Networked sensors improve message decoding from physical signals
Networked Embodied Communication: From Collective Distinguishability to Communication Reliability
Information Theory
Summary
Some devices communicate by physically arranging parts so nearby sensors can read hidden messages. But if sensors see the message only from one spot, they might get confused by similar-looking signals. The authors show that using multiple sensors working together helps clear up these ambiguities, making messages more reliable to decode. They also find the best ways to place these sensors and arrange message parts to reduce errors efficiently.
What this means in practice
- •For industrial automation teams: Design sensor networks that accurately read status signals from robotic or physical devices encoded via spatial configurations.
- •For smart building engineers: Deploy distributed sensors to distinguish device states or commands encoded physically without active communication hardware.
Authors
Yewen Cao, Yulin Shao
Abstract
Embodied agents need to convey information to surrounding infrastructure, but their active communication interfaces may be unavailable, constrained, or intentionally inactive.Their ability to manipulate physical states offers a complementary path: messages can be encoded in deliberately selected configurations and recovered through infrastructure sensing. This principle underlies embodied communication. Yet physical differences do not guarantee distinguishable messages: a single sensing viewpoint may leave ambiguities that repeated sensing cannot resolve. This paper develops networked embodied communication, where distributed access points (APs) jointly observe message-bearing scatterer positions under fixed illumination.Under a correlated Gaussian sensing model, we characterize the additional distinguishability supplied by receive APs, establish exact redundancy conditions, and reveal how distinctions absent from individual observations can emerge through cross-AP statistical relationships. We then establish the exact asymptotic optimal maximum-error behavior of a finite alphabet under repeated independent sensing. The largest group of indistinguishable messages determines the error floor; once all messages are distinguishable, the minimum pairwise Chernoff information determines the error exponent. For a given alphabet, receiver cooperation can therefore eliminate an error floor that repetition at any individual AP cannot overcome. Building on these results, we derive finite-budget reliability conditions and jointly design the receive AP set and message-bearing positions. Numerical results show that the proposed search closely approaches exact benchmarks on reduced instances with substantially fewer candidate evaluations than exhaustive enumeration, while receiver cooperation reduces the sensing intervals needed to guarantee reliable decoding.