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arXiv:2501.00314 · IEEE Wireless Communications Letters

Quantum-MUSIC: Multiple Signal Classification for Quantum Wireless Sensing

Hanvit Kim, Hyunwoo Park, Sunwoo Kim

Published Mar 10, 2025• 13 citations
arXivHTMLPDF

Abstract

This letter proposes a Quantum-MUSIC, the first multiple signal classification (MUSIC) algorithm for quantum wireless sensing of multi-user. Since the atomic receiver for quantum wireless sensing can only measure a magnitude of the received signal, sensing performance degradation of traditional dipole antenna-based signal processing algorithms is inevitable. To overcome this limitation, the proposed algorithm first retrieves the channel matrix and incorporates the MUSIC algorithm, enabling the multi-user wireless sensing with magnitude-only measurement. Simulation results showed that the proposed algorithm outperforms the classical MUSIC algorithm, validating the theoretical potential of quantum wireless sensing and atomic receiver.

DOI
10.1109/lwc.2025.3549767

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This letter proposes a Quantum-MUSIC, the first multiple signal classification (MUSIC) algorithm for quantum wireless sensing of multi-user. Since the atomic receiver for quantum wireless sensing can only measure a magnitude of the received signal, sensing performance degradation of traditional dipole antenna-based signal processing algorithms is inevitable. To overcome this limitation, the proposed algorithm first retrieves the channel matrix and incorporates the MUSIC algorithm, enabling the multi-user wireless sensing with magnitude-only measurement. Simulation results showed that the proposed algorithm outperforms the classical MUSIC algorithm, validating the theoretical potential of quantum wireless sensing and atomic receiver.
The direction of arrival (DOA) estimation in array signal processing is an important research area. The effectiveness of the direction of arrival greatly determines the performance of multi-input multi-output (MIMO) antenna systems. The multiple signal classification (MUSIC) algorithm, which is the most canonical and widely used subspace-based method, has a moderate estimation performance of DOA. However, in hybrid massive MIMO systems, the received signals at the antennas are not sent to the receiver directly, and spatial covariance matrix, which is essential in MUSIC algorithm, is thus unavailable. Therefore, the spatial covariance matrix reconstruction is required for the application of MUSIC in hybrid massive MIMO systems. In this article, we present a quantum algorithm for MUSIC-based DOA estimation in hybrid massive MIMO systems. Compared with the best-known classical algorithm, our quantum algorithm can achieve an exponential speedup on some parameters and a polynomial speedup on others under some mild conditions. In our scheme, we first present the quantum subroutine for the beam sweeping based spatial covariance matrix reconstruction, where we implement a quantum singular vector transition process to avoid extending the steering vectors matrix into the Hermitian form. Second, a variational quantum density matrix eigensolver (VQDME) is proposed for obtaining signal and noise subspaces, where we design a novel objective function in the form of the trace of density matrices product. Finally, a quantum labeling operation is proposed for the direction of arrival estimation of the signal.
The direction of arrival (DOA) estimation in array signal processing is an important research area. The effectiveness of the direction of arrival greatly determines the performance of multi-input multi-output (MIMO) antennas. The multiple signal classification (MUSIC) algorithm, which is the most canonical and widely used subspace-based method for direction angle estimation, has a moderate estimation performance of DOA. In this article, we present a quantum algorithm for performing MUSIC. Compared with the best-known classical algorithm, quantum MUSIC can show a polynomial speedup. In our scheme, we first efficiently implement a non-Hermitian chain product subroutine for the matrix ${\stackrel{\ifmmode \hat{}\else \^{}\fi{}}{R}}_{ss}\ensuremath{\in}{R}^{N\ifmmode\times\else\texttimes\fi{}N}$ with LLL snapshots, where the method is different from that of Cong and Duan [I. Cong and L. Duan, New J. Phys. 18, 073011 (2016)]. In this subroutine, we perform amplitude transduction [Y. R. Sanders, G. H. Low, A. Scherer, and D. W. Berry, Phys. Rev. Lett. 122, 020502 (2019)] by testing an inequality to neglect the calculation of the approximate arcsine function. Second, a quantum labeling operation based on the principal eigenvalues is proposed for preparing the coherent state of the principal eigenvectors. Finally, we generalize our results to some quantum algorithms with quantum principal component analysis subroutines and some existing quantum algorithms where the covariance matrices occur in the non-Hermitian chain product form.
