Trading Datarate for Latency in Quantum Communication

TL;DR

This paper investigates the trade-offs between latency and data rate in optical wireless communication, introducing models optimized for each and highlighting the role of quantum measurement strategies in operating points.

Contribution

It presents a novel analysis of latency-data rate trade-offs in optical wireless systems, incorporating quantum measurement strategies and proposing an IoT application scenario.

Findings

Compound codes reduce latency but lower data rates.

Channel estimation improves data rates but increases latency.

Quantum measurement strategies enable reaching specific operating points.

Abstract

Low latency and high data rate performance are essential in wireless communication systems. This paper explores trade-offs between latency and data rates for optical wireless communication. We introduce a latency-optimized model utilizing compound codes as one corner case and a data rate-optimized model employing channel estimation via pilot signals and feedback before data transmission. Trade-offs between the two extremes are displayed. Most importantly, we detail operating points that can only be reached when the receiver side of the link employs optimal quantum measurement strategies. Furthermore, we propose an IoT application in a robot factory as an example scenario. Our findings reveal a trade-off between latency and data rate driven by two basic algorithms: compound codes reduce latency at the cost of data rates, while channel estimation enhances data rates at the cost of latency.