基于三维q -学习的多参数智能通信抗干扰方法

Ziming Pu, Yingtao Niu, Guoliang Zhang
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引用次数: 1

摘要

针对传统智能通信抗干扰算法的不足,提出了一种基于三维q -学习(3DQL)的无线通信多参数智能抗干扰方法。在多信道随机干扰情况下,无线通信系统通过学习信道、时隙和干扰功率的随机变化规律,引导发射机在每个时隙选择最优的信道和功率进行通信或保持沉默,达到最优决策精度和时隙利用率的抗干扰效果。仿真结果表明,3DQL算法在决策精度和槽利用率方面都优于传统的二维Q-learning (2DQL)算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Multi-Parameter Intelligent Communication Anti-Jamming Method Based on Three-Dimensional Q-Learning
Aiming at the deficiency of the traditional intelligent communication anti-jamming algorithms, a multi-parameter intelligent anti-jamming method for wireless communication based on three-dimensional Q-learning (3DQL) is proposed. In the case of multi-channel random jamming, the wireless communication system guides the transmitter to choose the optimal channel and power for communication or keep silent in each timeslot by learning the random variation law of channel, timeslot and power of jamming, achieving the anti-jamming effect of optimal decision accuracy and timeslot utilization. Simulation results show that the 3DQL algorithm is better than the traditional two-dimensional Q-learning (2DQL) algorithm in decision accuracy and slot utilization.
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