This paper proposes a multi-band quantum wireless sensing algorithm for the Rydberg atomic receiver. The proposed algorithm first estimates the non-linear wireless channel for the atomic receiver by adopting the biased Gerchberg-Saxton (GS) algorithm to retrieve the eliminated phase information. Thereafter, correlations between the estimated channel and multi-band steering vectors are calculated in the quantized angular grids to detect the angle-of-arrivals (AoAs) of multi-band users in an exhaustive manner. To the best of our knowledge, the proposed algorithm enables multi-band quantum wireless sensing for the first time and is unveiling the theoretical potential of the Rydberg atomic receivers.
Abstract The multiple signal classification (MUSIC) algorithm is a well-established method to evaluate the direction of arrival (DOA) of signals. However, the construction and eigen-decomposition of the sample covariance matrix (SCM) are computationally costly for MUSIC in hybrid multiple input multiple output (MIMO) systems, which limits the application and advancement of the algorithm. In this paper, we present a novel quantum method for MUSIC in hybrid MIMO systems. Our scheme makes the following three contributions. First, the quantum subroutine for constructing the approximate SCM is designed, along with the quantum circuit for the steering vector and a proposal for quantum singular vector transformation. Second, the variational density matrix eigensolver is proposed to determine the signal and noise subspaces utilizing the destructive swap test. As a proof of principle, we conduct two numerical experiments using a quantum simulator. Finally, the quantum labelling procedure is explored to determine the DOA. The proposed quantum method can potentially achieve exponential speedup on certain parameters and polynomial speedup on others under specific moderate circumstances, compared with their classical counterparts.
Quantum wireless sensing using Rydberg atomic receivers enables high-sensitivity signal acquisition direction-of-arrival (DoA) estimation. However, it suffers from a fundamental limitation, where only the magnitude of the received signal is observable. The recently proposed Quantum-MUSIC algorithm addresses this problem by recovering phase information through alternating minimization and subsequently applying the MUSIC algorithm for DoA estimation. However, the existing approach relies on an ℓ2\ell_2ℓ2​-norm phase retrieval step, making it highly sensitive to outlier measurements produced by hardware faults, sensor saturation, or adversarial interference. In this letter, we propose a \emph{Robust Quantum-MUSIC} (RobQMUSIC) framework that replaces the ℓ2\ell_2ℓ2​-norm with an ℓ1\ell_1ℓ1​-norm formulation. The resulting weighted phase-retrieval problem is solved efficiently via an Iteratively Reweighted Least Squares (IRLS) scheme embedded within the alternating minimization loop, requiring no increase in structural complexity relative to the baseline algorithm. Simulation results demonstrate that RobQMUSIC achieves near-identical DoA estimation accuracy to Quantum-MUSIC under ideal conditions, while maintaining robust performance over a wide range of outlier contamination levels at which Quantum-MUSIC fails entirely.
The advancement of Rydberg atoms is driving a paradigm shift from classical receivers to atomic receivers. Capitalizing on the extreme sensitivity of Rydberg atoms to external disturbance, atomic receivers can measure radio waves more precisely than classical receivers to support high-performance wireless communication. Although the atomic receiver is developing rapidly in the field of quantum physics, its integration with wireless communications is at a nascent stage. Particularly, systematic methods to enhance communication performance through this integration are largely uncharted. Motivated by this observation, we propose to incorporate atomic receivers into multiple-input multiple-output (MIMO) communications to implement atomic-MIMO receivers. We establish the framework of atomic-MIMO receivers by exploiting the principle of quantum sensing. Our model reveals that the signal detection of atomic-MIMO systems is intrinsically a nonlinear phase-retrieval problem, as opposed to the linear model in classical MIMO systems. To perform atomic-MIMO signal detection, we propose an Expectation-Maximization-Gerchberg-Saxton (EM-GS) algorithm based on the maximum likelihood (ML) criteria. Its novelty lies in treating the unobserved phase information as a latent variable and thereby decoupling the intricate ML problem into a sequence of tractable linear regression problems with analytical solutions. Experimental results validate the effectiveness of detecting atomic-MIMO signals using the EM-GS algorithm.