https://doi.org/10.1140/epjp/s13360-025-06093-7
Regular Article
Improved quantum singular value-based channel estimation algorithm for mmWave massive MIMO systems
School of Information and Communication Engineering, Hainan University, 570228, Haikou, China
Received:
22
July
2024
Accepted:
5
February
2025
Published online:
7
March
2025
The technology based on quantum theory has super parallel transmission capability and is considered as one of the effective means to solve the difficulties of future wireless communication systems. In this paper, the improved quantum singular value (IQSV)-based channel estimation scheme for millimeter wave (mmWave) massive multiple input multiple output (MIMO) systems is designed by using the quantum computing technology. Firstly, the precoding matrix and the received matrix are extended to the Hermitian form, and the eigenvalues and eigenvectors of the extended precoding matrix are calculated. Secondly, the extended precoding matrix and the extended received matrix are transformed into the quantum states by the quantum coding technology. Therefore, the quantum states of the left and right singular values of the precoding matrix are further given. Then, the quantum state channel information is obtained by the quantum singular value estimation, the quantum controlled rotation operation and the inverse quantum state comparison operation, in which the appropriate quantum circuit and quantum controlled rotation circuit are designed. Finally, this paper proposes the modified quantum state data extraction algorithm, which can effectively extract the amplitude information, the phase information and the symbol information from the output quantum state data. By analyzing the distribution of the quantum parameter in mmWave massive MIMO systems, the convergence and usability of the proposed IQSV-based algorithm is demonstrated. In addition, we provide the complexity of the proposed IQSV-based algorithm. Experimental simulation shows that the proposed IQSV-based algorithm is superior to traditional channel estimation algorithms in estimation accuracy and significantly less than traditional channel estimation algorithms in running time, whether on the classical computer or the IBM quantum cloud platform. Moreover, this paper also studies the influence of quantum noise on the estimation performance of the proposed IQSV-based algorithm. Experimental analysis shows that IBM quantum cloud platform is more conducive to the development and research of channel estimation algorithms based on quantum theory.
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© The Author(s), under exclusive licence to Società Italiana di Fisica and Springer-Verlag GmbH Germany, part of Springer Nature 2025
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
