Optical-Fiber-Based Integrated Sensing and Communication Using Distributed Acoustic Sensing

Abstract

Distributed acoustic sensing (DAS) based on optical fibers has emerged as a powerful technology for real-time, long-range, and high-resolution monitoring in harsh environments, including underwater, underground, and downhole scenarios. While recent studies have explored data transmission using DAS systems, most approaches treat communication as a standalone function, while the simultaneous use of the same DAS infrastructure for independent distributed sensing remains underexplored and field-level validation is limited. In this work, we report an optical-fiber-based integrated sensing and communication (O-ISAC) framework that enables simultaneous distributed acoustic sensing and data communication over a single optical fiber. The system is implemented using a phase-sensitive optical time-domain reflectometry ($\Phi$-OTDR) architecture and a joint spatial–spectral signal-processing strategy that enables sensing and communication to coexist with no evident spectral interference under the tested conditions. To enhance communication robustness under fading and environmental noise, a convolutional neural network (CNN) is employed for data demodulation. The framework is validated through laboratory experiments and field deployment in a harbor canal, where distributed sensing captures boat-induced acoustic signatures at speeds ranging from approximately 2.5 to 8.6 m/s and in opposite traversal directions, while communication is maintained concurrently. Experimental results demonstrate reliable sensing alongside accurate data transmission, achieving a demodulation accuracy of 97.84% under laboratory integrated operation and consistently exceeding 95% under dynamic field conditions.