Abstract The paper emphasises on the principles of O-ISAC such as coherent Lightwave modulation, spectrum recycling, and photonic signal processing which enable duality of operations to be realised seamlessly. By integrating sensing into the optical transmission, O-ISAC inherits the advantages of light such as high frequency, broad bandwidth, and low propagation delay, which is superior to the traditional RF-based ISAC. It has been shown by comparative study that OD integration shows better bandwidth scalability, lower energy consumption, and higher sensing resolution, which is a promising technology for the AI-based 6G ecosystem. To improve adaptation, the paper proposes an AI-based O-ISAC architecture. Machine learning and AI methods allow for adaptive resource allocation, joint perception-connectivity optimization, and intelligent orchestration among heterogeneous devices and apps. Simulation studies and experimental results also show the potential gains, including ∼65 % lower energy-per-bit consumption and over 2 × in enhancement of sensing accuracy with respect to the traditional dual-function systems. Last but not least, the abstract admits the deployment challenges, such as thermal management, fabrication yield, and standardization, which should tackle before the wide adoption. It ends with framing O-ISAC as a core nabling technology for scalable, sustainable, secure 6G networks, providing a road to a future-proof intelligent infrastructure.
Bansal et al. (Mon,) studied this question.
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