A Learning-Based Spectrum Access Stackelberg Game: Friendly Jammer-Assisted Communication Confrontation

Qi, Nan; Wang, Wei; Xiao, Ming; Jia, Luliang; Jin, Shi; Zhu, Qiuming; Tsiftsis, Theodoros A.

doi:10.1109/tvt.2021.3049653

Cited by 48 publications

(30 citation statements)

References 34 publications

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“…And the optimization problem in these works is often difficult to resolve with traditional optimization methods. Hence, to solve the above problem, we exploit secure channel access by channel switching [27][28][29][30] and propose a two-stage task and resource assignment method that exploits convex optimization theory [31] and fading memory joint strategy fictitious play with inertia (FM-JSFP) [32] to formulate the problem and resolve it.…”

Section: Researchmentioning

confidence: 99%

Distributed Energy-Efficient and Secure Offloading in Air-to-Ground MEC Networks

Liu

et al. 2021

Preprint

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This paper mainly investigates the energy-efficient and secure offloading problem in air-to-ground MEC networks. The proposed efficient offloading mechanism is as per the requirements of the heterogeneous tasks of ground users. Further, the optimizing offloading rate, offloading object, and channel access jointly formulate system energy consumption and eavesdropping rate minimization. A distributed two-stage offloading scheme is proposed for achieving the sub-optimal solution for the Mixed-integer Nonlinear Programming (MINLP) problem. Finally, simulation results demonstrate that the proposed scheme is superior to several benchmark schemes.

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Section: Researchmentioning

confidence: 99%

Distributed Energy-Efficient and Secure Offloading in Air-to-Ground MEC Networks

Liu

et al. 2021

Preprint

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“…Various methods have been proposed to implement the anti‐jamming communications such as game theory [28, 29], optimization theory [30] and machine learning[21, 32–34]. Stackelberg game was used to model users and the jammer into the leader and follower [28].…”

Section: Related Workmentioning

confidence: 99%

“…Various methods have been proposed to implement the anti-jamming communications such as game theory [28,29], optimization theory [30] and machine learning [21,[32][33][34].…”

Section: Related Workmentioning

confidence: 99%

Joint relay and channel selection against mobile and smart jammer: A deep reinforcement learning approach

et al. 2021

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This paper investigates the joint relay and channel selection problem using a deep reinforcement learning (DRL) algorithm for cooperative communications in a dynamic jamming environment. The latest types of jammers include the mobile and smart jammer that contains multiple jamming patterns. This new type of jammer poses serious challenges to reliable communications such as huge environment states, tightly coupled joint action selections and real-time decision requirements. To cope with these challenges, a DRLbased relay-assisted cooperative communication scheme is proposed. In this scheme, the joint selection problem is constructed as a Markov decision process (MDP) and a double deep Q network (DDQN) based anti-jamming scheme is proposed to address the unknown and dynamic jamming behaviors. Concretely, a joint decision-making network composed of three sub-networks is designed and the independent learning method of each sub-network is proposed. The simulation results show that the user agent is able to anticipate the jammer behaviors and elude the jamming in advance. Furthermore, compared with the sensing-based algorithm, the Q learning-based algorithm and the existing DRL-based anti-jamming approaches, the proposed algorithm maintains a higher average normalized throughput. INTRODUCTIONRelay-assisted cooperative communication technology has been considered as a direct technology that increases the system transmission rate and expands the communication coverage [1]. However, cooperative communications are vulnerable to malicious jamming signals, which calls for efficient anti-jamming technologies [2][3][4]. Several techniques such as power control, frequency hopping, backscatter and beamforming have been proposed to combat the malicious jamming [5][6][7][8].Recently, the authors [9, 10] summarize the jammers' behaviors in each domain and name them the jamming patterns. The policy of frequency decisions of the jammer can be regarded as the jamming pattern in frequency domain. As shown in Figure 1(a), in the comb pattern, the jammer transmits jamming signals at fixed frequency points [11]. Figure 1(b) illustrates the sweeping pattern where the jammer hops jamming signals at aThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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“…While considering the existence of malicious jamming attacks, the Stackelberg game [15][16][17][18][19][20][21][22][23][24][25][26][27] is a suitable game model to formulate the competitive interactions between the user-side and the jammer-side as it can well depict the sequential decision-making relationship between two countermeasure sides. For example, Yang et al formulated the anti-jamming power control problem using the Stackelberg game [15,16].…”

mentioning

confidence: 99%

“…Considering the multi-user anti-jamming scenario, in [20], a one-leader multi-follower Bayesian Stackelberg game was formulated, and the influence of observation error as well as mobility of unmanned aerial vehicles (UAVs) were investigated. Moreover, authors in [21] investigated the communication confrontation scenario, and modeled the interactions in the confrontation scenario as a Stackelberg game, with each player seeking for maximizing their utility respectively. However, there exist some main challenges to extend the above game approaches to the multi-user coordinated channel access scenario in the clustering networks with dynamic wide-band jamming attacks.…”

mentioning

confidence: 99%

Hierarchical coordinated anti-jamming channel access in clustering networks: a multi-leader multi-follower Stackelberg game approach

Chen

Feng

et al. 2021

EURASIP J. Adv. Signal Process.

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This paper mainly investigates the multi-user coordinated anti-jamming problem in clustering communication networks. In such kinds of networks, there exist multiple clusters and multiple users who communicate with their receivers simultaneously. Besides, a malicious jammer persistently attacks channels with wide-band and dynamic changing jamming signals. To cope with these challenges brought by the large-scale clustering network and the dynamic wide-band jamming, a hierarchical coordinated anti-jamming approach is proposed, and a multi-leader multi-follower Stackelberg game is introduced to model the anti-jamming problem. In detail, cluster heads act as leaders, and select available frequency bands to avoid jamming attacks, while users in each cluster act as followers and select corresponding channels distributedly and independently. Moreover, it is proved that there exist multiple Stackelberg equilibriums (SEs) in the proposed game. To obtain SEs, a hierarchical coordinated anti-jamming channel access (HCACA) algorithm is designed. Simulation results illustrate that the proposed approach is effective to cope with the dynamic wide-band jamming attacks. Furthermore, it is also depicted that the proposed approach outperforms the distributed anti-jamming comparative approach in terms of convergence speed.

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A Learning-Based Spectrum Access Stackelberg Game: Friendly Jammer-Assisted Communication Confrontation

Cited by 48 publications

References 34 publications

Distributed Energy-Efficient and Secure Offloading in Air-to-Ground MEC Networks

Distributed Energy-Efficient and Secure Offloading in Air-to-Ground MEC Networks

Joint relay and channel selection against mobile and smart jammer: A deep reinforcement learning approach

Hierarchical coordinated anti-jamming channel access in clustering networks: a multi-leader multi-follower Stackelberg game approach

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