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

Abstract

In order to meet mobile cellular users' ever-increasing network usage, today's 4G and 5G 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 Challenge paper takes a long view on this problem, envisioning a NextG scenario where the network leverages quantum annealing computation for cellular baseband processing. We gather and synthesize insights on power consumption, computational throughput and latency, spectral efficiency, and operational cost, and deployment timelines surrounding quantum technology. Armed with these data, we analyze and project the quantitative performance targets future quantum hardware must meet in order to provide a computational and power advantage over silicon hardware, while matching its wholenetwork spectral efficiency. Our quantitative analysis predicts that with quantum hardware operating at a 140 𝜇s problem latency and 4.3M qubits, quantum computation will achieve a spectral efficiency equal to silicon while reducing power consumption by 40.8 kW (45% lower) in a representative 5G base station scenario with 400 MHz bandwidth and 64 antennas, and an 8 kW power reduction (16% lower) using 2.2M qubits in a 200 MHz-bandwidth 5G scenario.

Ising Machines’ Dynamics and Regularization for Near-Optimal MIMO Detection

“…• Finally, we estimate how a physical implementation of a CIM could employ these algorithms to bridge the gap between optimality and efficiency in MIMO detection and may realize a near-optimal MIMO detector, meeting the cellular-system-complexity and timing requirements of practical scenarios, years before quantum-annealing technology would reach the necessary maturity [48], [49].…”