信号处理
Electromagnetic (EM) communication is nearing its physical and thermodynamic limits, where further performance gains through spectrum optimization alone have become increasingly unsustainable. Finite bandwidth, propagation loss at higher…
Pinching antennas (PAs), as an emerging flexible-antenna technology, enables movable PAs deployed along waveguides to customize channel conditions over a large scale. This paper investigates an application of PAs to enable physical-layer…
Direction-of-Arrival (DOA) estimation in sensor arrays faces limitations under demanding conditions, including low signal-to-noise ratio, single-snapshot scenarios, coherent sources, and unknown source counts. Conventional beamforming…
Direction-of-arrival (DoA) estimation with leaky-wave antennas (LWAs) offers a compact and cost-effective alternative to conventional antenna arrays but remains challenging in the presence of coherent sources. To address this issue, we…
Accurate channel prediction and effective beamforming are essential for low Earth orbit (LEO) satellite communications to enhance system capacity and enable high-speed connectivity. Most existing channel prediction and predictive…
This study proposes a multi-radar system for non-contact physiological sensing across arbitrary body orientations. In integrating signals obtained from different radar viewpoints, we adopt a multivariate variational mode decomposition…
Traditional directed graph signal processing generally depends on fixed representation matrices, whose rigid structures limit the model's ability to adapt to complex graph topologies. To address this issue, this study employed the unified…
The graph linear canonical transform (GLCT)-based filtering methods often optimize transform parameters and filters separately, which results in high computational costs and limited stability. To address this issue, this paper proposes a…
Rydberg atomic quantum receivers (RAQRs) have attracted significant attention in recent years due to their ultra-high sensitivity. Although capable of precisely detecting the amplitude and phase of weak signals, conventional RAQRs face…
In nature, signals often appear in the form of the superposition of multiple non-stationary signals. The overlap of signal components in the time-frequency domain poses a significant challenge for signal analysis. One approach to addressing…
In this paper, we investigate an intelligent reflecting surface (IRS) aided wireless communication system, where active IRSs (AIRSs) are deployed to assist communication between a base station (BS) and users of both the uplink (UL) and…
Movable antenna (MA) has emerged as a promising technology to flexibly reconfigure wireless channels by adjusting antenna placement. In this paper, we study a dual-functional radar-communication (DFRC) system enhanced with movable antennas.…
Deep learning-based radio frequency fingerprinting (RFFP) has become an enabling physical-layer security technology, allowing device identification and authentication through received RF signals. This technology, however, faces significant…
Networked integrated sensing and communication (ISAC) has gained significant attention as a promising technology for enabling next-generation wireless systems. To further enhance networked ISAC, delegating the reception of sensing signals…
Polarimetry, which is the ability to measure the scattering response of the environment across orthogonal polarizations, is fundamental to enhancing wireless communication and radar system performance. In this paper, we utilize the Zak-OTFS…
The limitations of unimodal deep learning models, particularly their tendency to overfit and limited generalizability, have renewed interest in multimodal fusion strategies. Multimodal deep neural networks (MDNN) have the capability of…
The use of drones in a wide range of applications is steadily increasing. However, this has also raised critical security concerns such as unauthorized drone intrusions into restricted zones. Therefore, robust and accurate drone detection…
Artificial intelligence (AI) has emerged as a pivotal enabler for next-generation wireless communication systems. However, conventional AI-based models encounter several limitations, such as heavy reliance on labeled data, limited…
This paper proposes a deep learning-based beamforming design framework that directly maps a target beam pattern to optimal beamforming vectors across multiple antenna array architectures, including digital, analog, and hybrid beamforming.…
Time-interleaved ADCs (TI-ADCs) achieve high sampling rates by interleaving multiple sub-ADCs in parallel. Mismatch errors between the sub-ADCs, however, can significantly degrade the signal quality, which is a main performance bottleneck.…