arXiv subjects

Pei Xiao

Publications and source records attributed to Pei Xiao.

At least 19 recordsLinked to original sources

arXiv2026

Continuous Wideband Multicarrier Rydberg Atomic Quantum Receiver

This paper investigates continuous wideband orthogonal frequency-division multiplexing (OFDM) reception using an auxiliary (AUX)-assisted five-level Rydberg atomic quantum receiver (RAQR) with a single microwave local oscillator (LO), without requiring additional atomic reception transitions or LO frequency combs. By exploiting Floquet theory, the proposed framework characterizes the dynamic atomic response at finite signal-LO detunings without relying on a quasi-static Taylor expansion around the LO operating point. Specifically, closed-form radio-frequency (RF)-to-electrical conversion expressions are derived from the Lindblad master equation under weak-probe and weak-signal approximations. Building on these expressions, an equivalent multicarrier communication model is established, revealing the inherent frequency selectivity of the atomic response and the resulting subcarrier-dependent amplitude and phase distortions. RAQR-aware zero-forcing (ZF) equalization is developed to enable reliable OFDM reception. Furthermore, analytical results reveal how LO and AUX driving influence the atomic response through dressed-state splitting and energy-level shifts. An upper bound on the LO-referenced half-power span is derived, and an approximately $18$-dB reduction in center-response power per bandwidth doubling is established in the AUX-free strong-LO regime. Simulation results validate the analytical response model and reveal pronounced subcarrier-dependent amplitude and phase variations across over $10$~MHz, highlighting the potential of RAQRs as wideband receiving front ends for future wireless communications.

eess.SP↗

arXiv2026

Grid-Refinement SBL for AFDM Channel Estimation Under Fractional Delay and Fractional Doppler Channels

This paper investigates channel estimation for affine frequency division multiplexing (AFDM) systems over channels with fractional delay and fractional Doppler (FDFD) shifts. An exact FDFD channel model is first established, and the corresponding input--output relationship is also derived. To address the FDFD-induced delay--Doppler coupling, a first-order linear approximation grid-refinement sparse Bayesian learning (FLA-GR-SBL) method is developed. To further remedy the convergence and stability issues caused by the limited accuracy of the first-order approximation, we propose a two-dimensional grid-approximation SBL (2D-GA-SBL) algorithm, which iteratively refines the delay--Doppler grid and thereby characterizes the channel more accurately. Simulation results demonstrate that the proposed algorithms significantly outperform existing on-grid and off-grid SBL benchmarks in terms of both normalized mean square error (NMSE) and bit error rate (BER).

eess.SP↗

arXiv2026

Guess and Send: World-Model-Guided Semantic Packet Transmission for Robust Video Perception

Reliable video perception over bandwidth-constrained wireless links requires transmitting information that the receiver cannot already recover from its evolving scene representation. This paper introduces Guess and Send, a world-model-guided semantic packet transmission framework that prioritizes information according to its contribution to the receiver's perception. A shared feature-space world model predicts the receiver's scene state through affine motion compensation and learned residual displacement, while sender-side verification identifies reusable predictions. An acknowledgment-synchronized receiver twin estimates task-impact scores through two counterfactual evaluations, guiding packet selection and unequal error protection over LDPC-coded wireless channels. A compact 3-bit feature representation increases spatial coverage under stringent bandwidth constraints, while predictive fallback sustains perception during packet outages. Experiments on KITTI-MOTS (KITTI) and VisDrone2019-MOT (VisDrone) under Rayleigh fading and AWGN demonstrate substantial gains in low-SNR conditions. On KITTI at a 4.13% reference bandwidth budget, Guess and Send achieves 47.5% J&F at 0 dB Rayleigh SNR, outperforming H.264 by 11.3 percentage points. Controlled ablations show that world-model prediction contributes up to 8.7 points under Rayleigh fading. Object-detection experiments further demonstrate the transferability of receiver-relative predictive transmission across visual perception tasks. These results establish world-model-guided, receiver-state-aware transmission as an effective approach to robust video perception under severe communication constraints.

