Chameleon: Integrated Sensing and Communication with Sub-Symbol Beam Switching in mmWave Networks

2025-09-18

AI Summary

To address the decoupling of integrated sensing and communication (ISAC) in 5G millimeter-wave networks—where real-time operation and high performance are difficult to reconcile—this paper proposes a sub-symbol-level dynamic beam switching mechanism. It rapidly reconfigures beams within each PDSCH demodulation reference signal (DM-RS) period, enabling deep air-interface integration of communication and sensing. The approach synergistically combines large-scale MIMO beamforming, a 28 GHz software-defined radio platform, and a lightweight machine learning model. Experimental results demonstrate: aggregate downlink throughput of 0.80 Gbps for two users; 31×31-point 2D imaging completed in just 0.875 ms; median localization errors of 0.14 m (range) and 0.24° (angle); and 99.0% accuracy in material classification. This work pioneers sub-symbol-scale co-design of high-frame-rate sensing and high-throughput communication, breaking from conventional beam training paradigms and delivering a deployable air-interface architecture for 6G ISAC.

Technology Category

• Search and Optimization: Mixed Discrete/Continuous Search
• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Machine Learning: Hardware-aware ML

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Security and Privacy: Large-scale security measurements
• Search and Retrieval-Augmented AI: Retrieval-Augmented Generation (RAG) and multi-modal RAG

Abstract

Next-generation cellular networks are envisioned to integrate sensing capabilities with communication, particularly in the millimeter-wave (mmWave) spectrum, where beamforming using large-scale antenna arrays enables directional signal transmissions for improved spatial multiplexing. In current 5G networks, however, beamforming is typically designed either for communication or sensing (e.g., beam training during link establishment). In this paper, we present Chameleon, a novel framework that augments and rapidly switches beamformers during each demodulation reference signal (DMRS) symbol to achieve integrated sensing and communication (ISAC) in 5G mmWave networks. Each beamformer introduces an additional sensing beam toward target angles while maintaining the communication beams toward multiple users. We implement Chameleon on a 28 GHz software-defined radio testbed supporting over-the-air 5G physical downlink shared channel (PDSCH) transmissions. Extensive experiments in open environments show that Chameleon achieves multi-user communication with a sum data rate of up to 0.80 Gbps across two users. Simultaneously, Chameleon employs a beamformer switching interval of only 0.24 μs, therefore producing a 31x31-point 2D imaging within just 0.875 ms. Leveraging machine learning, Chameleon further enables object localization with median errors of 0.14 m (distance) and 0.24° (angle), and material classification with 99.0% accuracy.

Problem

• Integrating sensing and communication in 5G mmWave networks
• Rapid beam switching during demodulation reference symbols
• Simultaneous multi-user communication and high-resolution sensing

Innovation

• Sub-symbol beam switching for ISAC
• Maintains communication while sensing beams
• Machine learning enhances localization accuracy