Embodied Communication: Sensing-Induced Reliability Fields and Capacity Bounds

TL;DR

This paper proposes embodied communication, a novel wireless modality where environmental sensing replaces traditional transmitters, enabling information transfer through environmental state distinguishability without occupying additional spectrum.

Contribution

It formalizes embodied communication via a multi-snapshot RF sensing model, deriving reliability fields, capacity bounds, and practical codebook designs, highlighting a sensing-duration tradeoff.

Findings

Introduces a sensing-induced reliability field for environmental state distinguishability.

Develops lattice-based codebooks and a hexagonal design for embodied communication.

Reveals an intrinsic tradeoff between sensing duration and reliability.

Abstract

This paper introduces embodied communication, a new wireless communication modality in which information is imprinted onto environmental states and recovered by the receiver through sensing. No dedicated communication transmitter is activated, and no additional communication spectrum is occupied; instead, the sensed environment itself becomes the carrier of information. The key insight is that sensing must be reinterpreted for communication. Rather than asking how accurately an unknown physical state can be estimated, embodied communication asks how reliably two states can be distinguished. We formalize this idea through a multi-snapshot radio frequency (RF) sensing model and derive a sensing-induced reliability field that quantifies the distinguishability between physical states. This field turns embodied symbol design into a geometric packing problem shaped by the sensing resolution of the infrastructure. For this embodied channel, we characterize the finite-snapshot $\epsilon$-capacity through achievable designs and converses. We develop lattice-based codebooks, obtain a closed-form hexagonal design under a main-lobe approximation, and establish information-theoretic and geometric upper bounds. We further reveal an intrinsic sensing-duration tradeoff: more sensing snapshots improve reliability, but also lengthen each embodied symbol, leading to a finite optimal sensing time. These results expose a latent communication pathway in sensing-enabled infrastructure and show how the environment can be transformed from a passive backdrop into an active information carrier.