arXiv subjects

Xiaofei Jia

Publications and source records attributed to Xiaofei Jia.

5 recordsLinked to original sources

arXiv2025

Hybrid Near-Field and Far-Field Localization with Multiple Holographic MIMO Surfaces

Localization using multiple base stations (BSs) has gained much attention for its advantage in localization accuracy. However, the performance of the multi-BS system suffers from its limited number of antennas. To solve the above issue, we propose to use reconfigurable intelligent surfaces (RIS) serving as antennas. Existing localization methods enabled by multiple RISs mainly focus on the far-field (FF) region of each RIS. As the scale of RIS increases, the near-field (NF) region of each RIS expands, where FF methods struggle to achieve high localization accuracy. In this letter, a hybrid NF and FF localization method aided by multiple RISs is proposed. In such scenarios, achieving user localization and RIS optimization becomes challenging due to the high complexity caused by the exhaustive search through all candidate locations to match the signals. Moreover, the interference from multiple RISs degrades the localization accuracy. To address this challenge, we propose a two-phase localization method that first estimates the relative locations of the user to each RIS and fuses the results to obtain the estimation. This approach reduces the complexity by decreasing the number of candidate locations considered in each step. Also, we introduce a constraint in the RIS optimization problem that limits the sidelobe levels directed towards other RISs, effectively minimizing inter-RIS interference. The effectiveness of the proposed method is verified through simulations.

eess.SP↗

arXiv2025

Exploiting Polarization Domain of the IOS for Enhanced Full-Dimensional Transmission

Intelligent omni-surface (IOS), capable of providing service coverage to mobile users (MUs) in a reflective and refractive manner, has recently attracted widespread attention. However, the performance of power-domain IOS-assisted systems is limited by the intimate coupling between the refraction and reflection behavior of IOS elements. In this paper, we introduce the concept of dual-polarized IOS-assisted communication to overcome this challenge. By employing the polarization domain in the design of IOS, full independent refraction and reflection modes can be delivered. We consider a downlink dual-polarized IOS-aided system while also accounting for the leakage between different polarizations. To maximize the sum rate, we formulated a joint base station (BS) digital and IOS analog beamforming problem and proposed an iterative algorithm to solve the nonconvex program. Simulation results validate that dual-polarized IOS significantly enhances the performance than that of the power-domain one.

eess.SP↗

arXiv2025

First-Principles Study of High-Temperature Superconductivity in X2MH6 Compounds under 20 GPa

Research on high-temperature superconductors has primarily focused on hydrogen-rich compounds, however, the need for extreme pressures limits their practical applications. The X2MH6-type structure Mg2IrH6 stands out because it exhibits superconductivity at 160 K under ambient pressure. This study investigates methods to increase the superconducting transition temperature of this structure via atomic substitution and low-pressure treatment and assess the mechanical, thermodynamic, and dynamic stability of structures obtained by substituting Mg and Ir atoms in Mg2IrH6 with elements from the same groups using first-principles calculations. The findings identify 11 stable ternary compounds, 10 of which exhibit superconducting transition temperatures, with three compounds, Mg2CoH6, Mg2RhH6, and Mg2IrH6, exceeding 100 K, classifying them as high-temperature superconductors. Their superconducting figure of merit S values are 2.71, 3.35, and 3.83, respectively, suggesting strong practical application potential. The analysis results indicate that mid-frequency hydrogen phonons significantly enhance superconducting properties via electron-phonon coupling. The band structure study highlights the importance of van Hove singularities near the Fermi level. In addition, electron localization function and Fermi surface topology analyses reveal that the Fermi surface shape and density of states are crucial for increasing superconducting transition temperatures.

cond-mat.supr-con↗

arXiv2024

Determination of crystal structure and physical properties of Ru2Al5 intermetallic from first-principles calculations

Novel ordered intermetallic compounds have stimulated much interest. Ru-Al alloys are a prominent class of high-temperature structural materials, but the experimentally reported crystal structure of the intermetallic Ru2Al5 phase remains elusive and debatable. To resolve this controversy, we extensively explored the crystal structures of Ru2Al5 using first-principles calculations combined with crystal structure prediction technique. Among the calculated X-ray diffraction patterns and lattice parameters of five candidate Ru2Al5 structures, those of the orthorhombic Pmmn structure best aligned with recent experimental results. The structural stabilities of the five Ru2Al5 structures were confirmed through formation energy, elastic constants, and phonon spectrum calculations. We also comprehensively analyzed the mechanical and electronic properties of the five candidates. This work can guide the exploration of novel ordered intermetallic compounds in Ru-Al alloys.

cond-mat.mtrl-sci↗

arXiv2021

Universal Face Restoration With Memorized Modulation

Blind face restoration (BFR) is a challenging problem because of the uncertainty of the degradation patterns. This paper proposes a Restoration with Memorized Modulation (RMM) framework for universal BFR in diverse degraded scenes and heterogeneous domains. We apply random noise as well as unsupervised wavelet memory to adaptively modulate the face-enhancement generator, considering attentional denormalization in both layer and instance levels. Specifically, in the training stage, the low-level spatial feature embedding, the wavelet memory embedding obtained by wavelet transformation of the high-resolution image, as well as the disentangled high-level noise embeddings are integrated, with the guidance of attentional maps generated from layer normalization, instance normalization, and the original feature map. These three embeddings are respectively associated with the spatial content, high-frequency texture details, and a learnable universal prior against other blind image degradation patterns. We store the spatial feature of the low-resolution image and the corresponding wavelet style code as key and value in the memory unit, respectively. In the test stage, the wavelet memory value whose corresponding spatial key is the most matching with that of the inferred image is retrieved to modulate the generator. Moreover, the universal prior learned from the random noise has been memorized by training the modulation network. Experimental results show the superiority of the proposed method compared with the state-of-the-art methods, and a good generalization in the wild.

cs.CV↗