Evaluation of Quantum Annealer Performance via the Massive MIMO Problem
| Autor: | Zsolt Tabi, Zsófia Kallus, Zoltán Zimborás, Peter Vaderna, Adam Marosits, István Gódor |
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| Rok vydání: | 2021 |
| Předmět: |
graph embedding
Radio access network Optimization problem General Computer Science Computer science MIMO Quantum annealing NP-hard optimization quantum annealing General Engineering Channel decoding quantum computing TK1-9971 Qubit massive MIMO General Materials Science Quadratic unconstrained binary optimization Electrical engineering. Electronics. Nuclear engineering Algorithm Quadrature amplitude modulation Phase-shift keying |
| Zdroj: | IEEE Access, Vol 9, Pp 131658-131671 (2021) |
| ISSN: | 2169-3536 |
| Popis: | Quantum annealing offers an appealing route to handle large-scale optimization problems. Existing Quantum Annealing processing units are readily available via cloud platform access for solving Quadratic Unconstrained Binary Optimization (QUBO) problems. In particular, the novel D-Wave Advantage device has been recently released. Its performance is expected to improve upon the previous state-of-the-art D-Wave 2000Q annealer, due to higher number of qubits and the Pegasus topology. Here, we present a comparative study via an ensemble of Maximum Likelihood (ML) Channel Decoder problems for MIMO scenarios in Centralized Radio Access Network (C-RAN) architectures. The main challenge for exact optimization of ML decoders with ever-increasing demand for higher data rates is the exponential increase of the solution space with problem sizes. Since current 5G solutions mainly use approximate methodologies, Kim et al. leveraged Quantum Annealing for large MIMO problems with Phase Shift Keying and Quadrature Amplitude Modulation scenarios. Here, we extend their work and analyze experiments for more complex modulations and larger MIMO antenna array sizes. By implementing the extended QUBO formulae on the novel annealer architecture, we uncover the limits of state-of-the-art quantum optimization for the massive MIMO ML decoder. We report on the improvements and discuss the uncovered limiting factors learned from the 64-QAM extension. We include the enhanced evaluation of raw annealer sampling via implementation of post-processing methods in the comparative analysis between D-Wave 2000Q and the D-Wave Advantage system. |
| Databáze: | OpenAIRE |
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