NextSense: A Semi-Synthetic Sensing Data generation Platform

2026-03-21

AI Summary

This work addresses the scarcity of real-world sensing data that hinders integrated sensing and communication (ISAC) research, as acquiring high-fidelity measurements from operational networks is often prohibitively expensive or infeasible. To overcome this limitation, the authors present an open, modular, semi-synthetic data generation platform—the first customizable, multi-perspective ISAC data simulation framework. The platform tightly integrates a 5G protocol stack, channel emulator, and user equipment simulator, enabling flexible configuration of wireless parameters, channel models, mobility patterns, and traffic profiles via either an API or a graphical interface. It simultaneously outputs IQ samples, protocol-level traces, and key performance indicators. Experimental validation demonstrates that the generated data faithfully reproduces the statistical characteristics of real network measurements, thereby providing a reliable and scalable foundation for ISAC algorithm development and evaluation.

Technology Category

• Search and Optimization: Sampling/Simulation-based Search
• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Planning, Routing, and Scheduling: Plan Execution and Monitoring

Application Category

• Web Mining and Content Analysis: Web data generation and simulation
• Systems and Infrastructure for Web, Mobile and WoT: Data management and stream processing for Web, mobile and wireless applications
• Security and Privacy: Data transparency and provenance

Abstract

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.

Problem

• integrated sensing and communication
• sensing data
• data collection
• real-world measurements
• low-level measurements

Innovation

• semi-synthetic data generation
• integrated sensing and communication (ISAC)
• 5G emulation
• channel emulation
• multi-perspective sensing data