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Qu Luo

Publications and source records attributed to Qu Luo.

At least 19 recordsLinked to original sources

Non-Uniform Antenna Array Design with Large Inter-Element Spacing for Massive MIMO

In massive multiple-input multiple-output (MIMO) systems, uniform arrays are typically configured with inter-element spacing no greater than half a wavelength to avoid grating lobes and spatial aliasing. However, many emerging fifth- and sixth-generation (5G/6G) applications rely on distributed arrays whose inter-element spacing far exceeds half a wavelength. In this paper, we propose an electromagnetic mutual-information-theoretic (EMIT)-guided non-uniform array (NUA) design with large inter-element spacing for massive MIMO systems to address the grating lobes and spatial aliasing artifacts, and in the meantime, to reduce the hardware cost and energy consumption. We start by developing a multipath channel model for non-uniform planar arrays, and analyze the resulting channel characteristics in terms of inter-user interference, aperture efficiency, favorable propagation and channel capacity for the proposed typical NUA patterns. The model is further extended to wideband scenarios, where NUAs demonstrate improved robustness against beam squint due to their more compact element distribution. In addition, we introduce an EMIT approach to NUA design, which links the spatial sampling pattern of an antenna array to the capacity of the resulting MIMO channel. This gives rise to two complementary shaping strategies, amplitude tapering and geometric shaping, and their joint optimization. Numerical results demonstrate that the proposed NUAs significantly outperform conventional uniform arrays in aperture efficiency, channel orthogonality, beam squint mitigation, capacity, and error rate performance.

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An Optical Pathway to Movable Rydberg Atomic Quantum Receivers

This paper develops an optically movable Rydberg atomic quantum receiver (RAQR), in which the probe and coupling beams are steered within each vapor cell to dynamically reconfigure the effective radio-frequency (RF) sensing position without mechanical actuation. A closed-form equivalent baseband model is derived by separating the atomic transduction coefficient, optical steering phase, and cell-center array response into distinct factors and the accuracy of the resulting model is validated against numerical solutions of the Lindblad master equation. Based on the derived model, we reveal two complementary channel-shaping mechanisms, including intrinsic beam-pattern shaping through RF-to-optical transduction and per-cell phase control enabled by optical displacement. To further exploit these capabilities, a non-convex sum-rate maximization problem is formulated over the optical positions and local oscillator design and solved via an alternating optimization framework with analytical gradients. Simulation results validate the derived model and demonstrate substantial performance gains enabled by optical movability, highlighting its potential as a programmable receiver architecture for future wireless networks.

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Joint Chirp Parameter Selection and Low-Complexity MMSE Receiver Design for AFDM Systems

Affine frequency division multiplexing (AFDM) has emerged as a promising waveform against doubly selective channels under high-mobility communication scenarios. Optimal chirp parameter selection and reduced-complexity receiver design in AFDM are essential for achieving satisfactory bit error rate (BER) performance with low computational complexity. In this paper, we investigate the joint optimization of chirp-parameter selection and low-complexity minimum mean square error (MMSE)-based receiver design by exploiting the structural characteristics of the AFDM effective channel matrix (ECM). First, a simplified BER performance metric is derived by leveraging the diagonal and circulant structure of the discrete affine Fourier transformation (DAFT), based on which a fast circulant-diagonal aggregation (FCDA) algorithm is developed for efficient $c_1$ selection. Then, a low-complexity banded MMSE (LC-BMMSE) receiver is developed by constructing a cyclic-banded ECM through path-wise structured sparsification, where banded Cholesky factorization is employed to avoid direct matrix inversion. Building upon the proposed BER metric and the LC-BMMSE receiver, a hierarchical-search-based joint chirp parameter and structured sparsification (HS-JCPS) algorithm is further proposed to jointly optimize the chirp parameter and sparsification pattern under a given complexity constraint. Simulation results demonstrate that the proposed FCDA reduces the search time for the optimal $c_1$ by an order of magnitude compared with using a BER-based criterion. Moreover, the proposed HS-JCPS algorithm with the LC-BMMSE receiver can identify a near-optimal $c_1$, while attaining a superior performance-complexity tradeoff.

