Two-Dimensional Antijamming Mobile Communication Based on Reinforcement Learning
Two-Dimensional Antijamming Mobile Communication Based on Reinforcement Learning
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DOI：
10.1109/tvt.2018.2856854
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发表时间：
2017-12
影响因子：
6.8
通讯作者：
Liang Xiao;Donghua Jiang;Dongjin Xu;Hongzi Zhu;Yanyong Zhang;H. V. Poor
中科院分区：
文献类型：
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作者：
Liang Xiao;Donghua Jiang;Dongjin Xu;Hongzi Zhu;Yanyong Zhang;H. V. Poor
通过使用智能无线电设备，干扰器可以基于相反的安全机制动态地改变其干扰策略;它甚至可以诱导移动终端进入特定的通信模式，然后相应地启动干扰策略。另一方面，移动的设备可以利用扩展频谱和用户移动性来解决阻塞和干扰。本文提出了一种二维抗干扰移动的通信方案，其中移动终端离开一个严重干扰的频率或区域。结果表明，通过应用强化学习技术，移动终端可以实现最佳的通信策略，而不需要知道的干扰和干扰模型和无线电信道模型在一个动态的游戏框架。更具体地说，提出了一种基于热引导深度Q网络的2-D移动的通信方案，该方案利用相似场景中的经验来减少游戏开始时的探索时间，并应用深度卷积神经网络和宏动作技术来加速动态情况下的学习。几个现实世界的情况下，模拟评估所提出的方法。这些仿真结果表明，我们提出的方案可以提高信号的信干噪比和效用的移动的设备对合作干扰与基准计划相比。
By using smart radio devices, a jammer can dynamically change its jamming policy based on opposing security mechanisms; it can even induce the mobile device to enter a specific communication mode and then launch the jamming policy accordingly. On the other hand, mobile devices can exploit spread spectrum and user mobility to address both jamming and interference. In this paper, a two-dimensional (2-D) antijamming mobile communication scheme is proposed in which a mobile device leaves a heavily jammed/interfered-with frequency or area. It is shown that, by applying reinforcement learning techniques, a mobile device can achieve an optimal communication policy without the need to know the jamming and interference model and the radio channel model in a dynamic game framework. More specifically, a hotbooting deep Q-network based 2-D mobile communication scheme is proposed that exploits experiences in similar scenarios to reduce the exploration time at the beginning of the game, and applies deep convolutional neural network and macro-action techniques to accelerate learning in dynamic situations. Several real-world scenarios are simulated to evaluate the proposed method. These simulation results show that our proposed scheme can improve both the signal-to-interference-plus-noise ratio of the signals and the utility of the mobile devices against cooperative jamming compared with benchmark schemes.