Cross-Layer Anti-Jamming Scheme: A Hierarchical Learning Approach | Zendy

Chen Han | Zendy; Yingtao Niu | Zendy

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Cross-Layer Anti-Jamming Scheme: A Hierarchical Learning Approach

Author(s) -

Chen Han,

Yingtao Niu

Publication year - 2018

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2018.2847045

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

This paper investigates the cross-layer optimization for anti-jamming in the network and MAC layers, in which the jammer can adjust the jamming policies to maximize the jamming effectiveness. The joint problem of routing selection, channel allocation, and power control is formulated as a Stackelberg game. The jammer leads the game by choosing the optimal jamming power and channels. The user follows by selecting the optimal nodes and corresponding channels, and adjusts its transmitting power to meet the communication requirement. Then, based on Q-learning, a cross-layer anti-jamming learning algorithm is proposed to obtain the Stackelberg equilibrium. Finally, simulation results are presented to verify the effectiveness of the proposed algorithm.

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