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AFDM-FTN: A Spectrally Efficient Waveform for High-Mobility Communications

This paper proposes an affine frequency division multiplexing (AFDM)-aided faster-than-Nyquist (FTN) waveform, termed AFDM-FTN, to enhance spectral efficiency (SE) in high-mobility communication scenarios. We first derive the AFDM-FTN input-output relationship and analyze the FTN-induced interference pattern in AFDM-FTN. To address the channel estimation challenges, a low-complexity channel estimator based on the basis expansion model (BEM) is developed. By exploiting the intrinsic characteristics of the AFDM channel matrix and the FTN coefficient matrix, a multi-layer message passing (MLMP) algorithm is proposed that leverages the sparsity of the time-domain (TD) channel and the FTN coefficient matrix, where belief messages are iteratively propagated across the TD channel, FTN, and transform layers. Building upon the BEM-assisted channel estimation and MLMP, a low-complexity joint channel estimation and data detection scheme (BEM-MLMP-JCED) is further developed to iteratively refine channel estimation with the aid of transmitted data. Finally, the channel estimation lower bound, the mean square error (MSE) performance of the BEM-MLMP-JCED, and the computational complexity are analyzed. Simulation results demonstrate that the proposed AFDM-FTN system with BEM-MLMP-JCED achieves comparable BER to conventional AFDM while providing enhanced SE and reduced complexity compared to benchmark receivers.

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Rydberg Atomic Quantum Radio: A Comprehensive Survey From Wireless Communication Perspective

Next-generation space-air-ground-sea integrated networks (SAGSIN) impose unprecedented demands on advanced radio frequency (RF) receivers for full-spectrum agility, ultra-high sensitivity, and anti-jamming resilience, pushing conventional electronic receivers to their physical limits. To address these challenges, the Rydberg atomic quantum (RAQ) radio has emerged as a promising quantum-enabled receiver paradigm that directly maps electromagnetic fields onto atomic quantum states, offering an alternative to alleviate bottlenecks of conventional RF front ends. To provide a clear research roadmap, this survey presents a comprehensive review of RAQ radios by bridging atomic physics and wireless communications. Specifically, we first introduce the underlying quantum mechanisms, representative architectures, and atomic response models of RAQ radio. On this basis, state-of-the-art techniques for enhancing sensitivity, instantaneous bandwidth, and operating frequency are systematically reviewed, with particular emphasis on the inherent trade-offs among these key metrics. To connect quantum response with communication theory, we further analyze equivalent channel modeling frameworks for characterizing systematic performance limits. From the wireless communication perspective, some RAQ-enabled advanced technologies including cognitive, interference-resilient, low-frequency and multiple-input multiple-output (MIMO) communications are reviewed, alongside emerging deployment scenarios such as satellite networks, integrated sensing and communications, and reconfigurable intelligent surface-assisted systems. Finally, we identify open challenges and provide potential future directions of RAQ radio to inspire the further exploration.

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Cell-Level Channel Shaping for Rydberg Atomic Quantum Receivers in Satellite Uplinks With Doppler-Enabled Superheterodyne Reception

