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A Broadband, High-Efficiency, Low-Sidelobe Transmitarray Antenna Employing Hybrid Transmission Metasurface Polarizer

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IEEE Antennas and Wireless Propagation Letters 2025年

作者： Yang, Jianing Ming, Rui Zhang, Yanting Tang, Ming-Chun Chongqing University School of Microelectronics and communication engineering Chongqing401331 China State Key Laboratory of Millimeter Waves Nanjing210096 China

A broadband, high efficiency transmitarray antenna (TA) with low sidelobe levels is proposed. First, an array antenna pattern synthesis algorithm is employed to predict and optimize the TA's radiation performance. Then, a novel set of hybrid metasurface elements is introduced, improving transmission bandwidth and efficiency compared to conventional single meta-atom designs, without increasing fabrication complexity. These elements maintain an average transmission coefficient exceeding 0.94 and offer 360° phase coverage from 8 GHz to 16 GHz (relative bandwidth of 66.7%). A TA prototype with a 186 mm aperture diameter was fabricated, exhibiting a measured peak gain of 24.35 dBi, a 3 dB gain bandwidth of 60.5%, and a peak aperture efficiency of 55.4%. Moreover, within this 3 dB gain bandwidth, the average sidelobe level is approximately -22.1 dB. © 2002-2011 IEEE.

关键词： Directional patterns (antenna)

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Ellipsoid-based Learning for Robust Resource Allocation with Differentiated QoS in Massive Internet of Vehicles Networks

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IEEE Transactions on Vehicular Technology 2025年

作者： Huang, Jie Lai, Xianzhi Yang, Fan Zhang, Ni Niyato, Dusit Jiang, Weiheng Chongqing University of Technology School of Electrical and Electronic Engineering Chongqing400054 China Nanyang Technological University School of Computer Science and Engineering 639798 Singapore Chongqing University School of Microelectronics and Communication Engineering Chongqing400044 China

In massive Internet of Vehicles (mIoV) networks, the substantial number of vehicles and the dense deployment of communication devices lead to extensive overlap in signal coverage, resulting in frequent co-channel interference (CCI) and adjacent-channel interference (ACI). This interference significantly impacts the Quality of Service (QoS) experienced by vehicles. Moreover, the QoS requirements for vehicles vary widely across different application scenarios, further complicating the design and optimization of resource allocation strategies. To this end, we propose a robust resource allocation method for differentiated QoS in mIoV, leveraging ellipsoid learning and joint interference management. First, a weighted interference hypergraph model is developed to effectively mitigate ACI and CCI experienced by vehicles, while simultaneously addressing the diverse QoS requirements across different vehicle applications. Then, a robust optimization model for vehicle-to-vehicle pair (VP) communications is proposed, and underlying spectrum sharing is adopted to improve spectrum utilization. Furthermore, an ellipsoid-based learning robust algorithm (ELRA) strategy is proposed to address dynamic uncertainties arising from imperfect channel state information (CSI), thereby enhancing the reliability and transmission rate of the communication link. Simulation results demonstrate that the proposed algorithm achieves superior network throughput and spectral efficiency performance in densely deployed mIoV. © 1967-2012 IEEE.

关键词： Cochannel interference

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Electrically Small Unidirectional Mixed-Multipole Antennas: Recent Advances and Their Applications

Electrically Small Unidirectional Mixed-Multipole Antennas: ...

