A Game-Theoretic Learning Approach for Anti-Jamming Dynamic Spectrum Access in Dense Wireless Networks

In this paper, we investigate the anti-jamming channel selection problem for interference mitigation (IM) based dense wireless networks in dynamic environment, in which the active user set is variable due to their specific traffic demands. We jointly consider the mutual interference among users and external jamming in IM-based dense wireless networks, and propose a generalized maximum protocol interference and jamming model to accurately capture the mutual interference and external jamming. Then, the anti-jamming channel selection problem is formulated as an anti-jamming dynamic game, and subsequently it is proved to be an exact potential game, which has at least one pure strategy Nash equilibrium (NE). Based on the stochastic learning theory, a distributed anti-jamming channel selection algorithm (DACSA) is proposed to find the NE solution. Moreover, the simulation results are presented to demonstrate the effectiveness of the proposed DACSA algorithm.

[1]  Alagan Anpalagan,et al.  Anti-Jamming Communications Using Spectrum Waterfall: A Deep Reinforcement Learning Approach , 2017, IEEE Communications Letters.

[2]  V. V. Phansalkar,et al.  Decentralized Learning of Nash Equilibria in Multi-Person Stochastic Games With Incomplete Information , 1994, IEEE Trans. Syst. Man Cybern. Syst..

[3]  Alagan Anpalagan,et al.  Distributed Channel Selection for Interference Mitigation in Dynamic Environment: A Game-Theoretic Stochastic Learning Solution , 2014, IEEE Transactions on Vehicular Technology.

[4]  Xi Fang,et al.  Coping with a Smart Jammer in Wireless Networks: A Stackelberg Game Approach , 2013, IEEE Transactions on Wireless Communications.

[5]  Yuan Wu,et al.  Distributed Power Allocation Algorithm for Spectrum Sharing Cognitive Radio Networks with QoS Guarantee , 2009, IEEE INFOCOM 2009.

[6]  Yuhua Xu,et al.  A hierarchical learning approach to anti-jamming channel selection strategies , 2019, Wirel. Networks.

[7]  Alagan Anpalagan,et al.  Distributed Channel Selection in Time-Varying Radio Environment: Interference Mitigation Game With Uncoupled Stochastic Learning , 2013, IEEE Transactions on Vehicular Technology.

[8]  Anthony Ephremides,et al.  Jamming games in wireless networks with incomplete information , 2011, IEEE Communications Magazine.

[9]  Meixia Tao,et al.  Game Theoretic Multimode Precoding Strategy Selection for MIMO Multiple Access Channels , 2010, IEEE Signal Processing Letters.

[10]  Lajos Hanzo,et al.  A Survey on Wireless Security: Technical Challenges, Recent Advances, and Future Trends , 2015, Proceedings of the IEEE.

[11]  Liang Xiao,et al.  Anti-Jamming Transmission Stackelberg Game With Observation Errors , 2015, IEEE Communications Letters.

[12]  Yuhua Xu,et al.  Self-Organizing Hit Avoidance in Distributed Frequency Hopping Multiple Access Networks , 2017, IEEE Access.

[13]  Qihui Wu,et al.  Distributed Channel Access for Device-to-Device Communications: A Hypergraph-Based Learning Solution , 2017, IEEE Communications Letters.

[14]  Marwan Krunz,et al.  Joint Adaptation of Frequency Hopping and Transmission Rate for Anti-Jamming Wireless Systems , 2016, IEEE Transactions on Mobile Computing.

[15]  Koji Yamamoto,et al.  A Comprehensive Survey of Potential Game Approaches to Wireless Networks , 2015, IEICE Trans. Commun..

[16]  Jianjun Jing,et al.  Distributed ABS-Slot Access in Dense Heterogeneous Networks: A Potential Game Approach With Generalized Interference Model , 2017, IEEE Access.

[17]  Zhu Han,et al.  Hypergraph based resource allocation for cross-cell device-to-device communications , 2016, 2016 IEEE International Conference on Communications (ICC).

[18]  Zhu Han,et al.  Radio Resource Allocation for Device-to-Device Underlay Communication Using Hypergraph Theory , 2016, IEEE Transactions on Wireless Communications.

[19]  Alain Bretto,et al.  Hypergraph Theory: An Introduction , 2013 .

[20]  Alagan Anpalagan,et al.  Opportunistic Spectrum Access in Unknown Dynamic Environment: A Game-Theoretic Stochastic Learning Solution , 2012, IEEE Transactions on Wireless Communications.

[21]  H. Vincent Poor,et al.  User-Centric View of Jamming Games in Cognitive Radio Networks , 2015, IEEE Transactions on Information Forensics and Security.

[22]  K. J. Ray Liu,et al.  Anti-Jamming Games in Multi-Channel Cognitive Radio Networks , 2012, IEEE Journal on Selected Areas in Communications.

[23]  K. J. Ray Liu,et al.  An anti-jamming stochastic game for cognitive radio networks , 2011, IEEE Journal on Selected Areas in Communications.

[24]  Alagan Anpalagan,et al.  Opportunistic Spectrum Access in Cognitive Radio Networks: Global Optimization Using Local Interaction Games , 2012, IEEE Journal of Selected Topics in Signal Processing.

[25]  Qiao Li,et al.  Maximal Scheduling in Wireless Ad Hoc Networks With Hypergraph Interference Models , 2012, IEEE Transactions on Vehicular Technology.

[26]  Zhu Han,et al.  Byzantine Attack and Defense in Cognitive Radio Networks: A Survey , 2015, IEEE Communications Surveys & Tutorials.

[27]  Alagan Anpalagan,et al.  Dynamic Spectrum Access in Time-Varying Environment: Distributed Learning Beyond Expectation Optimization , 2015, IEEE Transactions on Communications.

[28]  Alagan Anpalagan,et al.  Directed-Hypergraph-Based Channel Allocation for Ultradense Cloud D2D Communications With Asymmetric Interference , 2018, IEEE Transactions on Vehicular Technology.

[29]  Yueming Cai,et al.  Stochastic Game-Theoretic Spectrum Access in Distributed and Dynamic Environment , 2015, IEEE Transactions on Vehicular Technology.

[30]  L. Shapley,et al.  Potential Games , 1994 .

[31]  Yueming Cai,et al.  A Fully Distributed Algorithm for Dynamic Channel Adaptation in Canonical Communication Networks , 2013, IEEE Wireless Communications Letters.

[32]  Alagan Anpalagan,et al.  A Hierarchical Learning Solution for Anti-Jamming Stackelberg Game With Discrete Power Strategies , 2017, IEEE Wireless Communications Letters.

[33]  Yan Li,et al.  Power control with reinforcement learning in cooperative cognitive radio networks against jamming , 2015, The Journal of Supercomputing.

[34]  Alagan Anpalagan,et al.  Stackelberg Game Approaches for Anti-Jamming Defence in Wireless Networks , 2018, IEEE Wireless Communications.