In this paper, we propose a self-superheterodyne Rydberg uniform array receiver for satellite uplink communications, in which the Doppler shift naturally induced by satellite motion is exploited to generate the intermediate-frequency signal. We first develop a near-field local oscillator (LO) synthesis model and characterize the spatially varying LO electric field across the Rydberg vapor cells. Based on a vapor-cell-center approximation, a closed-form radio frequency (RF)-to-optical conversion is derived, establishing an explicit bridge between the incident satellite signal and the LO-induced cell-level response. The derived model reveals that the programmable LO serves as an analog-domain channel-shaping mechanism by controlling the cell-level transduction gain, phase response, and phase-matching behavior. Building upon this equivalent channel model, we formulate an LO design problem that maximizes the Shannon capacity of the effective channel, and develop an efficient optimization algorithm for the LO amplitudes and phases. Simulation results demonstrate that the vapor-cell transduction can reshape the effective channel, adjust the beam-pattern alignment, and moderately reduce the inter-user correlation under suitable LO configurations. Furthermore, the proposed LO design significantly improves the achievable capacity over benchmark schemes, offering a promising self-superheterodyne Rydberg architecture for future satellite communication systems.

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Frame-Based AFDM-ISAC Waveform Design With Chirp-Enabled Pulse Compression

This paper proposes an Affine frequency division multiplexing (AFDM)-empowered integrated sensing and communications (ISAC) design, referred to as AFDM-ISAC. We first design a novel AFDM-ISAC frame structure that consists of both ISAC and pure data symbols. Each ISAC symbol consists of a single chirp subcarrier for both sensing and channel estimation, while the remaining subcarriers are allocated for communication. Building upon this structure, we present an analog-domain sensing receiver that down-mixes the received echo with a local chirp to fully exploit \textit{chirp compression} gains avoiding the need for full-duplex hardware. In addition, a sensing fusion algorithm, guided by AFDM modulation parameters, is further proposed in the digital domain. Leveraging the distinct features of the proposed AFDM-ISAC frame, we present a low-complexity channel estimation scheme for high mobility channels based on a generalized complex exponential basis expansion model (GCE-BEM), along with an optimal power allocation strategy between pilot and data symbols. Moreover, to support frame-based AFDM communications, a GCE-BEM-based Kalman filter is also employed for robust intra-frame channel estimation.

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Spatially Coupled Sparse Code Multiple Access (SC-SCMA): A Spectral Graph Approach

This paper presents a spatially coupled sparse code multiple access (SC-SCMA) framework to overcome the performance and scalability limitations of conventional SCMA systems. By analyzing the pairwise error probability associated to multi-user error patterns, we show that spatial coupling projects the superimposed SCMA codewords into a higher-dimensional effective signal space, leading to a strictly improved minimum Euclidean distance (MED) compared with conventional SCMA, while simultaneously enhancing the coding gain through global message propagation and the diversity gain through inter-block resource spreading. Such a distance gain is shown to be governed by the effective access dimensionality (EAD) induced by the coupled factor graph. With the aid of spectral graph theory, we establish a direct relationship between the spectral gap of the factor graph and a lower bound on the EAD, providing a computable structural metric that guarantees MED improvement under various error patterns. Building upon these theoretical insights, we introduce a low-complexity structure-aware codebook design approach, including a spectral-gap-oriented construction of spatially coupled factor matrices and a localized codebook optimization strategy that exploits the dominant error-inducing local user group. Simulation results validate the analysis and demonstrate that the proposed SC-SCMA consistently outperforms conventional SCMA in overloaded massive access channels.

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MCRB and MSE Analysis for Parameter Estimation in AFDM-ISAC Systems

Affine frequency division multiplexing (AFDM) is a promising waveform for integrated sensing and communication (ISAC). In AFDM systems, the complex gains, delays, and Doppler shifts are commonly estimated from the AFDM symbols carrying pilots and data simultaneously. In practice, however, the unknown data symbols and data-pilot coupling interference may render the estimator mismatched to the true signal model. In this paper, we systematically characterize the parameter-estimation performance of AFDM-ISAC systems under practical model misspecification. The main contributions are threefold. First, we extend the Cram\'er-Rao bound (CRB) for a general observation model that treats the data symbols as unknown, which generalizes existing AFDM CRB analyses and serves as the matched benchmark for the subsequent analysis. Second, we identify two practical sources of misspecification, namely a covariance mismatch caused by insufficient pilot-data isolation and a combined covariance-and-mean mismatch caused by sequential single-target estimation, and derive the corresponding misspecified CRB (MCRB). Third, we characterize the pseudotrue parameters under different levels of prior knowledge, analyze the resulting estimation bias, and establish a lower bound (LB) on the mean square error (MSE). Simulation results validate the derived bounds and show that, under model misspecification, the CRB is overly optimistic while the MCRB and LB faithfully characterize the achievable accuracy. The comparison further reveals how these bounds vary with the pilot length and pilot power, providing useful guidance for pilot configuration.