cs.MM↗

arXiv2026

Recursive Code Evolution for Task-Oriented Semantic Communications

Semantic communication jointly optimizes inference accuracy, channel use, and computation, yet the underlying communication program is typically specified before training. This paper presents ComRSI (Communications-Oriented Recursive Self-Improvement), a framework for recursively evolving that program through large-language-model-assisted code edits. An agent modifies the encoder, channel adapters, decoder, loss, and training policy; a protected evaluator screens candidates under prescribed budgets and resource constraints. Accepted code and textual feedback inform subsequent proposals, while candidate weights are trained from scratch. In the original ten-generation CIFAR-100 lineage, eight accepted revisions produce an attention-pooled code achieving 74.3% test accuracy over an Additive White Gaussian Noise (AWGN) channel at 32 complex symbols per image, compared with 67.2% at 256 symbols for the initial design. The program also improves fading-channel accuracy and transfers to Tiny-ImageNet after retraining, where a separate ComRSI search demonstrates further recursive improvements. A repeat study with ten searches per method compares ComRSI against non-recursive agents with and without textual history. Mean final search scores balancing accuracy, transmission rate, and computational cost are 0.7587, 0.7376, and 0.7089, respectively; the mean numbers of accepted revisions per search are 6.0, 5.0, and 2.1. The advantage over the memoryless agent is supported by a two-sided rank test, whereas the difference from the history-equipped agent remains statistically inconclusive at this sample size. Archived proposals show that pooling can yield a large improvement, while retained history supports subsequent refinement. These results support recursive program optimization within the evaluated setting and expose its remaining rate-robustness and compute-placement trade-offs.

cs.IT↗

arXiv2026

Improving Energy Efficiency of Uplink RSMA via Rydberg Atomic Quantum Receiver

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.

cs.IT↗

arXiv2026

AFDM-ISAC Design Amalgamating FMCW Radar and Carrier Aggregation

Carrier-aggregation (CA)-assisted affine frequency division multiplexing (AFDM) is conceived for integrated sensing and communication (ISAC) systems. A frequency-modulated continuous-wave (FMCW)-inspired dechirping receiver is developed to exploit the inherent pulse-compression property of AFDM chirp subcarriers for accurate delay-Doppler estimation. To further enhance sensing performance, a pair of CA schemes is proposed. The Type-I CA scheme improves sensing accuracy by aggregating echo signals across multiple CA bands prior to radar processing, thereby reducing estimation error with low hardware overhead. The Type-II CA scheme enhances range resolution by effectively enlarging the sensing bandwidth, where chirps from different CA bands are designed to form a continuous set of chirp signals. Based on this principle, variable subcarrier sensing and asynchronous sensing schemes are developed. For the communication receiver, the generalized input-output relationship of AFDM is derived under both fractional delay and fractional Doppler (FDFD) channels. To address the challenge of FDFD estimation, a cross-domain sensing-assisted channel estimation (CDS-CE) scheme is proposed to facilitate time-domain delay-Doppler parameter estimation and affine-domain channel coefficient recovery. Simulation results demonstrate that the proposed framework achieves significant improvements in sensing accuracy and resolution, as well as in channel estimation performance compared with state-of-the-art methods.

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arXiv2026

Rydberg Atomic Quantum Receiver Empowered Hybrid Non-orthogonal Multiple Access

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.

cs.IT↗

arXiv2026

Waveform Bandwidth and Frequency Diversity in FDA-MIMO Range-Angle Estimation: A CRLB Perspective

Frequency-diverse array multiple-input multiple-output (FDA-MIMO) radar introduces range-dependent phase diversity through element-dependent carrier-frequency offsets, in addition to the delay information carried by transmitted waveforms. This paper develops a bandwidth-aware Cramer-Rao lower bound (CRLB) framework to characterize how these two mechanisms jointly affect range-angle estimation. Starting from a Nyquist-rate sampled observation model that retains waveform delays and FDA frequency offsets, we derive an equivalent Fisher information matrix (EFIM) after eliminating an unknown quasi-static complex scattering coefficient as a nuisance parameter. We derive closed-form CRLB approximations that reveal the interplay between waveform root-mean-square (RMS) bandwidth and FDA frequency diversity. A three-factor decomposition of the squared normalized cross-information further characterizes range-angle coupling. Results show that when increased independently, both waveform RMS bandwidth and FDA frequency diversity reduce the range CRLB, but FDA frequency diversity increases the angle CRLB at fixed nonzero waveform bandwidth, whereas waveform RMS bandwidth reduces it. Additionally, under a fixed aggregate spectral budget, the range CRLB exhibits an interior maximum, whereas the angle CRLB increases monotonically with the FDA spectral-allocation fraction. Numerical results corroborate the closed-form approximations and the predicted trends.

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arXiv2026

Multi-Functional Chirp Signalling for Next-Generation Multi-Carrier Wireless Networks: Communications, Sensing and ISAC Perspectives

To meet the increasingly demanding quality-of-service requirements of the next-generation multi-carrier mobile networks, it is essential to design multi-functional signalling schemes facilitating efficient, flexible, and reliable communication and sensing in complex wireless environments. As a compelling candidate, we advocate chirp signalling, beneficially amalgamating sequences (e.g., Zadoff-Chu sequences) with waveforms (e.g., chirp spread spectrum and frequency-modulated continuous wave (FMCW) radar), given their resilience against doubly selective channels. Besides chirp sequences, a wide range of chirp waveforms is considered, ranging from FMCW to affine frequency-division multiplexing (AFDM), to create a promising chirp multicarrier waveform. This study also highlights the advantages of such waveforms in supporting reliable high-mobility communications, plus integrated sensing and communications (ISAC). Finally, we outline several emerging research directions for chirp signalling designs.

