# Variational Quantum Integrated Sensing and Communication

arXiv: https://arxiv.org/abs/2511.16597 · HTML: https://mlsanity.com/paper/2511.16597/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 17 references that are in the map.
- First posted on arXiv 20 Nov 2025.

## Builds on (most cited first, 5 of 5)

- [Integrated Sensing and Communications: Towards Dual-functional Wireless Networks for 6G and Beyond](https://mlsanity.com/paper/2108.07165/) (2021)
- [An Introduction to Quantum Machine Learning for Engineers](https://mlsanity.com/paper/2205.09510/) (2022)
- [An Overview of Signal Processing Techniques for Joint Communication and Radar Sensing](https://mlsanity.com/paper/2102.12780/) (2021)
- [Dynamic Estimation Loss Control in Variational Quantum Sensing via Online Conformal Inference](https://mlsanity.com/paper/2505.23389/) (2025)
- [1Q: First-Generation Wireless Systems Integrating Classical and Quantum Communication](https://mlsanity.com/paper/2509.14731/) (2025)

## Built on by (most cited first, 1 of 1)

- [Quantum Integrated Sensing and Computation with Indefinite Causal Order](https://mlsanity.com/paper/2602.10225/) (2026)

## Abstract (arXiv)

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.