基于mab的三层Stackelberg博弈的抗干扰中继通信离散功率控制方法

Zhibin Feng, Yijie Luo, Xueqiang Chen, Wen Li
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引用次数: 0

摘要

本文研究了抗干扰中继通信网络中的离散功率控制问题。基于发射机(用户和中继)与干扰机之间的等级竞争关系,构造了一个三层Stackelberg博弈模型,其中用户为领导,中继为副领导,干扰机为随从。从层次博弈论的角度出发,我们将功率优化问题表述为一个多臂抢匪(MAB)问题,其中用户、中继器和干扰器作为参与者,每个可选的功率策略作为一个手臂进行选择。基于MAB理论,给出了后悔函数来表示整个沟通过程的收益损失。为了最大限度地减少用户和继电器的遗憾,我们提出了一种基于ucb1的离散功率控制在线学习算法。仿真结果给出了所提出的抗干扰方案下的功率选择率和对数增量遗憾。在不同算法下,对用户和继电器的效用进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A MAB-Based Discrete Power Control Approach in Anti-jamming Relay Communication via Three-layer Stackelberg Game
In this paper, we investigate the discrete power control problem in anti-jamming relay communication networks. Based on the hierarchical competitive relationships between transmitters (user and relay) and jammer, a three-layer Stackelberg game is formulated, in which user acts as leader, relay acts as vice-leader and jammer acts as follower. From the perspective of hierarchical-game theoretic, we formulate the power optimization problem as a multi-armed bandit (MAB) problem, where user, relay and jammer act as players and each optional power strategy is considered as an arm to select. Based on MAB theory, we give the regret function to express the loss of payoff of the whole communication process. To minimize the regrets of user and relay, we propose a UCB1-based discrete power control online learning algorithm. Simulation results give the power selection rate and logarithmic incremental regrets in the proposed anti-jamming scenario. The user's and relay's utilities are also compared under different algorithms.
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