arXiv subjects

Mengyuan Xu

Publications and source records attributed to Mengyuan Xu.

13 recordsLinked to original sources

arXiv2026

FoV and Efficiency Optimization for Resonant Beam SLIPT with Telescope Integration

Meeting the large bandwidth demands of wireless communication for mobile Internet of Things (IoT) devices while enhancing their endurance is a significant challenge. Simultaneous lightwave information and power transfer (SLIPT) technology offers the potential to realize wireless charging and signal transfer, making it suitable for supporting autonomous vehicles and drones. The resonant beam system (RBS) leverages the self-aligning property of a spatially distributed laser resonator (SSLR), allowing energy transmission from the transmitter to the receiver without mechanical alignment. However, the existing resonant beam SLIPT system exhibits a limited field of view (FoV) and transmission efficiency, facing challenges in practical applications. In this paper, we propose a resonant beam SLIPT system enhanced by incorporating an internal telescope and optimizing the communication, energy transfer, and FoV performance by solving the Pareto front set of the system's achievable performance region. The results indicate that the optimized FoV is increased by $17\%$, reaching $\pm26.8^\circ$, while its average end-to-end efficiency is improved by $145\%$, achieving $5.4\%$.

physics.optics↗

arXiv2026

MIRA: Medical Image Reflection for Agentic Diagnosis

Medical visual agents can use tools to inspect images and retrieve external knowledge, but indiscriminate tool use may introduce noisy or misleading evidence. Reliable diagnosis therefore requires not only acquiring additional observations, but also verifying whether tool actions are necessary and whether the resulting evidence supports the current hypothesis. We introduce MIRA (Medical Image Reflection for Agentic Diagnosis), a medical visual diagnostic framework for autonomous evidence search and reflective verification. MIRA dynamically invokes image-processing operations, including zooming, grounding, pointing, rotation, and measurement, as well as web search, while evaluating the relevance and consistency of the acquired evidence. We develop MIRA through a two-stage training strategy. First, a tool-augmented Monte Carlo Tree Search data engine explores diverse diagnostic hypotheses and jointly verifies visual grounding accuracy and semantic consistency to construct supervised fine-tuning trajectories. Second, reinforcement learning further improves decision-making through online reflective principle evolution: failure cases are distilled into candidate principles, and only principles that improve held-out rollout rewards are retained. Across nine medical visual reasoning benchmarks, MIRA achieves an average score of 64.73, improving its Qwen3-VL-8B backbone by 7.44 points. It also increases useful tool-use judgments from 56.2% to 73.8% and reduces harmful judgments from 8.9% to 1.6%. Qualitative analyses show that MIRA can re-examine evidence, correct premature conclusions, and adapt its tool-use strategy. Project page: https://MIRA-VL.github.io/

cs.CV↗

arXiv2026

Simultaneous Self-Localization and Base Station Localization with Resonant Beam

High-precision positioning in GPS-denied environments is a demanding but challenging technology. Resonant Beam Positioning (RBP) utilizes a resonant beam with properties such as energy focusing, self-establishment, self-alignment, and passive operation, offering a promising solution for this task. However, traditional RBP algorithms require a fixed number of resonant beam base stations, which can be costly to expand coverage. To address this limitation, we propose a distributed resonant beam positioning (DRBP) system that simultaneously estimates the base station and mobile target (MT) positions. Firstly, the MT receives resonant beam samples to locate the base station in the limited field of view (FoV) region. Subsequently, it estimates self-position based on the known locations of the base stations. During moving, the DRBP system facilitates self-positioning on the MT side, enabling dynamic expansion of both the number of base stations and the coverage area. Numerical results demonstrate that DRBP achieves a positioning root mean square error (RMSE) of $0.1$ m and a rotation RMSE of 2$^\circ$, validating the system's high accuracy.