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European Conference on Antennas and Propagation, EuCAP

作者： Ming-Chun Tang Yi-Lin Lang Mei Li Richard W. Ziolkowski School of Microelectronics and Communication Engineering Chongqing University Chongqing China Department of Electrical and Computer Engineering University of Arizona Tucson AZ USA

ISBN: (数字)9788831299107

ISBN: (纸本)9798350366327

This paper reviews recent advances in and applications of electrically small unidirectional mixed-multipole antennas (ES-UMMAs), with a focus on notable improvements in bandwidth and directivity. The bandwidth enhancement methodologies applied to ES Huygens dipole antennas (HDAs), which are the lowest order UMMAs, are based on near-field resonant parasitic (NFRP) grid-shaped elements that act as electric dipoles and interdigitated capacitor (IDC) loaded loops that act as magnetic dipoles. Directivity enhancements include the realization of a superdirective ES Huygens quadrupole antenna (ES-HQA). These innovative dipole and quadrupole designs have been demonstrated experimentally; they achieve significantly improved performance characteristics over previously reported ES-HDAs. Their recent applications include integration with and direct impedance matching to complex circuits to realize rectennas for wireless power transfer (WPT) systems that exhibit superior AC-to-DC power conversion efficiencies. Examples include battery-less sensors such as an RFID epidermal skin temperature monitoring tag whose reading range is significantly beyond that of commercially available products. These developments enable ES-UMMAs as essential technologies for future generation (XG) compact and high-performance wireless systems, particularly for pioneering IoT and healthcare applications.

关键词： Temperature sensors Wireless communication Temperature measurement Dipole antennas Rectennas Magnetic resonance Bandwidth Wireless power transfer Internet of Things Monitoring

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CFragHMM - A Traffic Accident Critical Fragments Evaluation and Recognition Model

CFragHMM - A Traffic Accident Critical Fragments Evaluation ...

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Control Conference (ANZCC), Australian and New Zealand

作者： Qingwen Han Mingdeng Tan Xinyue Song Lei Ye Lingqiu Zeng Ke Liu Lingfeng Qi School of Microelectronics and Communication Engineering Chongqing University Chongqing China College of Computer Science Chongqing University Chongqing China

ISBN: (数字)9798331532192

ISBN: (纸本)9798331532208

The results of driving risk assessment are crucial for the development of driving safety warning strategys. In general, the driving risk assessment of road vehicles is determined by a combination of cruising characteristics and external road traffic conditions. However, the nature of driving accidents evolves gradually, and in order to detect potential accident events, common characteristics prior to the accident should be observed and investigated. Therefore, in this paper, a new concept, critical fragment, is proposed to express driving risk evolution. A series of impact factors are discussed, and XGBoost is used to select critical features. The Hidden Markov Model(HMM) is then designed to recognize critical fragments. Finally, the CFragHMM model proposed in this paper is obtained. The experimental results show that the proposed method is able to recognize the key segments well and provide basic information support for the timing selection that can be used as a traveling warning.

关键词： Road vehicles Hidden Markov models Feature extraction Road traffic Hazards Timing Risk management Indexes Data mining Accidents

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TS-CATMA: A Lung Cancer Electronic Nose Data Classification Method Based on Adversarial Training and Multi-scale Attention 21st

TS-CATMA: A Lung Cancer Electronic Nose Data Classification ...

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21st Pacific Rim International Conference on Artificial Intelligence, PRICAI 2024

作者： Chen, Yuze Yi, Lin Wang, Shidan Tian, Fengchun Liu, Ran College of Computer Science Chongqing University Chongqing400044 China Chongqing Key Laboratory of Translational Research for Cancer Metastasis and Individualized Treatment Chongqing University Cancer Hospital Chongqing400030 China School of Microelectronics and Communication Engineering Chongqing University Chongqing400044 China

ISBN: (纸本)9789819601189

Accurate lung cancer diagnosis is crucial for effective treatment and improved outcomes. This study introduces TS-CATMA (Time Series Classification with Adversarial Training and Multi-scale Attention), a novel method designed for lung cancer detection using electronic nose data. TS-CATMA leverages a multi-scale attention mechanism and adversarial training to extract discriminative, domain-invariant features from raw time series data. Evaluated on a lung cancer electronic nose dataset, TS-CATMA achieved a detection accuracy of 90.59% with rapid training (6.15 s) and testing (39.57 ms) times, indicating its potential for early diagnosis. The source code is available at https://***/CQU-3DTEAM/TS-CATMA. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Lung cancer

