Journal
SIGCOMM '19 - PROCEEDINGS OF THE ACM SPECIAL INTEREST GROUP ON DATA COMMUNICATION
Volume -, Issue -, Pages 241-255Publisher
ASSOC COMPUTING MACHINERY
DOI: 10.1145/3341302.3342072
Keywords
Wireless Networks; Massive MIMO; Maximum Likelihood Detection; Sphere Decoder; Quantum Computing; Quantum Annealing
Categories
Funding
- National Science Foundation (NSF) [1824357, 1824470]
- USRA Cycle 3 Research Opportunity Program
- Princeton University School of Engineering and Applied Science Innovation Fund
- Division Of Computer and Network Systems
- Direct For Computer & Info Scie & Enginr [1824470, 1824357] Funding Source: National Science Foundation
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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).
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