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

Abstract

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 $10^{-4}$.

https://dl.acm.org/doi/10.1145/3341302.3342072

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• Improving performance of logical qubits by parameter tuning and topology compensation
• Mixer-Phaser Ansätze for Quantum Optimization with Hard Constraints
• Uplink MIMO Detection using Ising Machines: A Multi-Stage Ising Approach
• A Finite-Range Search Formulation of Maximum Likelihood MIMO Detection for Coherent Ising Machines
• Security and Privacy in O-RAN for 6G: A Comprehensive Review of Threats and Mitigation Approaches
• Quantum-Classical Autoencoder Architectures for End-to-End Radio Communication
• Towards Neuromorphic Processing for Next-Generation MU-MIMO Detection