Variational Quantum Integrated Sensing and Communication

TL;DR

This paper introduces a quantum protocol that combines sensing and communication using entanglement, optimized through variational learning, enabling flexible trade-offs between data rate and sensing accuracy.

Contribution

It presents a novel quantum integrated sensing and communication protocol that adaptively optimizes encoding and measurement using variational circuits and machine learning.

Findings

Achieves a flexible trade-off between communication rate and estimation accuracy.

Demonstrates effectiveness in qudit systems through numerical simulations.

Utilizes variational circuit learning and classical machine learning for optimization.

Abstract

The integration of sensing and communication functionalities within a common system is one of the main innovation drivers for next-generation networks. In this paper, we introduce a quantum integrated sensing and communication (QISAC) protocol that leverages entanglement in quantum carriers of information to enable both superdense coding and quantum sensing. The proposed approach adaptively optimizes encoding and quantum measurement via variational circuit learning, while employing classical machine learning-based decoders and estimators to process the measurement outcomes. Numerical results for qudit systems demonstrate that the proposed QISAC protocol can achieve a flexible trade-off between classical communication rate and accuracy of parameter estimation.