Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

arXiv:2605.25688

Robust Quantum-MUSIC for DoA Estimation Using Rydberg Atomic Receiver Arrays

Sourav Banerjee, Neel Kanth Kundu, Prajwalita Borah

Published May 25, 2026• 0 citations
arXivHTMLPDF

Abstract

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 $\ell_2$-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 $\ell_2$-norm with an $\ell_1$-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.

DOI
10.48550/arxiv.2605.25688

Related papers

Rydberg Atomic Quantum Receivers for Multi-Target DOA Estimation

Tierui Gong, Chau Yuen, Chong Meng Samson See +2 more

Quantum sensing technologies have experienced rapid progresses since entering the ‘second quantum revolution’. Among various candidates, schemes relying on Rydberg atoms exhibit compelling advantages for detecting radio frequency signals. Based on this, Rydberg atomic quantum receivers (RAQRs) have emerged as a promising solution to classical wireless communication and sensing. To harness the advantages and exploit the potential of RAQRs in wireless sensing, we investigate the realization of the direction of arrival (DOA) estimation by RAQRs. Specifically, we first conceive a Rydberg atomic quantum uniform linear array (RAQ-ULA) aided wireless receiver for multi-target DOA detection and propose the corresponding signal model of this sensing system. Our model reveals that the presence of the radio-frequency local oscillator in the RAQ-ULA creates sensor gain mismatches, which degrade the DOA estimation significantly by employing the classical Estimation of Signal Parameters via Rotational Invariant Techniques (ESPRIT). To solve this sensor gain mismatch problem, we propose the Rydberg atomic quantum ESPRIT (RAQ-ESPRIT) relying on our model. Lastly, we characterize our scheme through numerical simulations, where the results exhibit that it is capable of reducing the estimation error of its classical counterpart on the order of >$400$- fold and >$9000$- fold in the PSL and SQL, respectively.

arXiv:2501.02820•IEEE Transactions on Vehicular Technology•Dec 17, 2025•14 citations

Quantum-MUSIC: Multiple Signal Classification for Quantum Wireless Sensing

Hanvit Kim, Hyunwoo Park, Sunwoo Kim

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.

arXiv:2501.00314•IEEE Wireless Communications Letters•Mar 10, 2025•13 citations

Quantum Algorithm for DOA Estimation in Hybrid Massive MIMO

Fanxu Meng

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.

arXiv:2102.03963•Feb 8, 2021•2 citations

Weight Hybrid Architecture of Rydberg-Atomic Sensors

Hao Wu, Xinyuan Yao, Shanchi Wu +3 more

Rydberg atomic quantum receivers have been seen as novel radio frequency measurements and the high sensitivity to a large range of frequencies makes it attractive for communications reception. However, their performance can be significantly degraded by hardware-induced noise, particularly the noise from laser, which impacts the overall system noise floor and exhibits correlation. To address this challenge, this paper proposes a weight hybrid (WH) architecture for Rydberg-atomic sensors, a novel four-channel combining scheme designed for atomic sensors operating in correlated noise environments. By jointly processing dual signal channels and dual noise reference channels, the WH architecture effectively mitigates noise contributions from lasers and other hardware components. All channels are optimally combined via maximum likelihood estimation within an expectation maximization framework, enabling robust signal extraction under correlated noise. Moreover, the proposed WH architecture is universal and can be readily extended to other types of Rydberg receivers to achieve consistent performance improvements.

arXiv:2605.14474•May 14, 2026•0 citations

Programmable Signal Design for Quantum Phase Estimation via Quantum Signal Processing

