# Multi-sensor Transmission Management for Remote State Estimation under Coordination

## TL;DR

This paper studies multi-sensor remote state estimation in cyber-physical systems, modeling sensor interactions as a game and proposing a correlation policy to improve transmission strategies over shared channels.

## Contribution

It introduces a multi-player game framework and a correlation equilibrium approach to optimize sensor transmission power decisions in shared communication environments.

## Key findings

- Correlation equilibrium outperforms Nash equilibrium in efficiency.
- Analytical comparison of game values with/without power constraints.
- Numerical simulations validate the proposed approach.

## Abstract

This paper considers the remote state estimation in a cyber-physical system (CPS) using multiple sensors. The measurements of each sensor are transmitted to a remote estimator over a shared channel, where simultaneous transmissions from other sensors are regarded as interference signals. In such a competitive environment, each sensor needs to choose its transmission power for sending data packets taking into account of other sensors' behavior. To model this interactive decision-making process among the sensors, we introduce a multi-player non-cooperative game framework. To overcome the inefficiency arising from the Nash equilibrium (NE) solution, we propose a correlation policy, along with the notion of correlation equilibrium (CE). An analytical comparison of the game value between the NE and the CE is provided, with/without the power expenditure constraints for each sensor. Also, numerical simulations demonstrate the comparison results.