Jamming resiliency and mobility management in cognitive communication networks

Adem, Nadia; Hamdaoui, Bechir

doi:10.1109/icc.2017.7996709

Cited by 11 publications

(4 citation statements)

References 19 publications

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“…When the jamming information was unavailable, authors in [25] proposed a method based on maximum likelihood estimation to obtain the parameter of jamming. RL techniques can be used to achieve an optimal communication policy via trial-and-error without being aware of the jamming and network model [26]. A two-dimensional anti-jamming mobile communication scheme has been proposed by applying RL techniques in [27] to obtain an optimal policy without any knowledge about the jamming models.…”

Section: Related Workmentioning

confidence: 99%

Learning-Based Multi-Domain Anti-Jamming Communication with Unknown Information

Li,

Wang,

Gao

2023

Electronics

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Due to the open nature of the wireless channel, wireless networks are vulnerable to jamming attacks. In this paper, we try to solve the anti-jamming problem caused by smart jammers, which can adaptively adjust the jamming channel and the jamming power. The interaction between the legitimate transmitter and the jammers is modeled as a non-zero-sum game. Considering that it is challenging for the transmitter and the jammers to acquire each other’s information, we propose two anti-jamming communication schemes based on the Deep Q-Network (DQN) algorithm and hierarchical learning (HL) algorithm to solve the non-zero-sum game. Specifically, the DQN-based scheme aims to solve the anti-jamming strategies in the frequency domain and the power domain directly, while the HL-based scheme tries to find the optimal mixed strategies for the Nash equilibrium. Simulation results are presented to validate the effectiveness of the proposed schemes. It is shown that the HL-based scheme has a better convergence performance and the DQN-based scheme has a higher converged utility of the transmitter. In the case of a single jammer, the DQN-based scheme achieves 80% of the transmitter’s utility of the no-jamming case, while the HL-based scheme achieves 63%.

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Section: Related Workmentioning

confidence: 99%

Learning-Based Multi-Domain Anti-Jamming Communication with Unknown Information

Li,

Wang,

Gao

2023

Electronics

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“…Rending to their high ability in learning, predicting patterns, and taking decisions accordingly, AI techniques, on the other hand, lead to enhancing wireless network performance in situations where legacy techniques fail to [15], [41], [42].…”

Section: Intelligence Of Future Network and Autonomymentioning

confidence: 99%

How Crucial Is It for 6G Networks to Be Autonomous?

Adem¹,

Benfaid²,

Harib³

et al. 2021

Preprint

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The sixth generation (6G), unlike any of the previous generations, is envisioned by 2030 to connect everything. Moreover, in addition to the new use cases 6G is expected to support, it will need to provide a superior performance over 5G. The global connectivity, large network dimensions, users heterogeneity, extremely low-power consumption, high throughput, ultrahigh reliability, efficient network operation and maintenance, and lowlatency requirements to be met by future networks inevitably necessitate the autonomy of 6G. Intelligence, facilitated mainly by the advancement of artificial intelligence (AI) techniques, is a key to achieve autonomy. In this paper, we provide a bird'seye view of 6G, its vision, progress, and objectives. Furthermore, we present some technologies that would be mainly enabling intelligent globally connected world. In addition to discussing the role of AI for future wireless communications, we, unlike any other review papers, provide our original results which give early evidence for the viability of achieving 6G networks autonomy through leveraging AI advances. Furthermore, we, very importantly, identify 6G implementation challenges and key innovative techniques that promise to solve them. This article serves as a starting point for learners to acquire more knowledge about 6G and also for researchers to promote more development to the field.

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“…In the works of Adem et al, 2 jamming mitigation techniques for CRNs, where mobile nodes are assumed to have no access to multiple channels during jamming, are provided. Both techniques rely on time‐based hopping and time evasion when jamming happens.…”

Section: Related Workmentioning

confidence: 99%

Batch‐based security‐aware spectrum sharing with simultaneous assignment decisions in time‐critical IoT networks with cognitive radio capabilities

Almajali

Ayyash

Elgala

2018

Trans Emerging Tel Tech

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Cognitive radio (CR) is considered as a key enabling communication technology that offers efficient wireless connectivity to Internet of Things (IoT) devices. Its integration with the future 5G architecture is expected to advance the IoT paradigm. Security attacks can severely degrade the performance of such CR‐based IoT (CRIoT) networks. The effect of security attacks can be reduced by implementing defensive approaches. However, such solutions come at the expense of degrading spectrum efficiency and consuming more network resources. In this paper, we investigate the spectrum sharing and access problem in a multidevice single‐transceiver CRIoT network with time‐critical applications under jamming attacks. Our main goal is to maximize the number of simultaneously served IoT devices over all available idle channels while ensuring delay requirement, hardware, link quality, security attacks, and spectrum utilization constraints. This problem is formulated as a total unimodular binary linear programming, which is shown to be solvable in polynomial time. Unlike most of previous security‐aware channel assignment solutions that conduct the channel assignment sequentially, our solution simultaneously provides secured distributed channel‐assignment decisions for multiple CRIoT links (batching method). Batching can be realized through an admission control stage for CR IoT devices to announce their control packets. Simulation results reveal that our solution significantly improves network performance compared to previous security‐aware schemes.

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Jamming resiliency and mobility management in cognitive communication networks

Cited by 11 publications

References 19 publications

Learning-Based Multi-Domain Anti-Jamming Communication with Unknown Information

Learning-Based Multi-Domain Anti-Jamming Communication with Unknown Information

How Crucial Is It for 6G Networks to Be Autonomous?

Batch‐based security‐aware spectrum sharing with simultaneous assignment decisions in time‐critical IoT networks with cognitive radio capabilities

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