In this paper, we propose a novel uplink Hybrid Non-Orthogonal Multiple Access (NOMA) architecture assisted by Rydberg Atomic Quantum Receivers (RAQRs) to improve energy efficiency by addressing the physical constraints of atomic sensing. We formulate a joint optimization problem encompassing phase measurements and multi-user power allocation to minimize the total transmit power. This problem is particularly challenging due to the non-linear amplitude-only observations of atomic vapor cells. To decomposes the resulting non-convexity, we develop a hierarchical three-layer decomposition optimization framework that systematically decouples the global problem. The inner layer employs a customized Expectation Maximization-Gerchberg-Saxton (EM-GS) algorithm to resolve phase ambiguity and estimate equivalent channel gains. The middle layer derives closed-form optimal power allocation solutions via Karush-Kuhn-Tucker (KKT) conditions. The outer layer utilizes linear Minimum Mean Square Error (MMSE) detection for high-reliability signal recovery. Simulation results demonstrate the superiority of the proposed framework over conventional RF-based Hybrid NOMA. Notably, the atomic architecture achieves approximately a 93% reduction in total power consumption compared to Orthogonal Multiple Access (OMA) baselines while maintaining strict backward compatibility, thereby laying a solid foundation for practical deployment in next-generation green communication networks.
In this paper, we propose a novel uplink Hybrid Non-Orthogonal Multiple Access (NOMA) architecture assisted by Rydberg Atomic Quantum Receivers (RAQRs) to improve energy efficiency by addressing the physical constraints of atomic sensing. We formulate a joint optimization problem encompassing phase measurements and multi-user power allocation to minimize the total transmit power. This problem is particularly challenging due to the non-linear amplitude-only observations of atomic vapor cells. To decomposes the resulting non-convexity, we develop a hierarchical three-layer decomposition optimization framework that systematically decouples the global problem. The inner layer employs a customized Expectation Maximization-Gerchberg-Saxton (EM-GS) algorithm to resolve phase ambiguity and estimate equivalent channel gains. The middle layer derives closed-form optimal power allocation solutions via Karush-Kuhn-Tucker (KKT) conditions. The outer layer utilizes linear Minimum Mean Square Error (MMSE) detection for high-reliability signal recovery. Simulation results demonstrate the superiority of the proposed framework over conventional RF-based Hybrid NOMA. Notably, the atomic architecture achieves approximately a 93% reduction in total power consumption compared to Orthogonal Multiple Access (OMA) baselines while maintaining strict backward compatibility, thereby laying a solid foundation for practical deployment in next-generation green communication networks.
This paper investigates an uplink rate-splitting multiple access (RSMA) network empowered by a Rydberg atomic quantum receiver (RAQR) to maximize energy efficiency (EE). To overcome the amplitude-only measurement limitation of the considered direct readout RAQR, we devise a phase alignment mechanism that linearizes the received signal while retaining full channel energy, thereby enabling tractable optimization. The resulting non-convex fractional EE problem is transformed via Dinkelbach's method. For IoT scenarios with symmetric rate requirements, we derive exact closed-form power allocation from the Karush-Kuhn-Tucker (KKT) conditions, which yields a globally optimal bisection search with negligible computational latency. For asymmetric rate requirements, we develop a generalized block coordinate descent-based power allocation (BCD-PA) framework that eliminates reliance on expensive interior-point solvers. We further propose a low-complexity paired allocation (LC-Paired) that exploits user pairing and closed-form bandwidth solutions via the Lambert-W function. Simulation results confirm that the KKT-based scheme attains the highest EE, while the BCD-PA offers a flexible complexity-performance trade-off. The LC-Paired scheme drastically reduces computational cost with only moderate EE degradation.
In this paper, we propose a hybrid simultaneous wireless information and power transfer (SWIPT)–enabled multiple-input multiple-output (MIMO) architecture, where the base station (BS) uses a conventional radio-frequency (RF) transmitter for downlink transmission and a Rydberg atomic quantum receiver (RAQR) for receiving uplink signals from Internet of Things (IoT) devices. To fully exploit this integration, we jointly design the transmission scheme and the power-splitting strategy to maximize the weighted sum rate, which leads to a non-convex problem. To address this challenge, we first derive closed-form lower bounds on the uplink achievable rates for maximum ratio combining (MRC) and zero-forcing (ZF), as well as on the downlink rate and harvested energy for maximum ratio transmission (MRT) and ZF precoding. Building upon these bounds, we propose an iterative algorithm relying on the best monomial approximation and geometric programming (GP) to solve the non-convex problem. Finally, simulations validate the tightness of our derived lower bounds and demonstrate the superiority of the proposed algorithm over benchmark schemes. Importantly, by integrating RAQR with SWIPT-enabled MIMO, the BS can reliably detect weak uplink signals from IoT devices powered only by harvested energy, enabling battery-free IoT networks.
