A Cost and Power Feasibility Analysis of Quantum Annealing for NextG Cellular Wireless Networks
A Cost and Power Feasibility Analysis of Quantum Annealing for NextG Cellular Wireless Networks
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DOI：
10.1109/tqe.2023.3326469
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发表时间：
2021-09
影响因子：
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通讯作者：
Srikar Kasi;P. Warburton;John Kaewell;K. Jamieson
中科院分区：
文献类型：
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作者：
Srikar Kasi;P. Warburton;John Kaewell;K. Jamieson
为了满足移动蜂窝用户日益增长的数据需求，如今的4G和5G无线网络的设计主要是以最大化频谱效率为目标。虽然他们在这方面取得了进展，但控制此类网络的碳足迹和运营成本仍然是网络设计师长期面临的问题。本文着眼于这个问题，展望了下一代网络利用量子退火法进行蜂窝基带处理的场景。我们收集和综合有关功耗、计算吞吐量和延迟、频谱效率、运营成本以及围绕量子退火技术的可行性时间表的见解。有了这些数据，我们预测了未来量子退火硬件必须达到的定量性能目标，以便在匹配其全网络频谱效率的同时，提供比互补金属氧化物半导体(CMOS)硬件更高的计算和功率优势。我们的定量分析预测，在具有82.32美元的S问题延迟和2.68M个量子比特的情况下，在具有400 MHz带宽和天线的大型MIMO基站上，量子退火法将获得与CMOS相当的频谱效率，同时降低功耗41kW(降低45%)；在由三个大型MIMO基站组成的集中式无线接入网络中，使用804M量子比特的功率降低160kW(降低55%)。
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.