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Towards Standardizing Affine Frequency Division Multiplexing (AFDM) for Future Wireless Networks

Affine frequency division multiplexing~(AFDM) has emerged as a compelling waveform candidate for future wireless networks, owing to its strong resilience to doubly selective channels and its ability to enable the seamless integration of communication and sensing functionalities. Against this context, this article provides a systematic study of AFDM from a standardization perspective. We first introduce the principles of AFDM and discuss the major considerations involved in waveform standardization. We then examine the backwards compatibility of AFDM with 4G/5G multi-numerology frameworks and their anticipated evolution, frequency-modulated continuous-wave (FMCW) radar waveforms, and long-range (LoRa) modulation, demonstrating that AFDM can be incorporated into legacy processing chains with limited modification. Key standardization-critical capabilities are further discussed, including multiple-antenna and multi-user support, and peak-to-average power ratio (PAPR). Finally, we investigate the potential of AFDM in several emerging scenarios, including non-terrestrial networks~(NTN), integrated sensing and communications (ISAC), vehicle-to-everything (V2X), and underwater acoustic (UWA) communications, whereby severe delay-Doppler dispersion places stringent demands on waveform robustness. Through these explorations, it is shown that that AFDM represents a timely and compelling technology for future wireless networks.

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Beyond the RF Paradigm: Rydberg Atomic Receivers for Next-Generation IoT

Next-generation Internet-of-Things (IoT) is evolving toward a ubiquitous, ultra-low-power, and multi-band heterogeneous networking paradigm that seamlessly integrates terrestrial, non-terrestrial, and ambient devices. This vision places unprecedented demands on conventional radio frequency (RF) receivers, whose fundamental bottlenecks in sensitivity, power consumption, coverage, and multi-band operation are rooted in the RF antenna. To tackle these issues, we show that the quantum properties of Rydberg atomic quantum receivers (RAQRs), including ultra-high sensitivity, broad frequency agility, and diverse reception modalities, provide a physically distinct receiver-side path that replaces the conventional antenna-and-low-noise-amplifier chain. Using LoRa, narrowband IoT, and ambient IoT as case studies, this article shows that RAQRs deliver significant gains in weak-uplink, low-power, and battery-free regimes. A stochastic-geometry analysis in cellular and cell-free architectures then maps these device-level gains onto network coverage, where the RAQR retains roughly a 4 dB half-coverage advantage over the RF receiver in sparse deployments at \(\lambda \sim 10^{-5}~{\mathrm m}^{-2}\), with the gain eroded as device density grows. The open challenges are presented to stand between current RAQR prototypes and deployable IoT infrastructure.

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Signal-Dependent Shot Noise Modeling of Rydberg Atomic Quantum Receivers: A Design Perspective

