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Meihui Liu

Publications and source records attributed to Meihui Liu.

6 recordsLinked to original sources

Online Material-Labeled Environment Reconstruction via Bayesian Multipath Attribution for Low-Altitude ISAC

Environment reconstruction for low-altitude integrated sensing and communications (ISAC) has largely focused on geometry-centric maps, overlooking material-dependent propagation effects. Material-labeled reconstruction is therefore a key step toward propagation-aware mapping, enabling more physically grounded channel prediction and uncrewed aerial vehicle (UAV) networking. However, constructing such maps from wireless multipath observations is challenging in outdoor multi-building scenarios because multipath components (MPCs) from different facades are mixed, path-to-facade attribution is uncertain, and UAV measurements arrive sequentially under time-varying observation geometries. To address these challenges, we propose a unified online probabilistic framework that represents each reflecting facade as a virtual anchor (VA) and couples Bayesian VA localization, multipath attribution, and material inference. The Bayesian front end estimates facade-level geometry and computes soft MPC-to-VA attribution probabilities using a speculardiffuse likelihood model, thereby accounting for both dominant specular paths and diffuse surface-interacted components. These attribution probabilities are used to construct attribution-aware MPC representations, which are aggregated in a VA-centric manner and mapped by a material inference network to facadelevel material evidence. The resulting evidence is recursively fused through an online Bayesian update to produce stable material posteriors and material-labeled environment maps. Ray-tracing simulations in a representative urban street scenario show that the proposed method substantially outperforms a no-attribution baseline, achieves 93.75% final facade-level material accuracy on a held-out UAV trajectory, and maintains accurate VA-based facade localization.

cs.IT

Hierarchical Beam Training and Codebook Design for Movable Antenna-Assisted Near-Field Systems

As sixth-generation (6G) communication systems evolve toward higher frequency bands and larger array apertures, the near-field range expands rapidly, making near-field channel estimation increasingly important and challenging. Beam training has been recognized as an effective approach for channel state information (CSI) acquisition. However, because of the propagation characteristics of spherical waves, beam training needs to perform a joint search in the angle and distance domains, which results in unaffordable beam training overhead. By flexibly reconfiguring antenna positions, movable antenna (MA) technology can fully exploit the spatial variations of wireless channels and achieve more accurate beam focusing, thereby providing additional flexibility for efficient beam training design. Therefore, based on MA-assisted near-field systems, we develop a hierarchical beam training strategy that combines reduced training overhead with high beam gain and design a corresponding hierarchical codebook. This codebook forms focused beams over the joint angle-distance domain, maximizing beam gain within the target region while suppressing energy leakage into non-target regions. Simulation results confirm substantial performance gains of the method over the conventional fixed-position antenna (FPA) system and the far-field beam training method.

cs.IT

Joint Power Allocation and Phase-Shift Design for Beyond-Diagonal Stacked Intelligent Metasurfaces-Aided ISAC Systems

Stacked intelligent metasurfaces (SIM) provide an efficient architecture for integrated sensing and communication (ISAC) with few radio-frequency (RF) chains. However, diagonal SIM provide only element-wise phase control, so balancing multiuser communication and sensing performance may require additional layers. In this letter, we propose a beyond-diagonal SIM (BD-SIM) architecture for ISAC, enabling controllable intra-layer coupling through reconfigurable impedance networks, thereby enhancing wave-domain processing flexibility. We develop a unified alternating optimization framework applicable to fully-connected, group-connected, and diagonal SIM architectures. Within this framework, we derive a closed-form power allocation rule and propose an effective variable separation algorithm for multi-layer phase-shift design. Simulation results show that the proposed BD-SIM achieve a better communication-sensing trade-off and require fewer layers to attain performance comparable to conventional SIM.

cs.IT

Theoretical and experimental study of the correlation between pulsed light repetition frequency and electric field measurement

We propose a novel approach for improving the performance of Rydberg atom sensors by utilizing the repetition frequency of pulsed lasers, which has been validated through experimental testing. Rydberg atoms excited by pulsed lasers are influenced significantly by the repetition frequency of the pulsed laser on the Rydberg state population. As the number of Rydberg atoms increases, the measurement sensitivity of the sensor to external fields also increases, directly enhancing the performance of the sensor. This paper investigates the response of the sensor to the same electric field when the repetition frequency of the pulsed laser is at the MHz level, with a focus on its gain effects on the broadcast communication frequency bands of 66MHz and 88MHz. This research substantiates the distinctive benefits of pulsed light for Rydberg atom excitation, thereby enhancing the efficacy of the detection of feeble signals and introducing a new approach for the development of more sensitive atomic sensors.

physics.atom-ph

Beamforming Optimization for Extremely Large-Scale RIS-Aided Near-Field Secure Communications

This paper studies an extremely large-scale reconfigurable intelligent surface (XL-RIS)-aided near-field physical layer security (PLS) communication system, aiming to maximize the secrecy rate by jointly optimizing precoding vector at the BS and the reflection coefficient matrix at the XL-RIS. Artifi-cial jamming was introduced to further enhance communication security. To solve the non-convex secrecy rate problem, an alternate optimization-based algorithm is adopted to decompose it into two sub-problems. Specifically, when optimizing the transmit beamformer at the BS, the non-convex prob-lem is transformed into a convex one through the weighted minimum mean-square error and the successive convex approximation-based algorithms. For the optimization problem of the XL-RIS phase-shifting matrix, a low-complexity alternating direction method of multipliers-based algorithm is employed to enhance the flexibility of the design. The proposed algorithm is capable of accommodating discrete phase optimization for the XL-RIS, thus better aligning with practical system requirements. Simulation results demonstrate that when the eavesdropper reside in the same direction as the legitimate user and is located closer to the XL-RIS, the proposed scheme in this paper can still ensure the secure communication.

cs.IT

Beamforming Design for ISAC Systems with Suppressed Range-Angle Sidelobes

Integrated sensing and communication (ISAC) represents a pivotal advancement for future wireless networks. This paper introduces a novel ISAC beamforming method for enhancing sensing performance while preserving communication quality by leveraging the ambiguity function (AF). We formulate an optimization problem to minimize the integrated sidelobe level ratio (ISLR) of the AF subject to the constraints of transmission power, communication signalto-interference-plus-noise ratio, and sensing gain. To address the non-convexity of the optimization problem, semidefinite relaxation is adopted. Numerical results show that our method significantly reduces range sidelobes and achieves a lower ISLR in the rangeangle domain compared to other approaches.

cs.IT