Quantum Annealing for Active User Detection in NOMA Systems

Detecting active users in a non-orthogonal multiple access (NOMA) network poses a significant challenge for 5G/6G applications. Traditional algorithms tackling this task, relying on classical processors, have to make a compromise between performance and complexity. However, a quantum computing based strategy called quantum annealing (QA) can mitigate this tradeoff. In this paper, we first propose a mapping between the AUD searching problem and the identification of the ground state of an Ising Hamiltonian. Then, we compare the execution times of our QA approach for several code domain multiple access (CDMA) scenarios. We evaluate the impact of the cross-correlation properties of the chosen codes in a NOMA network for detecting the active user's set.

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Publication Details

Published
2024-10-27
DOI
https://doi.org/10.1109/ieeeconf60004.2024.10943100
Citations
5
Primary Topic
Retinal Imaging and Analysis
Type
article
Field-Weighted Citation Impact
2.02
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article

Quantum Annealing for Active User Detection in NOMA Systems

Claire Goursaud, Romain Piron
5 citations
Retinal Imaging and Analysis
2.02
article

Quantum Annealing for Active User Detection in NOMA Systems

Claire Goursaud, Romain Piron
article en
5 citations

Abstract

Detecting active users in a non-orthogonal multiple access (NOMA) network poses a significant challenge for 5G/6G applications. Traditional algorithms tackling this task, relying on classical processors, have to make a compromise between performance and complexity. However, a quantum computing based strategy called quantum annealing (QA) can mitigate this tradeoff. In this paper, we first propose a mapping between the AUD searching problem and the identification of the ground state of an Ising Hamiltonian. Then, we compare the execution times of our QA approach for several code domain multiple access (CDMA) scenarios. We evaluate the impact of the cross-correlation properties of the chosen codes in a NOMA network for detecting the active user's set.

Institut national de recherche en sciences et technologies du numérique (FR), Institut National des Sciences Appliquées de Lyon (FR)
Affordable and clean energy
Openalex Percentile: Top 12%
Retinal Imaging and Analysis
2.02
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