physics.optics↗

arXiv2026

Word Frequency Counting Based on Serverless MapReduce

With the increasing demand for high-performance and high-efficiency computing, cloud computing, especially serverless computing, has gradually become a research hotspot in recent years, attracting numerous research attention. Meanwhile, MapReduce, which is a popular big data processing model in the industry, has been widely applied in various fields. Inspired by the serverless framework of Function as a Service and the high concurrency and robustness of MapReduce programming model, this paper focus on combining them to reduce the time span and increase the efficiency when executing the word frequency counting task. In this case, the paper use a MapReduce programming model based on a serverless computing platform to figure out the most optimized number of Map functions and Reduce functions for a particular task. For the same amount of workload, extensive experiments show both execution time reduces and the overall efficiency of the program improves at different rates as the number of map functions and reduce functions increases. This paper suppose the discovery of the most optimized number of map and reduce functions can help cooperations and programmers figure out the most optimized solutions.

cs.DC↗

arXiv2025

GigaWorld-0: World Models as Data Engine to Empower Embodied AI

World models are emerging as a foundational paradigm for scalable, data-efficient embodied AI. In this work, we present GigaWorld-0, a unified world model framework designed explicitly as a data engine for Vision-Language-Action (VLA) learning. GigaWorld-0 integrates two synergistic components: GigaWorld-0-Video, which leverages large-scale video generation to produce diverse, texture-rich, and temporally coherent embodied sequences under fine-grained control of appearance, camera viewpoint, and action semantics; and GigaWorld-0-3D, which combines 3D generative modeling, 3D Gaussian Splatting reconstruction, physically differentiable system identification, and executable motion planning to ensure geometric consistency and physical realism. Their joint optimization enables the scalable synthesis of embodied interaction data that is visually compelling, spatially coherent, physically plausible, and instruction-aligned. Training at scale is made feasible through our efficient GigaTrain framework, which exploits FP8-precision and sparse attention to drastically reduce memory and compute requirements. We conduct comprehensive evaluations showing that GigaWorld-0 generates high-quality, diverse, and controllable data across multiple dimensions. Critically, VLA model (e.g., GigaBrain-0) trained on GigaWorld-0-generated data achieve strong real-world performance, significantly improving generalization and task success on physical robots without any real-world interaction during training.

cs.CV↗

arXiv2025

ASM-UNet: Adaptive Scan Mamba Integrating Group Commonalities and Individual Variations for Fine-Grained Segmentation

Precise lesion resection depends on accurately identifying fine-grained anatomical structures. While many coarse-grained segmentation (CGS) methods have been successful in large-scale segmentation (e.g., organs), they fall short in clinical scenarios requiring fine-grained segmentation (FGS), which remains challenging due to frequent individual variations in small-scale anatomical structures. Although recent Mamba-based models have advanced medical image segmentation, they often rely on fixed manually-defined scanning orders, which limit their adaptability to individual variations in FGS. To address this, we propose ASM-UNet, a novel Mamba-based architecture for FGS. It introduces adaptive scan scores to dynamically guide the scanning order, generated by combining group-level commonalities and individual-level variations. Experiments on two public datasets (ACDC and Synapse) and a newly proposed challenging biliary tract FGS dataset, namely BTMS, demonstrate that ASM-UNet achieves superior performance in both CGS and FGS tasks. Our code and dataset are available at https://github.com/YqunYang/ASM-UNet.

cs.CV↗

arXiv2025

Single-Frequency Self-Alignment RF Resonant Beam for Information and Power Transfer

