arXiv subjects

Min Hao

Publications and source records attributed to Min Hao.

5 recordsLinked to original sources

arXiv2026

Agentic AI for Embodied-enhanced Beam Prediction in Low-Altitude Economy Networks

Millimeter-wave or terahertz communications can meet demands of low-altitude economy networks for high-throughput sensing and real-time decision making. However, high-frequency characteristics of wireless channels result in severe propagation loss and strong beam directivity, which make beam prediction challenging in highly mobile uncrewed aerial vehicles (UAV) scenarios. In this paper, we employ agentic AI to enable the transformation of mmWave base stations toward embodied intelligence. We innovatively design a multi-agent collaborative reasoning architecture for UAV-to-ground mmWave communications and propose a hybrid beam prediction model system based on bimodal data. The multi-agent architecture is designed to overcome the limited context window and weak controllability of large language model (LLM)-based reasoning by decomposing beam prediction into task analysis, solution planning, and completeness assessment. To align with the agentic reasoning process, a hybrid beam prediction model system is developed to process multimodal UAV data, including numeric mobility information and visual observations. The proposed hybrid model system integrates Mamba-based temporal modelling, convolutional visual encoding, and cross-attention-based multimodal fusion, and dynamically switches data-flow strategies under multi-agent guidance. Extensive simulations on a real UAV mmWave communication dataset demonstrate that proposed architecture and system achieve high prediction accuracy and robustness under diverse data conditions, with maximum top-1 accuracy reaching 96.57%.

cs.NI↗

arXiv2026

Efficient Cross-View Localization in 6G Space-Air-Ground Integrated Network

Recently, visual localization has become an important supplement to improve localization reliability, and cross-view approaches can greatly enhance coverage and adaptability. Meanwhile, future 6G will enable a globally covered mobile communication system, with a space-air-ground integrated network (SAGIN) serving as key supporting architecture. Inspired by this, we explore an integration of cross-view localization (CVL) with 6G SAGIN, thereby enhancing its performance in latency, energy consumption, and privacy protection. First, we provide a comprehensive review of CVL and SAGIN, highlighting their capabilities, integration opportunities, and potential applications. Benefiting from the fast and extensive image collection and transmission capabilities of the 6G SAGIN architecture, CVL achieves higher localization accuracy and faster processing speed. Then, we propose a split-inference framework for implementing CVL, which fully leverages the distributed communication and computing resources of the 6G SAGIN architecture. Subsequently, we conduct joint optimization of communication, computation, and confidentiality within the proposed split-inference framework, aiming to provide a paradigm and a direction for making CVL efficient. Experimental results validate the effectiveness of the proposed framework and provide solutions to the optimization problem. Finally, we discuss potential research directions for 6G SAGIN-enabled CVL.

cs.NI↗

arXiv2024

Privacy-preserving Pseudonym Schemes for Personalized 3D Avatars in Mobile Social Metaverses

The emergence of mobile social metaverses, a novel paradigm bridging physical and virtual realms, has led to the widespread adoption of avatars as digital representations for Social Metaverse Users (SMUs) within virtual spaces. Equipped with immersive devices, SMUs leverage Edge Servers (ESs) to deploy their avatars and engage with other SMUs in virtual spaces. To enhance immersion, SMUs incline to opt for 3D avatars for social interactions. However, existing 3D avatars are typically generated through scanning the real faces of SMUs, which can raise concerns regarding information privacy and security, such as profile identity leakages. To tackle this, we introduce a new framework for personalized 3D avatar construction, leveraging a two-layer network model that provides SMUs with the option to customize their personal avatars for privacy preservation. Specifically, our approach introduces avatar pseudonyms to jointly safeguard the profile and digital identity privacy of the generated avatars. Then, we design a novel metric named Privacy of Personalized Avatars (PoPA), to evaluate effectiveness of the avatar pseudonyms. To optimize pseudonym resource, we model the pseudonym distribution process as a Stackelberg game and employ Deep Reinforcement Learning (DRL) to learn equilibrium strategies under incomplete information. Simulation results validate the efficacy and feasibility of our proposed schemes for mobile social metaverses.

cs.NI↗

arXiv2021

Influence of microstructural and crystallographic inhomogeneity on tensile anisotropy in thick-section Al-Li-Cu-Mg plates

Thick-section plates made from a recently developed Al-Cu-Mg-Li alloy have been evaluated to understand the influence of microstructure on the anisotropy of tensile strengths after natural and artificial ageing treatment. Pancake-shaped grains with a coarse substructure and strong crystallographic texture with a beta-fibre orientation at the mid-thickness position are observed. In addition, an inhomogeneous distribution of T1 precipitates through the plate thickness has been revealed with the volume fraction of intragranular precipitates ~ 40% higher at the plate centre than the thickness position. Altogether these microstructural features contribute to the in-plane anisotropy of tensile strengths that is ~ 5% higher at the mid-thickness position than the 1/4 thickness position. The variation of ageing-induced T1 precipitates through the plate thickness further contributes to the through-thickness anisotropy that is ~ 3% higher in T8 temper as compared to T3 temper.

cond-mat.mtrl-sci↗

arXiv2021

Application of high-spatial-resolution secondary ion mass spectrometry for nanoscale chemical mapping of lithium in an Al-Li alloy

High-spatial-resolution secondary ion mass spectrometry offers a method for mapping lithium at nanoscale lateral resolution. Practical implementation of this technique offers significant potential for revealing the distribution of Li in many materials with exceptional lateral resolution and elemental sensitivity. Here, two state-of-the-art methods are demonstrated on an aluminium-lithium alloy to visualise nanoscale Li-rich phases by mapping the 7Li+ secondary ion. NanoSIMS 50L analysis with a radio frequency O- plasma ion source enabled visualisation of needle-shaped T1 (Al2CuLi) phases as small as 75 nm in width. A compact time-of-flight secondary ion mass spectrometry detector added to a focused ion beam scanning electron microscope facilitated mapping of the T1 phases down to 45 nm in width using a Ga+ ion beam. Correlation with high resolution electron microscopy confirms the identification of T1 precipitates, their sizes and distribution observed during SIMS mapping.

cond-mat.mtrl-sci↗