A Cost and Power Feasibility Analysis of Quantum Annealing for NextG Cellular Wireless Networks

Abstract

In order to meet mobile cellular users' ever-increasing data demands, today's 4G and 5G wireless networks are designed mainly with the goal of maximizing spectral efficiency. While they have made progress in this regard, controlling the carbon footprint and operational costs of such networks remains a long-standing problem among network designers. This article takes a long view on this problem, envisioning a NextG scenario where the network leverages quantum annealing for cellular baseband processing. We gather and synthesize insights on power consumption, computational throughput and latency, spectral efficiency, operational cost, and feasibility timelines surrounding quantum annealing technology. Armed with these data, we project the quantitative performance targets future quantum annealing hardware must meet in order to provide a computational and power advantage over complementary metal–oxide semiconductor (CMOS) hardware, while matching its whole-network spectral efficiency. Our quantitative analysis predicts, that with 82.32 $\mu$s problem latency and 2.68 M qubits, quantum annealing will achieve a spectral efficiency equal to CMOS while reducing power consumption by 41 kW (45% lower) in a large MIMO base station with 400-MHz bandwidth and 64 antennas, and a 160-kW power reduction (55% lower) using 8.04 M qubits in a centralized radio access network setting with three large MIMO base stations.

Keywords

• Quantum annealing (QA)
• quantum computing
• radio access networks (RANs)
• wireless communication