Cascade Source Coding with a Side Information "Vending Machine"

TL;DR

This paper investigates a cascade source coding model with a controllable side information vending machine, deriving optimal coding strategies that balance transmission rates, distortions, and acquisition costs in networked scenarios.

Contribution

It provides a single-letter characterization of the rate-distortion-cost trade-offs and demonstrates the necessity of joint source and control signal design for efficiency.

Findings

Layered coding strategies are optimal for the considered models.

Joint source and control design improves communication efficiency.

Performance trade-offs depend on network topology and action costs.

Abstract

The model of a side information "vending machine" (VM) accounts for scenarios in which the measurement of side information sequences can be controlled via the selection of cost-constrained actions. In this paper, the three-node cascade source coding problem is studied under the assumption that a side information VM is available and the intermediate and/or at the end node of the cascade. A single-letter characterization of the achievable trade-off among the transmission rates, the distortions in the reconstructions at the intermediate and at the end node, and the cost for acquiring the side information is derived for a number of relevant special cases. It is shown that a joint design of the description of the source and of the control signals used to guide the selection of the actions at downstream nodes is generally necessary for an efficient use of the available communication links. In particular, for all the considered models, layered coding strategies prove to be optimal, whereby the base layer fulfills two network objectives: determining the actions of downstream nodes and simultaneously providing a coarse description of the source. Design of the optimal coding strategy is shown via examples to depend on both the network topology and the action costs. Examples also illustrate the involved performance trade-offs across the network.