Leveraging Quantum Annealing for Large MIMO Processing in Centralized Radio Access Networks

被引:68
作者
Kim, Minsung [1 ]
Venturelli, Davide [2 ]
Jamieson, Kyle [1 ]
机构
[1] Princeton Univ, Princeton, NJ 08544 USA
[2] USRA Res Inst Adv Comp Sci, Columbia, MD USA
来源
SIGCOMM '19 - PROCEEDINGS OF THE ACM SPECIAL INTEREST GROUP ON DATA COMMUNICATION | 2019年
基金
美国国家科学基金会;
关键词
Wireless Networks; Massive MIMO; Maximum Likelihood Detection; Sphere Decoder; Quantum Computing; Quantum Annealing; OPTIMIZATION; SEARCH;
D O I
10.1145/3341302.3342072
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
User demand for increasing amounts of wireless capacity continues to outpace supply, and so to meet this demand, significant progress has been made in new MIMO wireless physical layer techniques. Higher-performance systems now remain impractical largely only because their algorithms are extremely computationally demanding. For optimal performance, an amount of computation that increases at an exponential rate both with the number of users and with the data rate of each user is often required. The base station's computational capacity is thus becoming one of the key limiting factors on wireless capacity. QuAMax is the first large MIMO centralized radio access network design to address this issue by leveraging quantum annealing on the problem. We have implemented QuAMax on the 2,031 qubit D-Wave 2000Q quantum annealer, the state-of-the-art in the field. Our experimental results evaluate that implementation on real and synthetic MIMO channel traces, showing that 10 mu s of compute time on the 2000Q can enable 48 user, 48 AP antenna BPSK communication at 20 dB SNR with a bit error rate of 10(-6) and a 1,500 byte frame error rate of 10(-4).
引用
收藏
页码:241 / 255
页数:15
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