Sun Juan, Zhang Shubin, Yang Changsong, Huang Liang
College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310014, China.
Guangxi Key Laboratory of Cryptography and Information Security, Guilin University of Electronic Technology, Guilin 541004, China.
Entropy (Basel). 2022 Apr 24;24(5):596. doi: 10.3390/e24050596.
The Age of Information (AoI) measures the freshness of information and is a critic performance metric for time-sensitive applications. In this paper, we consider a radio frequency energy-harvesting cognitive radio network, where the secondary user harvests energy from the primary users' transmissions and opportunistically accesses the primary users' licensed spectrum to deliver the status-update data pack. We aim to minimize the AoI subject to the energy causality and spectrum constraints by optimizing the sensing and update decisions. We formulate the AoI minimization problem as a partially observable Markov decision process and solve it via dynamic programming. Simulation results verify that our proposed policy is significantly superior to the myopic policy under different parameter settings.
信息年龄（AoI）衡量信息的新鲜度，是对时间敏感型应用的关键性能指标。在本文中，我们考虑一个射频能量收集认知无线电网络，其中次级用户从初级用户的传输中收集能量，并机会性地接入初级用户的授权频谱以传输状态更新数据包。我们的目标是通过优化感知和更新决策，在能量因果关系和频谱约束条件下使AoI最小化。我们将AoI最小化问题表述为一个部分可观测马尔可夫决策过程，并通过动态规划求解。仿真结果验证了我们提出的策略在不同参数设置下明显优于近视策略。
