A Complexity-Efficient Quantum Architecture and Simulation for Eigen Spectrum Estimation of Vandermonde System in a Large Antenna Array

Laskar, Mostafizur Rahaman; Dutta, Asudeb

doi:10.1109/tcsi.2023.3247886

Cited by 2 publications

(1 citation statement)

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“…Leveraging the said advantages, quantum-based optimization methods have been employed to efficiently manage the transmit power allocation in MIMO systems, enabling optimal allocation of the limited resources in scenarios requiring high data speeds under complex channel conditions. For instance, the work of [97] presented a quantum-based decomposition of Vandermode matrix, which holds potential in a range of applications involving high-dimensional computation, such as signal recovery and channel modeling for MIMO systems.…”

Section: A Qml For Physical Layermentioning

confidence: 99%

Quantum Machine Learning for Next-G Wireless Communications: Fundamentals and the Path Ahead

Narottama,

Mohamed,

Aïssa

2023

IEEE Open J. Commun. Soc.

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A comprehensive coverage of the state-of-the-art in quantum machine learning (QML) methodologies, with a unique perspective on their applications for wireless communications, is presented. The paper begins by delving into the fundamental principles of quantum computing, and then goes through different operations and techniques that are involved in QML deployments. Subsequently, it provides an in-depth look at various methods peculiar to quantum computing, such as quantum search algorithms, and discusses their potentials towards maximizing the performance of wireless systems. The integration of quantum-based learning models into the existing machine learning methodologies, such as within the frameworks of unsupervised learning and reinforcement learning, are then examined. Taking the viewpoint of wireless communications, diverse studies in the literature that employ QML-based optimization methods are also highlighted. Finally, to ensure the applicability and feasibility of QML for optimizing wireless systems, potential solutions for deployment challenges are addressed.INDEX TERMS Next-generation wireless communications; Quantum machine learning; Optimization of wireless systems.

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Section: A Qml For Physical Layermentioning

confidence: 99%