Path to Diversity: A Primer on ISAC-izing Commodity Wi-Fi for Practical Deployments

TL;DR

This work reframes Wi-Fi sensing as a core capability of next-gen ISAC by adopting a bottom-up, signal-formation perspective. It identifies four orthogonal diversity domains—Temporal, Frequency, Link, and Spatial—that transform commodity Wi-Fi into a high-fidelity sensing platform, demonstrated through four representative systems: ISAC-Fi (synchronized monostatic sensing with active SIC), UWB-Fi (high-resolution sensing via discrete channel sampling), MUSE-Fi (hybrid physical-digital multi-user sensing), and Beam-Fi (programmable directional sensing). The paper surveys the signal models, hardware imperfections, and advanced algorithms across these domains, and provides concrete case studies to validate absolute ranging, centimeter-level resolution, multi-user separability, and directional sensing on commodity hardware. It also outlines open challenges, including standardization, multi-diversity orchestration, resource-efficient deployment, universal generalization with wireless foundation models, and privacy considerations, arguing that practical ISAC will emerge from holistic cross-domain fusion. Overall, the tutorial offers a systematic blueprint for turning Wi-Fi into a deployable ISAC platform, with clear guidance toward standardization and real-world deployment.

Abstract

Integrated Sensing and Communication (ISAC) has emerged as a key paradigm in next-generation wireless networks. While the ubiquity and low cost of commodity Wi-Fi make it an ideal platform for wide-scale sensing, it is the continuous evolution of Wi-Fi standards-towards higher frequency bands, wider bandwidths, and larger antenna arrays-that fundamentally unlocks the physical resources required for high-performance ISAC. To structure this rapidly expanding field, numerous surveys have appeared. However, prevailing literature predominantly adopts a top-down perspective, emphasizing upper-layer applications or deep learning models while treating the physical layer as an opaque abstraction. Consequently, these works often fail to touch the bottom layer of signal formation and lack technical guidance on overcoming the physical barriers that constrain sensing performance. To bridge this gap, this tutorial takes a bottom-up approach, systematically analyzing the sensing gains brought by Wi-Fi advancements through the lens of physical-layer diversity. We organize the framework around four orthogonal dimensions: i) Temporal Diversity addresses synchronization gaps to enable absolute ranging; ii) Frequency Diversity expands the effective bandwidth to sharpen range resolution; iii) Link Diversity leverages distributed topologies and digital feedback to achieve ubiquitous observability; and iv) Spatial Diversity utilizes multi-antenna arrays to combine passive angular discrimination with active directional control. Collectively, these orthogonal dimensions resolve fundamental ambiguities in time, range, and space, bridging physical capabilities with challenging sensing diversities. By synthesizing these dimensions, this tutorial provides a comprehensive guide for "ISAC-izing" commodity Wi-Fi, paving the way for future standardization and robust deployment.

Figures (19)

• Figure 1: Uniform linear array consisting of $J$ receive antennas
• Figure 2: Transformation from frequency-domain CSI to time-domain PDP via IFFT and norm operation xie2015precise.
• Figure 3: A ToF-AoA spectrum generated from CSI, where peaks indicate the ToF and AoA of distinct signal paths li2024uwb.
• Figure 4: Comparison of signal characteristics between CSI (blue) and BFI (orange). Top Row (a)-(c): Standard Deviation (Std) analysis showing BFI's reduced jitter. Bottom Row (d)-(f): Power Spectrum demonstrating the low-pass filtering effect of BFI generation hu2023muse.
• Figure 5: Bistatic (a) vs Monostatic (b) sensing. The thin arrows represent RF propagation, while thick arrows denote sensed subject motions chen2024isac.