physical Communication, 53, 101675.
DOI: 10.1016/j.phycom.2022.101675
Hema, P. P., & Babu, A. V. (2024). Full‐duplex jamming for physical layer security improvement in NOMA‐enabled overlay cognitive radio networks. Security and Privacy, 7(3), e371.
DOI: 10.1002/spy2.371
Onay, M. Y., & ERTUĞ, Ö. (2023, July). Performance Analysis under Signal Jammer in Relay Aided Ambient Backscatter Cognitive Radio Networks. In 2023 31st Signal Processing and Communications Applications Conference (SIU) (pp. 1-4). IEEE.
Sun, J., Zhang, S., & Chi, K. (2021). Optimal time allocation for throughput maximization in backscatter assisted wireless powered communication networks. IET Communications, 15(12), 1620-1631.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 International Journal of Computational and Experimental Science and Engineering
This work is licensed under a Creative Commons Attribution 4.0 International License.