Physical layer security (PLS) provides information-theoretic confidentiality for next-generation wireless systems, yet its practical deployment is fundamentally constrained by the sensitivity and noise characteristics of classical radio receivers. Recent advances in quantum sensing, particularly Rydberg atom-based receivers (RAQRs), present a promising approach to address these limitations. This paper introduces a Rydberg atomic quantum multiple-input multiple-output (RAQ-MIMO) architecture for secure multi-user uplink communications, where an array of Rydberg vapor cells functions as a high-sensitivity, reconfigurable receiving front-end. We develop a comprehensive end-to-end signal and channel model that incorporates quantum sensor response, wireless fading, and eavesdropper behavior under passive interception. To maximize the achievable secrecy rate, we propose a joint optimization framework that adaptively tunes key system degrees of freedom, including the Rabi frequency of the local oscillator, phase configuration, digital combining matrix, and user transmit power. Extensive simulations validate that RAQ-MIMO substantially outperforms classical MIMO in terms of secrecy rate across varying transmission distances, power budgets, and user loads—particularly under low-signal to noise ratio (SNR) and extended-range regimes. Our work establishes a quantum-sensing-assisted security foundation for future high-assurance wireless networks, bridging atomic physics with scalable communication system design with scalable communication system design under narrowband operation.
Rydberg atomic quantum receivers (RAQRs) are capable of receiving multi-band radio-frequency (RF) signals simultaneously, which are expected to break Chu's limit for classical electronic antennas. However, signals from different users will interfere with each other in the optical intermediate frequency (IF) domain of the multi-band quantum receiver, which is termed the IF interference (IFI) problem. To address this problem, in this paper, we propose a multi-input multi-output (MIMO) architecture for Rydberg atomic quantum receiver (RAQ-MIMO) by exploiting the additional spatial diversity of MIMO receivers. Specifically, by applying the dynamic signal model of RAQRs, we clarify the physical relationship between the quantum local oscillator (LO) configurations and the multi-band gains with the concept of quantum transconductance. Then, with the quantum transconductance-based signal model, we formulate the spectral efficiency (SE) maximization problem and further propose the quantum weighted minimum mean square error (qWMMSE) algorithm, which jointly optimizes the quantum LO configurations and the classical precoder/combiner matrices. Furthermore, we test the qWMMSE algorithm within the standard space division multiple access (SDMA) scheme and the frequency division multiple access (FDMA) scheme. Simulation results demonstrate that the qWMMSE optimization framework can significantly improve the SE of RAQ-MIMO systems for both multiple access schemes, and that RAQ-MIMO systems can outperform classical electronic receiver-based multi-user MIMO systems by eliminating the mutual coupling effect between classical antennas.
The advancement of Rydberg atoms in quantum information technology is driving a paradigm shift from classicalradio-frequency(RF) receivers to Rydberg atomic receivers. Capitalizing on the extreme sensitivity of Rydberg atoms to external electromagnetic fields, Rydberg atomic receivers are capable of realizing more precise radio-wave measurements than RF receivers to support high-performance wireless communication and sensing. Although the atomic receiver is developing rapidly in quantum-physics domain, its integration with wireless communications is at a nascent stage. In particular, systematic methods to enhance communication performance through this integration are yet to be discovered. Motivated by this observation, we propose in this paper to incorporate Rydberg atomic receivers intomultiple-input-multiple-output(MIMO) communication, a prominent 5G technology, as the first attempt on implementing atomic MIMO receivers. To begin with, we provide a comprehensive introduction on the principles of Rydberg atomic receivers and build on them to design the atomic MIMO receivers. Our findings reveal that signal detection of atomic MIMO receivers corresponds to a non-linear biasedphase retrieval(PR) problem, as opposed to the linear Gaussian model adopted in classical MIMO systems. Then, to recover signals from this non-linear model, we modify the Gerchberg-Saxton (GS) algorithm, a typical PR solver, into a biased GS algorithm to solve the biased PR problem. Moreover, we propose a novel Expectation-Maximization GS (EM-GS) algorithm to cope with the unique Rician distribution of the biased PR model. Our EM-GS algorithm introduces a high-pass filter constructed by the ratio of Bessel functions into the iteration procedure of GS, thereby improving the detection accuracy without sacrificing the computational efficiency. Finally, the effectiveness of the devised algorithms and the feasibility of atomic MIMO receivers are demonstrated by theoretical analysis and numerical simulation.
Resource management in next-generation wireless communication networks poses substantial computational challenges due to its combinatorial structure and mixed discrete–continuous nature. Many such problems are NP-hard (non-deterministic polynomial-time hard), rendering conventional optimization techniques computationally demanding and often impractical for large-scale deployments. Recent advances in neutral atom quantum computing have demonstrated innovative potential for solving combinatorial optimization problems through graph-based formulations. However, their application to wireless resource management remains largely unexplored. This paper investigates the use of neutral atom quantum processors to address the maximum access problem (MAP) in uplink non-orthogonal multiple access (NOMA)-enabled non-terrestrial networks (NTNs). The MAP is first formulated as a large-scale mixed-integer optimization problem that jointly captures admission control, user clustering, channel assignment, and power allocation under signal-to-interference-plus-noise ratio (SINR) constraints, while accounting for imperfect successive interference cancellation (SIC) at the receiver. To enable hardware-aligned quantum implementation, the problem is transformed into a maximum independent set (MIS) problem over a conflict graph. The resulting graph structure is compatible with the operational principles of neutral atom quantum hardware, allowing direct mapping onto Rydberg atom arrays via blockade-induced interactions. Numerical evaluations assess admission performance, graph complexity, and computational behavior, highlighting the effectiveness of the proposed neutral atom-based framework for solving such graph-theoretic problems. By integrating quantum combinatorial optimization into wireless resource management, this work demonstrates a hardware-aligned mapping for NOMA-enabled NTN resource allocation and provides proof-of-concept validation on a current neutral atom processor, showcasing the potential of neutral atom quantum processors for addressing optimization problems in future 6G and beyond networks.