From Snapshot Sensing to Persistent EM World Modeling: A Generative-Space Perspective for ISAC

TL;DR

This paper introduces a generative-space framework for mmWave sensing that enables scalable, persistent electromagnetic world modeling by decoupling spatial observability from hardware constraints, demonstrated through a novel multi-RF chain architecture.

Contribution

It proposes a new generative-space perspective for mmWave sensing, allowing flexible, scalable, and persistent EM world modeling beyond traditional snapshot-based methods.

Findings

Achieves update rates comparable to phased arrays.

Enables interference-free excitation with low calibration overhead.

Supports scalable sensing without dense RF replication.

Abstract

Electromagnetic (EM) world modeling is emerging as a foundational capability for environment-aware and embodiment-enabled wireless systems. However, most existing mmWave sensing solutions are designed for snapshot-based parameter estimation and rely on hardware-intensive architectures, making scalable and persistent world modeling difficult to achieve. This article rethinks mmWave sensing from a system-level perspective and introduces a generative-space framework, in which sensing is realized through controlled traversal of a low-dimensional excitation space spanning frequency, waveform, and physical embodiment. This perspective decouples spatial observability from rigid antenna arrays and transmit-time multiplexing, enabling flexible and scalable sensing-by-design radios. To illustrate the practicality of this framework, we present a representative realization called Multi-RF Chain Frequency-as-Aperture Clip-on Aperture Fabric (MRC-FaA-CAF), where multiple FMCW sources coordinate frequency-selective modules distributed along guided-wave backbones. This architecture enables interference-free excitation, preserves beat-frequency separability, and maintains low calibration overhead. Case studies show that generative-space-driven sensing can achieve update rates comparable to phased arrays while avoiding dense RF replication and the latency penalties of TDM-MIMO systems. Overall, this work positions generative-space-driven sensing as a practical architectural foundation for mmWave systems that move beyond snapshot sensing toward persistent EM world modeling.