Millimeter-wave (mmWave) communication inside high-speed railway (HSR) intrawagon is essential for future high-data-rate and low-latency onboard services. Accurate and efficient channel modeling is essential for system design and evaluation. Ray-tracing (RT) techniques are capable of accurately capturing significant multipath components (MPCs). However, RT becomes complex and time-consuming in harsh environments, where dense multipath components (DMCs) exist and the reverberation effects occur. To address this issue, this paper analyzes the mmWave propagation channel inside HSR intrawagon and proposes a Quasi-Deterministic (QD) modeling approach. Channel measurements and RT simulations were conducted at the 26 GHz band to track major specular reflection paths and reveal the underlying mmWave propagation mechanisms. By combining the accuracy of RT with the computational efficiency of stochastic models, the proposed method accurately characterizes dominant MPCs and efficiently models DMCs. Experimental results demonstrate that the measured data aligns well with the proposed QD model. The proposed approach improves computational efficiency while maintaining modeling accuracy.

Infrared small target detection has extensive applications in various systems, including search and tracking, guidance and missile defense, as well as electro-optical pods. Although the existing saliency-based detection methods have demonstrated promising performance, two key issues include the inability to effectively suppress continuous strong edges and the lack of robustness in manually adjusting thresholds, persist as ongoing challenges. To address the aforementioned issues, we propose an infrared small target detection method based on a structure tensor indicator, which incorporates a structure tensor-based edge indicator with an adaptive balancing weight. Initially, structure tensor features are utilized to design two indicators that separately characterize clutter edges and targets, while incorporating a balancing weight to enhance the target and mitigate edge interference. To overcome the lack of adaptability in manually configured parameters, we propose an adaptive weighting factor based on a structural similarity index measure, which iteratively adjusts the weight by evaluating the differences between the target image and the detection image. Extensive experiments conducted on real-world datasets underscore the superiority of the proposed method in terms of target enhancement, background suppression (BS), and detection efficiency.

In this paper, we investigate the near-field wideband terahertz (THz) massive multi-input multi-output (MIMO) integrated sensing and communication (ISAC) systems. Specifically, we propose an energy-efficient serial true-time-delay (TTD)-based reconfigurable antenna architecture for the dual-function base station (DFBS). This architecture enables DFBS to switch between modular and compact MIMO configurations by dynamically controlling the activation of antenna subarrays, corresponding to the sensing and communication stages, respectively. During the sensing stage, a modular MIMO architecture is deployed by deactivating several subarrays and all TTDs. This configuration utilizes fewer antennas to achieve a larger array aperture with enhanced energy efficiency. Moreover, we take advantage of beam squint effects at both the main and grating lobes to extend sensing range and enable rapid user sensing. During the communication stage, a compact MIMO configuration is employed by activating all antennas, and the TTD network is activated to mitigate the near-field beam squint effect. Based on the channel state information obtained during the sensing stage, we formulate a joint optimization problem of the hybrid analog/digital beamforming and TTD network time delays to maximize the system sum rate. To solve it, we first design analog beamforming and time delays through a serial-delay approach, followed by an alternating iterative optimization for digital beamforming. In addition, our proposed scheme accounts for the finite resolution and limited delay range of TTDs. Simulation results demonstrate the effectiveness of our designed antenna architecture and optimization scheme.

Considering limited pilot overhead and large delay and Doppler shift in LoRa (Long Range)-based IoT (Internet of Things) systems, this paper presents an efficient joint parameter estimation and soft nonconherent detection scheme. During the parameter estimation, a joint delay and Doppler shift estimation method is proposed, which is called the JDDSE method. Different from the existing estimation methods, the proposed method utilizes the time-domain characteristic of the LoRa signal and only needs to estimate a joint offset of the delay and Doppler shift instead of their respective offsets. Then, a soft noncoherent detection is developed from the existing work in order to match the JDDSE method. Simulation results indicate the validity of the proposed method under the uplink IoT transmission.

Abstract Beam selection aims to select beams with large power and little inter‐user interference (IUI). In wireless communication scenarios, the levels of IUI are usually different, but, most existing beam selection methods apply the same beam selection criteria for all users, which is detrimental to maintain an attractive trade‐off between computational complexity and system performance. Considering the discrepancy of IUI comprehensively, this paper proposes a beam selection method based on interfering user grouping (IUG) for wideband millimetre‐wave massive multiple‐input multiple‐output (MIMO) systems. Firstly, a candidate beam set (CBS) is constructed in light of the sparsity and power distribution of the beamspace channel. Based on the CBS, all users are classified into non‐interfering users (NIUs), low‐interference users (LIUs) and high‐interference users (HIUs). For NIUs, the beams with large power are selected from CBS under the magnitude maximization (MM) criterion; for LIUs, a novel MM criterion with a tabu list is designed, which can effectively tackle the drawback of assigning shared beams in traditional MM; for HIUs, the incremental algorithm based on the sum‐rate maximization criterion is developed to find the optimal beams from CBS. Simulation results validate that the proposed IUG‐based method can obtain a good performance with lower computational complexity compared with the existing methods.

Wheat impurity content is an essential index for evaluating the quality level and price of wheat or reserved grain. We obtain 2D slice images of the scanned sample by cone-beam CT, then a hybrid filtering algorithm is used to improve the quality of the 2D slice images. Finally, the 2D slice image is reconstructed in 3D to obtain volume data, so as to obtain the volume of each part, and then use the density formula to achieve the calculation of wheat impurity content. The experiments have shown that the proposed method can obtain the detection accuracy up to 90%, and can provide objective online detection of grain impurity content compared with the impurity detection of the national standard GT/T5494-2019.

As the ever‐increasing attention to green communication, energy efficiency has become an imperative metric in the emerging massive multiple‐input multiple‐output (MIMO) systems. In order to maximize the energy efficiency, transmit antenna selection has been widely concerned by researchers. In this paper, we investigate the coded cooperation transmission for dynamic transmit antennas aided two‐hop massive MIMO systems. Explicitly, we propose a rate‐less codes aided cooperation scheme for reducing the implementation complexity in the broadcast phase, compared to the fixed‐rate coded cooperation scheme. Furthermore, we develop a partial cooperation scheme in the cooperative phase in order to avoid the low achievable rate caused by the full cooperation, especially when the source‐to‐relay (S‐R) channels are poor. Finally, the number of transmit antennas at the base station (BS) is optimized through theoretical analysis in a metric of maximizing the energy efficiency. Moreover, we also analyze the achievable error performance for different modulations. Our simulation results demonstrate the effectiveness of the proposed scheme.