Emerging integrated sensing and communication (ISAC) applications require large volumes of data, but collecting such datasets in real networks is costly, time consuming, and often infeasible due to limited access to low level measurements. In this paper we present NextSense, an open and modular semi-synthetic data generation platform that consists of a 5G stack, a channel emulator, and an UE emulator. The platform allows users full customization on radio configuration, channel and mobility, and traffic profiles through an API and GUI, and produces multi-perspective outputs that combine symbol-level IQ samples, protocol traces, and key performance indicators across UE, RAN, and CN. This paper describes the NextSense's architecture, and validates its ability to act as a faithful proxy for real measurements in sensing use cases.

翻译：新兴的集成感知与通信（ISAC）应用需要大量数据，但在真实网络中采集此类数据集成本高、耗时长，且往往因难以获取低层级测量数据而不可行。本文提出NextSense——一个开放且模块化的半合成数据生成平台，包含5G协议栈、信道仿真器和用户设备仿真器。该平台通过API和GUI允许用户完全自定义无线电配置、信道与移动性设置以及流量特征，并生成融合符号级IQ样本、协议轨迹及跨UE、RAN和CN关键性能指标的多视角输出。本文描述了NextSense的架构，并验证了其在感知场景中作为真实测量数据忠实代理的能力。