基于Q-learning的RFID多阅读器防碰撞算法

Anti-collision Algorithm Based on Q-learning for RFID Multiple Readers

为了解决无线射频识别(RFID)系统中多阅读器与标签通信的碰撞问题,文中将此问题建模为马尔可夫决策过程,并提出了一种基于Q-learning的防碰撞算法。该算法通过智能体agent不断与周围环境进行交互和学习,从而产生Q值函数,得到最佳信道分配策略;取消了HiQ算法中复杂的分层结构,简化了系统模型,引入ε贪婪策略以得到全局最优解,改进奖赏函数以得到最优状态。仿真结果表明,与HiQ算法和EHiQ算法相比,该智能算法能够自适应地为阅读器分配不同的信道来进行数据传输,从而有效降低碰撞率,提高信道利用率和吞吐率。

Due to the collision problem between multiple readers and tags communication in RFID system,this paper modeled the problem as a Markov decision process,and proposed an anti-collision algorithm based on Q-learning.By continuously interacting with the environment,the Q-value function is generated,as well as the optimal channel resources allocation.The complex hierarchical structure in HiQ algorithm is eliminated for simplifying the system model.The algorithm not only imports the concept ofε-greedy strategy to obtain the global optimal solution,but also improves the reward function to get the best state.Simulation results show that compared with HiQ and EHiQ,this intelligent algorithm can adaptively assign different channels to the reader for data transmission,therefore reduces the collision rate and improves the channel utilization and throughput rate.