In this paper, we develop a communication-oriented complex baseband equivalent model for superheterodyne Rydberg atomic quantum receivers (RAQRs). The model explicitly captures photodetection-induced signal-dependent shot noise and its coupling with the optical operating point. By leveraging an atomic superheterodyne architecture and a strong local oscillator, we construct a complex baseband representation for both the received signal and the signal-dependent shot noise under both direct incoherent optical detection and balanced coherent optical detection. The derived model reveals that the optical operating point jointly determines the normalized effective receive gain and the equivalent noise background, thereby establishing a traceable gain-noise tradeoff governed by system design. More importantly, the proposed model shows that neglecting signal-dependent shot noise may lead to inaccurate operating-point design. Finally, by extending to the multiple-input-multiple-output (MIMO) case, we derive a lower bound on the achievable rate while considering the signal-dependent shot noise. Our analysis \textcolor{black}{reveals} that the non-zero asymptotic rate of RAQ-MIMO and its superiority over conventional RF-MIMO hinge on the normalized noise floor of the RAQ receive chain falling below that of RF MIMO. Simulation results validate our analysis and yield practical, closed-form design guidelines for RAQR front ends, revealing parameter regimes in which RAQ-MIMO outperforms conventional MIMO systems.

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Low-Complexity Soft-Feedback Detector for AFDM Systems

Affine frequency division multiplexing (AFDM), an emerging multi-carrier modulation scheme, has garnered significant attention due to its resilience to Doppler shifts and capability to achieve full diversity in doubly dispersive channels. However, existing data detection algorithms for AFDM systems face a significant trade-off between computational complexity and accuracy. In this paper, a novel low-complexity data detection scheme, termed the soft-feedback detector (SFD), is proposed. Particularly, building upon a maximum ratio combining (MRC) estimator framework, the SFD leverages the a priori symbol distribution to mitigate error propagation during iterative detection. Specifically, soft-decision feedback is incorporated as extrinsic information derived from the log-likelihood ratios of the transmitted symbols. As a result, the proposed detector significantly enhances detection accuracy while maintaining low computational complexity. Simulation results demonstrate that the SFD consistently outperforms benchmark decision-feedback detectors. In particular, compared with the conventional MRC detector, the proposed scheme achieves approximately a 3 dB signal-to-noise ratio (SNR) gain at the bit error rate (BER) of $10^{-3}$.

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Ultra-Massive MIMO with Orthogonal Chirp Division Multiplexing for Near-Field Sensing and Communication Integration

This paper integrates the emerging ultra-massive multiple-input multiple-output (UM-MIMO) technique with orthogonal chirp division multiplexing (OCDM) waveform to tackle the challenging near-field integrated sensing and communication (ISAC) problem. Specifically, we conceive a comprehensive ISAC architecture, where an UM-MIMO base station adopts OCDM waveform for communications and a co-located sensing receiver adopts the frequency-modulated continuous wave (FMCW) detection principle to simplify the associated hardware. For sensing tasks, several OCDM subcarriers, namely, dedicated sensing subcarriers (DSSs), are each transmitted through a dedicated sensing antenna (DSA) within the transmit antenna array. By judiciously designing the DSS selection scheme and optimizing receiver parameters, the FMCW-based sensing receiver can decouple the echo signals from different DSAs with significantly reduced hardware complexity. This setup enables the estimation of ranges and velocities of near-field targets in an antenna-pairwise manner. Moreover, by leveraging the spatial diversity of UM-MIMO, we introduce the concept of virtual bistatic sensing (VIBS), which incorporates the estimates from multiple antenna pairs to achieve high-accuracy target positioning and three-dimensional velocity measurement. The VIBS paradigm is immune to hostile channel environments characterized by spatial non-stationarity and uncorrelated multipath environment. Furthermore, the channel estimation of UM-MIMO OCDM systems enhanced by the sensing results is investigated. Simulation results demonstrate that the proposed ISAC scheme enhances sensing accuracy, and also benefits communication performance.

