Beyond fifth generation wireless communication networks (B5G) are applied in many use-cases, such as industrial control systems, smart public transport, and power grids. Those applications require innovative techniques for timely transmission and increased wireless network capacities. Hence, this paper proposes optimizing the data freshness measured by the age of information (AoI) in dense internet of things (IoT) sensor-actuator networks. Given different priorities of data-streams, i.e., different sensitivities to outdated information, mixed-criticality is introduced by analyzing different functions of the age, i.e., we consider linear and exponential aging functions. An intricate non-convex optimization problem managing the physical transmission time and packet outage probability is derived. Such problem is tackled using stochastic reformulations, successive convex approximations, and fractional programming, resulting in an efficient iterative algorithm for AoI optimization. Simulation results validate the proposed scheme's performance in terms of AoI, mixed-criticality, and scalability. The proposed non-orthogonal transmission is shown to outperform an orthogonal access scheme in various deployment cases. Results emphasize the potential gains for dense B5G empowered IoT networks in minimizing the AoI.
翻译:第五代后第五代无线通信网络(B5G)应用到许多使用案例,如工业控制系统、智能公共交通和电网等,这些应用需要创新技术来及时传输和增加无线网络能力。因此,本文件建议优化在密集的事物互联网(IoT)传感器触动器网络中以信息年龄(AoI)衡量的数据更新度。鉴于数据流的不同优先事项,即对过时信息的不同敏感度,通过分析不同年龄功能,即我们考虑线性和指数性老化功能,采用混合临界度,即我们考虑线性和指数性老化功能。产生了复杂的非convex优化问题,对物理传输时间和包包出错概率进行管理。这些问题通过随机重整、连续的convex近似和分数程序处理,导致AoI优化的高效迭代算法。模拟结果验证了拟议方案在AoI、混合临界度和可伸缩性方面的性表现。在各种部署案例中,不垂直传输将Outal-toal adal AL 5 潜在A-E-E-E-BE-BE-BE-BE-BES-I-Slent-I-I-Es-Essssssssssviolvicolvilightmlightmlate res) res-violviolviolvicolvicol