Zikang Jia, Suying Liu, Yulong Dong

Quantum phase estimation is a central primitive in quantum algorithms and sensing, where performance is governed by the sensitivity of measurement signals to the target parameter. While existing methods have developed increasingly sophisticated inference and adaptive design strategies, the signal family used for phase learning is often largely pre-specified. Here we propose a programmable signal design framework for quantum phase estimation based on quantum signal processing, which enables the measurement signal to be tailored to the current uncertainty region. We cast phase estimation as a max-min optimization problem over admissible signals and introduce a sensitivity efficiency parameter that quantifies information gain per query depth. The resulting iterative algorithm combines optimized quantum signal transformations with structured classical inference, retaining Heisenberg-limited scaling while improving sensitivity efficiency and practical resource prefactors. Numerical results show reduced estimation variance compared with standard protocols such as robust phase estimation. Our framework also extends to Hamiltonian eigenvalue estimation in higher dimensions and establishes a quantum-classical co-design paradigm through programmable signal shaping.

quant-pharXiv:2604.01205•Apr 2, 2026•0 citations

Quantum algorithm for MUSIC-based DOA estimation in hybrid MIMO systems

Fan‐Xu Meng, Ze‐Tong Li, Xutao Yu +1 more

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 Science and Technology•Dec 20, 2021•15 citations
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.
Quantum sensing technologies have experienced rapid progresses since entering the ‘second quantum revolution’. Among various candidates, schemes relying on Rydberg atoms exhibit compelling advantages for detecting radio frequency signals. Based on this, Rydberg atomic quantum receivers (RAQRs) have emerged as a promising solution to classical wireless communication and sensing. To harness the advantages and exploit the potential of RAQRs in wireless sensing, we investigate the realization of the direction of arrival (DOA) estimation by RAQRs. Specifically, we first conceive a Rydberg atomic quantum uniform linear array (RAQ-ULA) aided wireless receiver for multi-target DOA detection and propose the corresponding signal model of this sensing system. Our model reveals that the presence of the radio-frequency local oscillator in the RAQ-ULA creates sensor gain mismatches, which degrade the DOA estimation significantly by employing the classical Estimation of Signal Parameters via Rotational Invariant Techniques (ESPRIT). To solve this sensor gain mismatch problem, we propose the Rydberg atomic quantum ESPRIT (RAQ-ESPRIT) relying on our model. Lastly, we characterize our scheme through numerical simulations, where the results exhibit that it is capable of reducing the estimation error of its classical counterpart on the order of >400400400- fold and >900090009000- fold in the PSL and SQL, respectively.
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.
Rydberg atomic quantum receivers have been seen as novel radio frequency measurements and the high sensitivity to a large range of frequencies makes it attractive for communications reception. However, their performance can be significantly degraded by hardware-induced noise, particularly the noise from laser, which impacts the overall system noise floor and exhibits correlation. To address this challenge, this paper proposes a weight hybrid (WH) architecture for Rydberg-atomic sensors, a novel four-channel combining scheme designed for atomic sensors operating in correlated noise environments. By jointly processing dual signal channels and dual noise reference channels, the WH architecture effectively mitigates noise contributions from lasers and other hardware components. All channels are optimally combined via maximum likelihood estimation within an expectation maximization framework, enabling robust signal extraction under correlated noise. Moreover, the proposed WH architecture is universal and can be readily extended to other types of Rydberg receivers to achieve consistent performance improvements.
Quantum phase estimation is a central primitive in quantum algorithms and sensing, where performance is governed by the sensitivity of measurement signals to the target parameter. While existing methods have developed increasingly sophisticated inference and adaptive design strategies, the signal family used for phase learning is often largely pre-specified. Here we propose a programmable signal design framework for quantum phase estimation based on quantum signal processing, which enables the measurement signal to be tailored to the current uncertainty region. We cast phase estimation as a max-min optimization problem over admissible signals and introduce a sensitivity efficiency parameter that quantifies information gain per query depth. The resulting iterative algorithm combines optimized quantum signal transformations with structured classical inference, retaining Heisenberg-limited scaling while improving sensitivity efficiency and practical resource prefactors. Numerical results show reduced estimation variance compared with standard protocols such as robust phase estimation. Our framework also extends to Hamiltonian eigenvalue estimation in higher dimensions and establishes a quantum-classical co-design paradigm through programmable signal shaping.
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.