# Decision-Oriented Communications: Application to Energy-Efficient Resource Allocation

## TL;DR

This paper introduces decision-oriented communication strategies focusing on how to quantize information efficiently for energy-aware resource allocation, optimizing utility functions in communication systems.

## Contribution

It proposes a novel framework for designing quantizers tailored to maximize utility functions in decision-making tasks, especially for energy-efficient resource allocation.

## Key findings

- Rough quantization suits sum-rate maximization.
- Energy-efficiency metrics are sensitive to quantization errors.
- Solutions provided for both known and observed utility functions.

## Abstract

In this paper, we introduce the problem of decision-oriented communications, that is, the goal of the source is to send the right amount of information in order for the intended destination to execute a task. More specifically, we restrict our attention to how the source should quantize information so that the destination can maximize a utility function which represents the task to be executed only knowing the quantized information. For example, for utility functions under the form $u\left(\boldsymbol{x};\ \boldsymbol{g}\right)$, $\boldsymbol{x}$ might represent a decision in terms of using some radio resources and $\boldsymbol{g}$ the system state which is only observed through its quantized version $Q(\boldsymbol{g})$. Both in the case where the utility function is known and the case where it is only observed through its realizations, we provide solutions to determine such a quantizer. We show how this approach applies to energy-efficient power allocation. In particular, it is seen that quantizing the state very roughly is perfectly suited to sum-rate-type function maximization, whereas energy-efficiency metrics are more sensitive to imperfections.