An Improved CSMA/CA Protocol Anti-Jamming Method Based on Reinforcement Learning

Ming, Zidong; Liu, Xin; Yang, Xiaofei; Wang, Mei

doi:10.3390/electronics12173547

Cited by 3 publications

(1 citation statement)

References 28 publications

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“…Several techniques use idle/busy time to estimate network performance. Exploring the idle time duration is important in radio networks where networks reuse resources not only in the spatial and temporal domains [21]- [26].…”

Section: Introductionmentioning

confidence: 99%

Effectiveness of Vehicular Communication Using NP-CSMA with Bernoulli-Based Gaussian Interpolation Function

Iskandarani

2024

Int. J. Adv. Sci. Eng. Inf. Technol.

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The objective is to investigate the effectiveness of Gaussian arrival and its effect on vehicular communication compared to Bernoulli's arrival. MATLAB simulation covers three different levels of slot probability: low, medium, and high. The goal behind such simulation is to establish the importance of an adaptive function such as Gaussian interpolation resulting in smoother control of vehicular communication with better channel performance when compared to Bernoulli. This work shows that at low slot probability (Pslot), Gaussian arrival results in a much higher throughput (S) compared to Bernoulli, with a gradual reduction in throughput as Gaussian spread (γ) increases. The decrease in S as γ increases is due to the Gaussian interpolation, which performs control and results in higher channel stability. At mid probability, the simulation and analysis show a convergence between Gaussian results and Bernoulli, with differences in buffered frames (Btotal) as a function of γ. At a high Pslot value, Bernoulli produces higher S than Gaussian, with the closest Gaussian values at γ=2. However, the number of buffered frames using Bernoulli arrival is much higher than Gaussian. The exceedingly high Btotal can result in more collisions, which Gaussian arrival controls very well with a small sacrifice in throughput. The shape function for Bernoulli is shown to be different from Gaussian, except for specific values of γ, where there is a match. The obtained results show the adaptability and smoothness in which Gaussian arrival can optimize channel communication using Non-Persistent CSMA, which enables intelligent vehicular communication.

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Section: Introductionmentioning

confidence: 99%

Effectiveness of Vehicular Communication Using NP-CSMA with Bernoulli-Based Gaussian Interpolation Function

Iskandarani

2024

Int. J. Adv. Sci. Eng. Inf. Technol.

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Intelligent Anti-Jamming Based on Deep Reinforcement Learning and Transfer Learning

Janiar,

Wang

2024

IEEE Trans. Veh. Technol.

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One of the security issues in a wireless network is jamming attacks, where the jammer causes congestion and significant decrement in the network throughput by obstructing channels and disrupting user signals. In this thesis, we first develop a deep reinforcement learning (DRL) model to confront the jammer. However, training a DRL model from scratch may take a long time. We further propose a transfer learning (TL) approach to enable the DRL agent to learn fast in dynamic wireless networks to confront jamming attacks effectively. To make our proposed TL method adaptive to different network environments, we propose a novel method to quantitatively measure the difference between the source and target domains, using an integrated feature extractor. Afterward, based on the measured difference, we demonstrate how it can help choosing an efficient setting for the TL model leading to a fast and energy-efficient learning. We also show that the proposed TL method can effectively reduce the training time for the DRL model and outperforms other existing TL methods.Finally, I would like to thank my family and friends for their love, support, and encouragement. Their unwavering belief in me has been a source of strength and motivation, and I am deeply grateful for their presence in my life.Thank you all for making this thesis possible.

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A Torpor-based Enhanced Security Model for CSMA/CA Protocol in Wireless Networks

Akinwale,

Efiong,

Olajubu

et al. 2024

AETiC

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Mobile wireless networks enable the connection of devices to a network with minimal or no infrastructure. This comes with the advantages of ease and cost-effectiveness, thus largely popularizing the network. Notwithstanding these merits, the open physical media, infrastructural-less attributes, and pervasive deployment of wireless networks make the channel of communication (media access) vulnerable to attacks such as traffic analysis, monitoring, and jamming. This study designed a virtual local area network (VLAN) model to circumvent virtual jamming attacks and other intrusions at the Media Access Control (MAC) layer of the Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) protocol. A Torpor VLAN (TVLAN) Data Frame Encapsulation and the algorithm for T-VLAN security in CSMA/CA were formulated and presented. A simulation experiment was conducted on the model using OMNeT++ software. The performance metrics used to evaluate the model were packet delivery ratio, network throughput, end-to-end channel delay, and channel load. The simulation results show that the TVLAN defence mechanism did not increase the channel load arbitrarily during TVLAN defence. similarly, the system throughput was shown to be 82% during TVLAN defence. Nevertheless, the network delay of the system during TVLAN defence was significantly high but the channel load was 297 when the TVLAN security mechanism was launched. These results demonstrate the model’s ability to provide a survivability mechanism for critical systems when under attack and add a security layer to the CSMA/CA protocol in wireless networks. Such a remarkable performance is required of a CSMA/CA infrastructure for improving the cybersecurity posture of a wireless network.

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An Improved CSMA/CA Protocol Anti-Jamming Method Based on Reinforcement Learning

Cited by 3 publications

References 28 publications

Effectiveness of Vehicular Communication Using NP-CSMA with Bernoulli-Based Gaussian Interpolation Function

Effectiveness of Vehicular Communication Using NP-CSMA with Bernoulli-Based Gaussian Interpolation Function

Intelligent Anti-Jamming Based on Deep Reinforcement Learning and Transfer Learning

A Torpor-based Enhanced Security Model for CSMA/CA Protocol in Wireless Networks

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