This paper proposes a novel tri-band dual-sense circularly polarized (CP) metasurface (MTS) microstrip antenna based on characteristic mode analysis (CMA). The antenna consists of modified 3×2 MTS units, orthogonally feeding slots, and a T-shaped power divider as the feeding network. CMA is initially conducted on the MTS units to elucidate the operational principles of the proposed antenna. Rectangular patches are replaced by curved rings with lower radiation, and adjustments are made to the corners of the units to achieve CP and mitigate reverse current in resonant modes. Subsequently, CMA is performed on the modified MTS units with the feeding slots to excite resonant modes. The results show that three pairs of orthogonal modes excited by the feeding slots are achieved at 7.75GHz, 8.8GHz, and 9.8GHz, respectively forming CP. Finally, the inclusion of a T-shaped power divider is simulated to validate the antenna's performance. A prototype experiment verifies the principle and design methodology, with measurements agreeing well with simulation results.

Wireless signals are frequently disturbed by complex noise sources, presenting a challenge to traditional direction of arrival (DOA) estimation methods that rely on the assumption of Gaussian noise. To address this issue, our letter proposes an innovative Bayesian DOA estimation approach. This method utilizes Gaussian mixture model (GMM) and Dirichlet process prior for accurately modeling the density function of complex noise environments. Additionally, an efficient combined message passing algorithm is formulated on the factor graph through the use of generalized approximate message passing (GAMP) and mean field (MF) techniques. Simulation results validate the effectiveness of this algorithm.

Ultra-wide-band (UWB) radar technology is a contactless signal detection technology. The UWB technology can be used for the clinical medical monitoring of the human heartbeat and respiration. In this paper, a novel algorithm is proposed to estimate heart rate (HR) and respiratory rate (RR) depending on the received UWB radar signal. The proposed algorithm initially applies Singular Spectrum Analysis (SSA) to remove noise from the received UWB radar signal, and then applies Variational Mode Decomposition (VMD) to effectively separate the respiratory and heartbeat components. To address the issue of heartbeat components being susceptible to harmonic and inter-modulation components interference, a double fuzzy logic estimation is implemented to achieve robust real-time extraction of heart rate. In this paper, extensive experiments are conducted at various distances and angles. The experimental results of the SSA-VMD-Double-Fuzzy-Logic (SVDF) method have been compared with other methods, demonstrating its effectiveness and the advantages of the SVDF proposed in this paper.

Enhancing physical layer security through the deployment of intelligent reflecting surfaces (IRS) is an emerging and significant research direction in 6G wireless networks. Existing methods mainly focus on optimizing the transmit beamforming of the access point (AP) and the phase shift of the IRS to maximize the secrecy rate, while neglecting the optimization of the IRS amplitude. We propose a joint op-timization framework that simultaneously optimizes the IRS amplitude, IRS phase shifts, and AP beamforming to enhance the secrecy rate. Due to the problem’s non-convexity, exist-ing alternating optimization methods face high challenges, particularly for large-scale IRS systems and high-power sce-narios. To tackle these issues, we propose a competition mechanism-based multi-strategy swarm optimization algo-rithm, which aims to better balance global exploration and local exploitation capabilities, thereby achieving more opti-mal IRS configurations. Simulations demonstrate that jointly optimizing IRS amplitude, phase, and AP beamforming sig-nificantly improves secrecy rate over phase-only beamforming methods.