ADAPTIVE INTERFERENCE SUPPRESSION IN WIRELESS NETWORKS BASED ON ARTIFICIAL NOISE
DOI:
https://doi.org/10.18372/2410-7840.26.20015Abstract
Adaptive interference suppression based on artificial noise is a promising approach to enhancing the security of wireless networks. In traditional cryptographic protection systems, attackers can exploit physical-layer attacks to intercept signals. One of the effective protection methods is the use of artificial noise (AN), which generates specially designed interference to complicate unauthorized access. This paper investigates the principles of adaptive artificial noise power control using the gradient descent method. The proposed approach enables dynamic noise level regulation based on communication channel parameters such as attacker distance, signal strength, and environmental interference. The modeling was conducted using an open-source wireless sensor network (WSN) dataset, allowing us to evaluate the impact of adaptive noise on packet loss and signal strength. The results demonstrate that the optimized method effectively reduces the probability of interception without significantly degrading the communication quality for legitimate users. The proposed model can be applied in modern mobile communication systems, IoT networks, and critical infrastructures requiring an increased level of data protection.
References
Phan N. N., Nguyen S. Q. Artificial Noise-aided Adaptive Secure Transmissions. 2022 International Conference on Advanced Technologies for Communications. Ha Noi, Vietnam, 20-22 October 2022. P. 230-
doi: 10.1109/ATC55345.2022.9942978.
Kang T. et al. Federated Low-Rank Adaptation with Differential Privacy over Wireless Networks. arXiv preprint arXiv:2411.07806, 2024. [Online]. Available: https://arxiv.org/abs/2411.07806.
Rajabi M.E., Khaleghi Bizaki H., Shafiee M. Adaptive Wireless Covert Communication with Full/Half- Duplex Transceiver using Artificial Noise. Arab J Sci Eng. 2024. doi: 10.1007/s13369-024-09800-1.
Khodadadi H. R., Falsafi S. Improvement of security in wireless communication networks with directional modulation and artificial noise. Scientific Journal of Electronical & Cyber Defence. 2023. [Online]. Available: https://www.sid.ir/fileserver/jf/1134-267714-fa-1082998.pdf
Ju Y. et al. Artificial noise hopping: A practical secure transmission technique with experimental analysis for millimeter wave systems. IEEE Systems Journal. 2020. Vol. 14, iss. 4. P. 5121-5132. doi: 10.1109/JSYST.2020.2976852.
Wang S. et al. Artificial noise aided hybrid analog-digital beamforming for secure transmission in MIMO millimeter wave relay systems. IEEE Access. 2019. Vol. 7. P. 28597-28606. doi: 10.1109/ACCESS.2019.2902144.
Yang N., Elkashlan M., Duong T. Q. Optimal transmission with artificial noise in MISOME wiretap channels. IEEE Transactions on Wireless Communications. 2015. Vol. 14, no. 5. P. 2476-2490. [Online]. Available: http://www.eecs.qmul.ac.uk/~maged/Optimal%20transmission%20with%20artificial%20noise%20in%20MI SOME%20wiretap%20channels.pdf
Wang W. et al. On the impact of adaptive eavesdroppers in multi-antenna cellular networks. IEEE Transactions on Communications. 2017. Vol. 65, no. 8. P. 3424-3437. doi: 10.1109/TIFS.2017.2746010.
Zhou X., McKay M. R. Secure transmission with artificial noise over fading channels: Achievable rate and optimal power allocation. IEEE Transactions on Vehicular Technology. 2010. Vol. 59, no. 6. P. 3831-3842. [Online]. Available: https://arxiv.org/pdf/1006.5938
Wang P. et al. Resource allocation optimization for secure multidevice wirelessly powered backscatter communication with artificial noise. IEEE Transactions on Wireless Communications. 2022. Vol. 21, no. 4.
P. 2532-2547. doi: 10.1109/TWC.2022.3162137.
Khemapech I., Miller A., Duncan I. A survey of transmission power control in wireless sensor networks. Proceedings of PGNet, 2007. P. 15-20.
Hung C. W. et al. Transmission power control in wireless sensor networks using fuzzy adaptive data rate. Sensors. 2022. Vol. 22, no. 24. [Online]. Available: https://www.mdpi.com/1424-8220/22/24/9963.

Downloads
Published
Issue
Section
License
Authors who publish with this journal agree to the following terms:- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).