On Remote Estimation with Multiple Communication Channels
For researchers in remote estimation and sensor scheduling, this work extends classical results to more realistic channel models, though the findings are incremental.
The paper studies remote estimation with multiple communication channels, showing that the symmetric threshold policy optimal for classical two-channel problems can be suboptimal when a noisy channel with power constraint is introduced. It proposes an optimal threshold-in-threshold scheduling under a side channel and provides numerical analysis revealing surprising properties.
This paper considers a sequential estimation and sensor scheduling problem in the presence of multiple communication channels. As opposed to the classical remote estimation problem that involves one perfect (noiseless) channel and one extremely noisy channel (which corresponds to not transmitting the observed state), a more realistic additive noise channel with fixed power constraint along with a more costly perfect channel is considered. It is shown, via a counter-example, that the common folklore of applying symmetric threshold policy, which is well known to be optimal (for unimodal state densities) in the classical two-channel remote estimation problem, can be suboptimal for the setting considered. Next, in order to make the problem tractable, a side channel which signals the sign of the underlying state is considered. It is shown that, under some technical assumptions, threshold-in-threshold communication scheduling is optimal for this setting. The impact of the presence of a noisy channel is analyzed numerically based on dynamic programming. This numerical analysis uncovers some rather surprising results inheriting known properties from the noisy and noiseless settings.