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arXiv2026

Green Cell-Free Massive MIMO for ISAC: Joint Cloud, Fronthaul and Radio Resource Allocation

In this paper, we develop a cross-layer end-to-end (E2E) resource orchestration framework for green cell-free massive multiple-input multiple-output (CF-mMIMO) integrated sensing and communication (ISAC) systems with distributed multi-target detection. We propose a distributed sensing approach in which receive access points (RX-APs) compute local test statistics, which are aggregated at the cloud using weights based on sensing interference and channel quality. We derive the local maximum a posteriori ratio test (MAPRT) detectors under fully informed and partially informed operation, representing different levels of transmit-signal information at the RX-APs. We further characterize their processing and fronthaul requirements and derive a network power model incorporating radio transmission, AP and cloud processing, and fronthaul infrastructure. We formulate a mixed-integer non-convex problem that jointly optimizes transmit powers, AP modes, user equipment (UE) and sensing-area associations, RX-AP assignments, and active fronthaul and cloud resources subject to communication, sensing, power, processing-capacity, and fronthaul constraints. A two-stage iterative algorithm based on Big-M reformulation, convex- concave programming, penalty-based relaxation, and structured discrete recovery is developed. Numerical results show that the proposed E2E framework reduces total power by up to 50% compared with transmit-power-only optimization and by approximately 11-17% compared with joint radio optimization under full coordination, while maintaining detection probabilities above 0:95.

cs.IT↗

arXiv2026

SemVideoSte: Agentic AI for Cross-Modal Semantic Video Steganography Communication

We propose an agentic artificial intelligence (AI)-driven cross-modal semantic video steganography communication (SemVideoSte) scheme for secure cross-modal information transmission. Agentic AI interprets the service context to determine a semantically matched public prompt and coordinates video generation, message embedding, semantic transmission, and message recovery process. A multi-mask mechanism combines variational autoencoder (VAE) reconstruction robustness, semantic transmission robustness, and latent separability to select reliable embedding positions. Meanwhile, a private digital token controls the random seed and guidance offset to construct positive and negative terminal latent states, enabling coverless message embedding during the final diffusion sampling step. Simulation results on open-source datasets demonstrate that SemVideoSte achieves high embedding capacity, reliable message recovery, and strong semantic consistency under different channel conditions. In addition, eavesdroppers without the correct digital token cannot reliably recover the secret message, and the generated stego videos effectively resist the steganalysis detection. We further establish a prototype testbed to verify the practical feasibility of SemVideoSte.

cs.CR↗

arXiv2026

Widely Linear-Enhanced IQ Imbalance Interference Cancellation for AFDM-FTN Systems

Internet of Things (IoT) networks require reliable and spectrally efficient wireless links to support massive device connectivity and high mobility applications. To meet these requirements, this paper investigates a widely linear (WL)-empowered receiver design for affine frequency division multiplexing (AFDM) with faster-than-Nyquist (FTN) signaling under practical receiver in phase and quadrature imbalance (IQI). The considered AFDM-FTN system couples the direct and image branches with FTN induced intersymbol interference (FTN-ISI) and delay-Doppler spreading in the affine domain. To address this coupled interference structure, a unified conjugate augmented input output model is established for IQI impaired AFDM-FTN systems. Based on this model, a WL minimum mean square error receiver with parallel interference cancellation (WL-MMSE-PIC) is developed, where WL-MMSE preprocessing is followed by the proposed hard decision PIC (HD-PIC) and damped soft decision PIC (SD-PIC). The proposed receiver is further analyzed in terms of the local stability of HD-PIC, a genie aided performance reference under ideal residual interference cancellation, and the impact of the AFDM chirp parameter on the post equalization interference distribution. Simulation results show that the proposed WL-MMSE-HD-PIC and WL-MMSE-SD-PIC receivers achieve significant error rate performance gains over the conventional linear-MMSE and WL-MMSE baselines. The results further show that FTN signaling provides a nominal spectral-efficiency gain, while residual-coupling-based chirp-parameter selection reduces the post-equalization residual coupling and improves detection reliability for high-mobility IoT links.

eess.SP↗

arXiv2026

A Low-Complexity Message-Passing Receiver for FTN-WAFT under Nonlinear Distortion

