Modern cellular infrastructure has grown in complexity and become an ecosystem that includes the host technologies, such as 4G Long Term Evolution (LTE) and 5G New Radio (NR), along with subsystems such as narrowband Internet of Things (NB-IoT), category M1 (Cat-M1/LTE-M), observed time difference of arrival (OTDOA) and support for 4G/5G coexistence using dynamic spectrum sharing (DSS). Such an increased complexity has driven the need for network monitoring to enable load tracking, congestion control, spectral efficiency analysis, intrusion detection, and cognitive radio communications. However, no approach can passively monitor the entire cellular ecosystem because some reservations are configured with high-layer messages that are only accessible to in-network, active, and sometimes user-specific equipment. In this work, we design the Resource Analyzer for Variable Ecosystem Networks (RAVEN) to monitor the individual technologies within the cellular ecosystem. RAVEN reduces the synchronization search space for multiple subsystems and enables a fine-grained subsystem-level tracking of spectrum usage. RAVEN also provides a method to detect anomalies and find subsystems that are not yet supported. RAVEN is validated through simulation and live experiments and is compared to other cellular network monitors.

中文翻译：

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蜂窝网络生态系统的认知资源分析器

现代蜂窝基础设施变得越来越复杂，并成为一个生态系统，其中包括 4G 长期演进 (LTE) 和 5G 新无线电 (NR) 等主机技术，以及窄带物联网 (NB-IoT) 等子系统，类别M1 (Cat-M1/LTE-M)、观测到的到达时间差 (OTDOA) 并支持使用动态频谱共享 (DSS) 的 4G/5G 共存。这种增加的复杂性推动了对网络监控的需求，以实现负载跟踪、拥塞控制、频谱效率分析、入侵检测和认知无线电通信。但是，没有任何方法可以被动地监控整个蜂窝生态系统，因为某些预留配置了高层消息，这些消息只能由网络内、活动的，有时是用户特定的设备访问。在这项工作中，我们设计了可变生态系统网络资源分析器 (RAVEN) 来监控蜂窝生态系统中的各个技术。RAVEN 减少了多个子系统的同步搜索空间，并实现了对频谱使用的细粒度子系统级跟踪。RAVEN 还提供了一种方法来检测异常并查找尚不支持的子系统。RAVEN 通过模拟和现场实验进行验证，并与其他蜂窝网络监视器进行比较。