Towards Hybrid Classical-Quantum Computation Structures in Wirelessly-Networked Systems

TL;DR

This paper investigates hybrid classical-quantum computation for wireless network optimization, demonstrating a prototype that achieves 2-10 times faster processing times than previous methods, leveraging reverse quantum annealing.

Contribution

It presents the first exploration of a real hybrid classical-quantum system for wireless optimization using reverse quantum annealing, with promising preliminary results.

Findings

Achieved 2-10X faster processing times compared to prior results.

Demonstrated feasibility of hybrid classical-quantum approach in wireless systems.

Provided a prototype using current quantum hardware techniques.

Abstract

With unprecedented increases in traffic load in today's wireless networks, design challenges shift from the wireless network itself to the computational support behind the wireless network. In this vein, there is new interest in quantum-compute approaches because of their potential to substantially speed up processing, and so improve network throughput. However, quantum hardware that actually exists today is much more susceptible to computational errors than silicon-based hardware, due to the physical phenomena of decoherence and noise. This paper explores the boundary between the two types of computation---classical-quantum hybrid processing for optimization problems in wireless systems---envisioning how wireless can simultaneously leverage the benefit of both approaches. We explore the feasibility of a hybrid system with a real hardware prototype using one of the most advanced experimentally available techniques today, reverse quantum annealing. Preliminary results on a low-latency, large MIMO system envisioned in the 5G New Radio roadmap are encouraging, showing approximately 2--10X better performance in terms of processing time than prior published results.