Preserving Simultaneity and Chronology for Sensing in Perceptive Wireless Networks

TL;DR

The paper tackles preserving temporal order of event-driven updates from spatially distributed sensors observing the same physical process over wireless links. It introduces temporal windows of integration (TWIs) and a composite latency model spanning physical signal propagation, sensing computation, and wireless transmission, deriving the probability of simultaneity violation. Two tractable approximations for the packet delay variation with two sensors yield closed-form expressions to design the TWI duration $W$ to meet a target simultaneity reliability. The results supply analytical tools to quantify how sensing and communication delays affect chronological event registration and guide the design of perceptive wireless networks with order preservation, with a path toward scalable multisensor deployments.

Abstract

We address the challenge of preserving the simultaneity and chronology of sensing events in multisensor systems with wireless links. The network uses temporal windows of integration (TWIs), borrowed from human multisensory perception, to preserve the temporal structure of the sensing data at the application side. We introduce a composite latency model for propagation, sensing, and communication that leads to the derivation of the probability of simultaneity violation. This is used to select the TWI duration aiming to achieve the desired degrees of chronological preservation, while maintaining the throughput of events. The letter provides important insights and analytical tools about the TWI impact on the event registration.

Figures (5)

• Figure 1: System to monitor a physical process from event-driven status updates produced by wireless sensors
• Figure 2: Timing diagram illustrating a physical process event, the generation and transmission of status updates related to that event by two sensors, and the delivery of the updates to the application based on the framework. In this scenario, sensor 1's update arrived later than sensor 2's due to the longer propagation and computation delays, and the delay resulting from the failed sr and packet transmission attempt. In this example, the design is inadequate for the simultaneous delivery of the updates: the lasts for three frames, while the update arrival times are separated by four frames.
• Figure 3: Approximations for the of the compared with Monte Carlo simulations following eq. \ref{['eq:packet-delay-variation-2-sensors']}. $D_{\max}=100$ m, $T_\text{f}=10$ ms, $M_{\max}=N_{\max}=5$, $\gamma_2=\gamma_\text{TH}=1$, $\mathcal{C}=(C_{\min},C_{\max})$ in ms.
• Figure 4: calculated by the approximations of (a) eq. \ref{['eq:psv-computation-approximation']} and (b) eq. \ref{['eq:psv-propagation-approximation']}, and obtained from Monte Carlo simulations. $D_{\max}=100$ m, $T_\text{f}=10$ ms, $\gamma_2=4$, $\gamma_\text{TH}=1$, $\mathcal{C}=(C_{\min},C_{\max})$ in ms.
• Figure 5: computed by the approximations of (a) eq. \ref{['eq:psv-computation-approximation']} and (b) eq. \ref{['eq:psv-propagation-approximation']} to achieve $\sigma(W^*)=10^{-3}$ and resulting latency obtained in different setups. $T_\text{f}=10$ ms, $\gamma_2=4$, $\gamma_\text{TH}=1$, $M_{\max}=9$, $N_{\max}=7$, $\rho_2=7\cdot10^{-5}$.

Theorems & Definitions (4)

• Definition 1: Simultaneity violation
• Definition 2: Packet delay variation
• Lemma 1
• Lemma 2