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Learning to Learn Quantum Turbo Detection

Bryan Liu, T. Koike-Akino, Ye Wang, K. Parsons·May 17, 2022·DOI: 10.48550/arXiv.2205.08611
Computer ScienceEngineering

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Abstract

This paper investigates a turbo receiver employing a variational quantum circuit (VQC). The VQC is configured with an ansatz of the quantum approximate optimization algorithm (QAOA). We propose a 'learning to learn' (L2L) framework to optimize the turbo VQC decoder such that high fidelity soft-decision output is generated. Besides demonstrating the proposed algorithm's computational complexity, we show that the L2L VQC turbo decoder can achieve an excellent performance close to the optimal maximum-likelihood performance in a multiple-input multiple-output system.

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