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First Name:
Burhan
Last Name:
Gulbahar
Datasets & Competitions
The data repository includes simulation parameters and results for the Quantum Approximate Optimization Algorithm (QAOA) channel decoding applied to short block-lengths in Additive White Gaussian Noise (AWGN) channels. This research utilizes a Random Linear Code (RLC) in a Coded Modulation (CM) design at the encoder. Extensive simulations were conducted using IBM Quantum Lab and the ibmq_qasm_simulator back-end provided by IBM Quantum, simulating quantum circuits on classical hardware.
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The data repository contains detailed information about theoretical model used in the simulations and data sets obtained with simulations for the article with the title "Maximum-Likelihood Detection with QAOA for Massive MIMO and Sherrington-Kirkpatrick Model with Local Field at Infinite Size". For a comprehensive understanding, please refer to the main article. We apply Quantum-approximate optimization algorithm (QAOA) on maximum-likelihood (ML) detection of massive multiple-input multiple output (MIMO) systems.
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