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From OFDM to AFDM: Enabling Adaptive Integrated Sensing and Communication in High-Mobility Scenarios

Integrated sensing and communication (ISAC) is a key feature of next-generation wireless networks, enabling a wide range of emerging applications such as vehicle-to-everything (V2X) and unmanned aerial vehicles (UAVs), which operate in high-mobility scenarios. Notably, the wireless channels within these applications typically exhibit severe delay and Doppler spreads. The latter causes serious communication performance degradation in the Orthogonal Frequency-Division Multiplexing (OFDM) waveform that is widely adopted in current wireless networks. To address this challenge, the recently proposed Doppler-resilient affine frequency division multiplexing (AFDM) waveform, which uses flexible chirp signals as subcarriers, shows great potential for achieving adaptive ISAC in high-mobility scenarios. This article provides a comprehensive overview of AFDM-ISAC. We begin by presenting the fundamentals of AFDM-ISAC, highlighting its inherent frequency-modulated continuous-wave (FMCW)-like characteristics. Then, we explore its ISAC performance limits by analyzing its diversity order, ambiguity function (AF), and Cramer-Rao Bound (CRB). Finally, we present several effective sensing algorithms and opportunities for AFDM-ISAC, with the aim of sparking new ideas in this emerging field.

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Uplink SCMA-empowered Uncoordinated Random Access for Future mMTC

In this paper, a novel uncoordinated random access (URA) protocol is presented to address the pressing demand for massive connectivity with low access latency in future massive machine type communication (mMTC) scenarios. The proposed URA scheme integrates the classical slotted ALOHA (S-ALOHA) protocol with sparse code multiple access (SCMA) technique, referred to as SCMA-empowered URA. Specifically, active users randomly choose an SCMA codebook to access the communication network in an arbitrary time slot whenever they want without scheduling. However, due to the lack of central coordination in the proposed URA scheme, SCMA codebook collisions become inevitable, making decoding challenging and leading to increased access failures. To cope with the decoding issue, an interference-canceling (IC) first decoding strategy is proposed at the access point (AP), which can partially tackles collision problems, contributing to a higher system throughput. Taking the proposed IC-first decoding strategy into account, a closed-form theoretical expression of the throughput is derived. Moreover, to alleviate the throughput degradation under the congested user traffic, a user barring mechanism is introduced to manage the traffic load. Firstly, a closed-form expression of idle codebook probability is developed to help indicate the system state, i.e., congested or not. Then, in addition to the estimated real-time load, the AP adaptively adjusts the access probability and redistributes the actual access load. Finally, simulation results demonstrate that the proposed SCMA-empowered URA scheme enjoys higher maximum throughput, compared to the conventional orthogonal multiple access (OMA) based URA scheme. Moreover, the accuracy of the presented theoretical analysis and the effectiveness of the user barring mechanism are verified.

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Enhanced Ground-Satellite Direct Access via Onboard Rydberg Atomic Quantum Receivers

Ground-satellite links for 6G networks face critical challenges, including severe path loss, tight size-weight-power limits, and congested spectrum, all of which significantly hinder the performance of traditional radio frequency (RF) front ends. This article introduces the Rydberg Atomic Quantum Receiver (RAQR) for onboard satellite systems, a millimeter-scale front end that converts radio fields to optical signals through atomic electromagnetically induced transparency. RAQR's high sensitivity and high frequency selectivity address link budget, payload, and interference challenges while fitting within space constraints. A hybrid atomic-electronic design and supporting signal model demonstrate enhanced data rate, coverage, and sensing accuracy relative to conventional RF receivers. The article concludes with integration strategies, distributed-satellite concepts, and open research problems for bringing RAQR-enabled satellite payloads into service.

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RIS-assisted Atomic MIMO Receiver

In this paper, we propose a novel and low-complexity atomic multiple-input multiple-output (MIMO) receiver architecture assisted by a reconfigurable intelligent surface (RIS). By introducing RIS and utilizing pulse amplitude modulation (PAM), the phase of the transmitted signal is effectively aligned with that of the local oscillator (LO), thereby mitigating phase ambiguity and substantially reducing both signal detection complexity and overall receiver complexity.To tackle the resulting non-convex optimization problem, we reformulate it into a tractable form by minimizing the Frobenius norm of an equivalent matrix, which is efficiently solved using an Adam-based gradient descent algorithm.

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