This letter proposes a faster-than-Nyquist (FTN) weighted affine Fourier transform (WAFT) transmission scheme, termed FTN-WAFT, which combines the peak-to-average power ratio (PAPR) flexibility of WAFT with FTN time compression to improve spectral efficiency and power amplifier (PA) efficiency over high-mobility channels. However, operating the PA at a reduced input back-off (IBO) inevitably introduces nonlinear distortion, which further couples with FTN-induced inter-symbol interference (FTN-ISI) and doubly selective channel dispersion. To address this practical impairment, a multilayer message-passing (MLMP) receiver aided by PA interference cancellation (PA-IC), termed PA-IC-MLMP, is proposed. The proposed receiver reconstructs the dominant PA distortion from soft symbol estimates, cancels the channel-propagated nonlinear interference, and performs MLMP over the WAFT, FTN, channel, and constellation layers. Simulation results show that the proposed receiver improves the bit error rate (BER) and effective throughput under nonlinear PA constraints while maintaining low complexity.

eess.SP↗

arXiv2026

AI-based Interference Mitigation for Power-domain Spectrum Sharing among LEO Satellites

Low-earth orbits (LEO) satellites have recently gained wide attention for their potential to provide high-data-rate services in desert, sea, and rural areas. Currently such systems operate in the Ku band on the down-link. However, inter-operator LEO satellites produce frequent In-Line-Events (ILE) creating co-channel interference between their waveforms. This situation will be exacerbated with the launch of more constellations being launched. To address this challenge, we propose a novel interference mitigation system based on power control. Specifically, satellites from one operator will adjust its transmit power to create a sufficient received-power gap for co-frequency beams, enabling successive interference cancellation (SIC) or AI-assisted algorithms on the user-side for interference mitigation, where AI requires a smaller power gap. We use the waveforms from Starlink and EutelsatOneweb to evaluate the designed system. Results show the designed system can significantly mitigate interference and increase the overall spectrum efficiency.

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arXiv2026

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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arXiv2026

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.

eess.AS↗

arXiv2026

Queue-Aware Graph Reinforcement Learning for UAV-ISAC-Assisted Maritime Data Collection

This paper studies high-altitude platform (HAP)-assisted sparse cooperative integrated sensing and communication (ISAC) for UAV-enabled ocean monitoring. A fleet of rotary-wing UAVs senses drifting buoys, collects their monitoring data, and reports local posterior estimates to a HAP that performs fusion and sparse cooperation control. The model explicitly accounts for a spatially correlated sea-patch field, patch-aware buoy dynamics, RCS- and clutter-aware echo sensing, fused posterior Cramér-Rao bounds (PCRBs), and propulsion-energy-limited UAV mobility. The long-horizon objective is cast as a queue-weighted buffered-collection Markov decision process rather than instantaneous throughput, where each buoy maintains a backlog of buffered observations. The resulting long-horizon design is formulated as a mixed discrete-continuous problem with sensing, communication, mobility, safety, buffered-collection, and onboard-energy constraints. To address the combinatorial association component without replacing learning by a deterministic optimizer, we propose a structured feasible-association graph-MARL framework. A heterogeneous graph encoder produces candidate-edge logits, and a masked sequential b-matching policy samples legal UAV-buoy associations while exactly satisfying UAV-load and buoy-cluster constraints. A MAPPO-style training procedure, an independent queue-state value critic, and a consistency-verification protocol are then specified to support reproducible training. Simulation results on congested maritime scenarios show that the proposed policy improves the cumulative queue-weighted collection utility by about 106\% over the rate-driven deterministic decoder, maintains a large margin across sea-state sweeps and medium-to-heavy traffic loads, and transfers to larger networks without fine-tuning.

eess.SY↗

arXiv2026

CSI Reconstruction in Fluid Antenna Systems Without Spatial Covariance Priors

Fluid antenna systems (FASs) exploit many candidate ports for spatial diversity, but hardware constraints allow channel observations at only a few active ports. Whether full-port CSI can be recovered without pre-acquired channel statistics remains open. Under the Clarke isotropic scattering model, we show that the channel lies in a low-dimensional spatial modal subspace determined by the scattering environment rather than the total port count. Consequently, recovery becomes feasible when the number of observed ports reaches the modal dimension (i.e., $M\geq r$), even when $M\ll N$. We further establish a sharp feasibility threshold: reliable recovery is impossible below this dimension regardless of SNR, whereas accuracy improves with additional observations above it. By decomposing the recovery error into modal truncation, estimation, and learning components, we derive explicit tradeoffs among RF chains, pilot overhead, transmit power, and training data. These results enable scalable prior-free full-port CSI recovery with few active ports.

cs.IT↗