Due to power attenuation, improving transmission efficiency in the radio-frequency (RF) band remains a significant challenge, which hinders advancements in various fields of the Internet of Things (IoT), such as wireless power transfer (WPT) and wireless communication. Array design and retro-directive beamforming (RD-BF) techniques offer simple and effective ways to enhance transmission efficiency. However, when the target is an array or in the near field, the RD-BF system (RD-BFS) cannot radiate more energy to the target due to phase irregularities in the target region, resulting in challenges in achieving higher efficiency. To address this issue, we propose the RF-based resonant beam system (RF-RBS), which adaptively optimizes phase and power distribution between transmitting and receiving arrays by leveraging the resonance mechanism to achieve higher transmission efficiency. We analyze the system structure and develop an analytical model to evaluate power flow and resonance establishment. Numerical analysis demonstrates that the proposed RF-RBS achieves self-alignment without beam control and provides higher transmission efficiency compared to RD-BFS, with improvements of up to 16%. This self-alignment capability allows the system to effectively transfer power and information across varying distances and offsets. The numerical results indicate the capability to transmit watt-level power and achieve 21 bps/Hz of downlink spectral efficiency in indoor settings, highlighting the advantages of RF-RBS in information and power transfer for mobile applications.

math.NA↗

arXiv2024

Resonant Beam Enabled Passive 3D Positioning

With the rapid development of the internet of things (IoT), location-based services are becoming increasingly prominent in various aspects of social life, and accurate location information is crucial. However, RF-based indoor positioning solutions are severely limited in positioning accuracy due to signal transmission losses and directional difficulties, and optical indoor positioning methods require high propagation conditions. To achieve higher accuracy in indoor positioning, we utilize the principle of resonance to design a triangulation-based resonant beam positioning system (TRBPS) in the RF band. The proposed system employs phase-conjugation antenna arrays and resonance mechanism to achieve energy concentration and beam self-alignment, without requiring active signals from the target for positioning and complex beam control algorithms. Numerical evaluations indicate that TRBPS can achieve millimeter-level accuracy within a range of 3.6 m without the need for additional embedded systems.

eess.SP↗

arXiv2024

Field of View Expansion for Resonant Beam Information and Power Transfer

Simultaneous wireless information and power transfer (SWIPT) leverages lightwave as the wireless transmission medium, emerging as a promising technology in the future Internet of Things (IoT) scenarios. The use of retro-reflectors in constructing spatially separated laser resonators (SSLR) enables a self-aligning wireless transmission system with the self-reproducing resonant beam, i.e. resonant beam system (RBS). However, it's effective Field of View (FoV) is physically limited by the size of retroreflectors and still requires significant improvement. This restricts the transmitter from providing seamless wireless connectivity and power supply to receivers within a large dynamic movement range. In this paper, we propose an FoV-enlarged resonant beam system operating at a meter distance by incorporating a telescope. The telescope plays a crucial role in minimizing the extra loss inflicted on the gain medium, which typically arises from the deviation of the resonant beam within the cavity. Further, we construct the proposed telescope-based RBS and experimentally demonstrate that the design could expand the FoV to 28$^\circ$ over 1 m transmission distance is about triple that of the ordinary RBS design.

physics.optics↗

arXiv2024

Resonant Beam Enabled DoA Estimation in Passive Positioning System

The rapid advancement of the next generation of communications and internet of things (IoT) technologies has made the provision of location-based services for diverse devices an increasingly pressing necessity. Localizing devices with/without intelligent computing abilities, including both active and passive devices is essential, especially in indoor scenarios. For traditional RF positioning systems, aligning transmission signals and dealing with signal interference in complex environments are inevitable challenges. Therefore, this paper proposed a new passive positioning system, the RF-band resonant beam positioning system (RF-RBPS), which achieves energy concentration and beam alignment by amplifying echoes between the base station (BS) and the passive target (PT), without the need for complex channel estimation and time-consuming beamforming and provides high-precision direction of arrival (DoA) estimation for battery-free targets using the resonant mechanism. The direction information of the PT is estimated using the multiple signal classification (MUSIC) algorithm at the end of BS. The feasibility of the proposed system is validated through theoretical analysis and simulations. Results indicate that the proposed RF-RBPS surpasses RF-band active positioning system (RF-APS) in precision, achieving millimeter-level precision at 2m within an elevation angle of 35$^\circ$, and an error of less than 3cm at 2.5m within an elevation angle of 35$^\circ$.

