Integrated sensing and communication for next generation wireless systems

Abstract

Wireless communication systems inherently interact with their surrounding physi- cal environment, causing transmitted signals to carry information beyond the data

they are intended to convey. This observation forms the basis of Integrated Sensing

and Communication (ISAC), where sensing and communication are jointly sup- ported using the same wireless infrastructure. Despite its promise, realizing ISAC

in practical systems—particularly with commodity Wi-Fi—remains challenging due to high-dimensional channel representations, compute intensive channel sounding,

hardware imperfection, and strong variability across environments. This thesis ad- dresses these challenges by developing practical, learning-driven ISAC frameworks

that explicitly exploit the structural properties of wireless channels across time, fre- quency, and space. The thesis is organized around two complementary thrusts.

First, communication-aided sensing is realized through PULSE , a lightweight framework that transforms raw Channel Frequency Response (CFR) measurements

into compact, physics-aware temporal representations for sensing inference and keep- ing it generalized across domains. Second, sensing-aided communication is enabled

through ELF , a scalable channel feedback framework that reformulates multi- antenna channel reporting as a structural inference problem, by feeding back only

a small number of representative subchannel embeddings. Experiments show that

PULSE achieves over 99% sensing accuracy across diverse activities while re- ducing the effective input dimensionality by approximately 85% and maintaining

low inference latency suitable for real-time edge deployment. PULSE generalizes to unseen environments and devices using as little as 5 seconds worth of labeled data, outperforming state-of-the-art Wi-Fi sensing frameworks under domain shifts. On

the other hand ELF reduces feedback overhead by up to 96% relative to dense sub- carrier reporting, while preserving near-identical communication reliability. Com- pared to standard IEEE 802.11ax explicit feedback, ELF achieves up to a 25×

reduction in feedback size across wide bandwidths, and its feedback cost remains effectively independent of antenna count, enabling scalable operation in large

Multiple-Input Multiple-Output (MIMO) systems. Extensive simulations and real- world Wi-Fi testbed evaluations demonstrate that the proposed approaches achieve

strong sensing accuracy, robust cross-domain generalization, and substantial reduc- tions in communication overhead. Collectively, this thesis establishes a unified and

deployable ISAC framework for commodity Wi-Fi systems, highlighting the role of channel structure in enabling efficient and reliable sensing and communication under real-world constraints.