eess.SP↗

arXiv2022

Binocular Localization Using Resonant Beam

Locating mobile devices precisely in indoor scenarios is a challenging task because of the signal diffraction and reflection in complicated environments. One vital cause deteriorating the localization performance is the inevitable power dissipation along the propagation path of localization signals. In this paper, we propose a high-accuracy localization scheme based on the resonant beam system (RBS) and the binocular vision, i.e., binocular based resonant beam localization (BRBL). The BRBL system utilizes the energy-concentrated and self-aligned transmission of RBS to realize high-efficiency signal propagation and self-positioning for the target. The binocular method is combined with RBS to obtain the three-dimensional (3-D) coordinates of the target for the first time. To exhibit the localization mechanism, we first elaborate on the binocular localization model, including the resonant beam transmission analysis and the geometric derivation of the binocular method with RBS. Then, we establish the power model of RBS, and the signal and noise models of beam spot imaging, respectively, to analyse the performance of the BRBL system. Finally, the numerical results show an outstanding performance of centimeter level accuracy (i.e., $<5\mathrm{cm}$ in $0.4\mathrm{m}$ width and $0.4\mathrm{m}$ length effective range at $1\mathrm{m}$ vertical distance, $<13\mathrm{cm}$ in $0.6\mathrm{m}$ width and $0.6\mathrm{m}$ length effective range at $2\mathrm{m}$ vertical distance), which applies to indoor scenarios.

eess.SP↗

arXiv2022

NLOS Transmission Analysis for Mobile SLIPT Using Resonant Beam

Simultaneous lightwave information and power transfer (SLIPT) is a potential way to meet the demands of sustainable power supply and high-rate data transfer in next-generation networks. Although resonant beam-based SLIPT (RB-SLIPT) can realize high-power energy transfer, high-rate data transfer, human safety, and self-alignment simultaneously, mobile transmission channel (MTC) analysis under non-line-of-sight (NLOS) propagation has not been investigated. In this paper, we propose analytical models and simulation tools for reflector-assisted NLOS transmission of RB-SLIPT, where transmission loss and accurate beam field profile of NLOS MTC can be obtained with a receiver at arbitrary positions and attitude angles. We establish analytical models relying on full diffraction theory for beam propagation between tilted or off-axis planes. Then, we provide three numerical methods (i.e., NUFFT-based, cubic interpolation-based, and linear interpolation-based methods) in simulations. Moreover, to deal with the contradiction between limited computing memory and high sampling requirements for long-range transmission analysis, we propose a multi-hop sliding window approach, which can reduce the sampling number by a factor of thousands. Finally, numerical results demonstrate that RB-SLIPT can achieve $4$W charging power and $12$bit/s/Hz data rate over $2$m distance in NLOS scenarios.

physics.optics↗

arXiv2021

End-to-End Transmission Analysis of Simultaneous Wireless Information and Power Transfer using Resonant Beam

Integrating the wireless power transfer (WPT) technology into the wireless communication system has been important for operational cost saving and power-hungry problem solving of electronic devices. In this paper, we propose a resonant beam simultaneous wireless information and power transfer (RB-SWIPT) system, which utilizes a gain medium and two retro-reflecting surfaces to enhance and retro-reflect energy, and allows devices to recharge their batteries and exchange information from the resonant beam wirelessly. To reveal the SWIPT mechanism and evaluate the SWIPT performance, we establish an analytical end-to-end (E2E) transmission model based on a modular approach and the electromagnetic field propagation. Then, the intra-cavity power intensity distribution, transmission loss, output power, and E2E efficiency can be obtained. The numerical evaluation illustrates that the exemplary RB-SWIPT system can provide about 4.20W electric power and 12.41bps/Hz spectral efficiency, and shorter transmission distance or larger retro-reflecting surface size can lead to higher E2E efficiency. The RB-SWIPT presents a new way for high-power, long-range WPT, and high-rate communication.

eess.SY↗