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A Quantized CSI Acquisition Strategy Based on Position Information Feedback for Indoor VLC-Based IoT Systems

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IEEE Internet of Things Journal 2025年

作者： Zhao, Qiong Fan, Jiacheng Lin, Bangjiang Chen, Chen Xi’an University of Posts and Telecommunications School of Communications and Information Engineering China Chinese Academy of Sciences Quanzhou Institute of Equipment Manufacturing Haixi Institutes China Chongqing University School of Microelectronics and Communication Engineering China

Channel State Information (CSI), characterizing real-time optical channel conditions, is critical for system optimization in visible light communication (VLC) systems. In VLC networks, CSI acquisition typically relies on uplink feedback mechanisms that require frequent updates due to rapid channel variations. As access point (AP) density increases, this feedback process incurs substantial overhead that scales with network size, becoming a major bottleneck for system scalability. ‌By decoupling static channel characteristics from dynamic user positions‌, this paper proposes a dual-step strategy decoupling offline channel quantization from online uplink positioning. This enables efficient downlink CSI reconstruction via pre-trained lookup tables, bypassing real-time computations. The feedback overhead scales as 1/M of conventional methods in M-AP systems, with experiments showing less than 3% spectrum efficiency loss for precoding-sensitive applications in high speed mobile scenarios. The framework’s adaptability to varying LED densities further supports practical deployment in large-scale networks.‌ This work resolves the CSI acquisition bottleneck, enabling scalable VLC systems with minimal performance degradation. © 2014 IEEE.

关键词： Visible light communication

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Deep Energy-Efficient Optimization Network for URLLC Over Cell-Free Massive MIMO

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IEEE Internet of Things Journal 2025年

作者： Li, Donggen Li, Jingfu Niyato, Dusit Feng, Wenjiang Jiang, Weiheng Chongqing University School of Microelectronics and Communication Engineering Chongqing400044 China Southwest Jiaotong University School of Information Science and Technology Chengdu611756 China Nanyang Technological University School of Computer Science and Engineering Singapore639798 Singapore

To achieve ultra-reliable and low-latency communication (URLLC) and support high density of wireless connections simultaneously, the sixth-generation industrial Internet of things (6G-IIoT) necessitates an expansion of antenna arrays and broader bandwidths, which suffers from high energy consumption. To address this issue, this paper investigates a cell-free massive multiple-input multiple-output (CF-mMIMO) system and designs an iterative search-based two-stage energy efficiency (EE) optimization algorithm for the uplink communication of the system. The first stage prioritizes reliability to ensure that all users meet the URLLC requirements regarding latency and reliability. The second stage maximizes the EE under URLLC-satisfied conditions. Considering that iterative search algorithms incur a high computational overhead and variable number of iterations, we further propose a convolutional neural network architecture (RACNN) to approximate an optimal resource allocation strategy and to realize the real-time and stable output. This structure extracts deep correlations among users from the global channel features. It takes strategies of multi-task learning and weight loss adaptation to improve the model's convergence speed. Furthermore, we employ deep transfer learning to adjust RACNN parameters to accommodate the potential of dynamic communication scenarios, thereby reducing the demand for training samples and training time overhead. Finally, the efficacy of the proposed algorithm, RACNN, and deep transfer learning is validated through experimental simulations. © 2014 IEEE.

关键词： Convolutional neural networks

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Near-Far Field Three-Stage Beam Training for RIS-Assisted Wideband OFDM communications

Near-Far Field Three-Stage Beam Training for RIS-Assisted Wi...

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IEEE Conference on Wireless communications and Networking

作者： Zhichao Cheng Shupei Zhang Shu Fu Boya Di School of Electronics Engineering and Computer Science Peking University Beijing China State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Peking University Beijing China Department of Microelectronics and Communication Engineering Chongqing University Chongqing China

ISBN: (数字)9798350368369

ISBN: (纸本)9798350368376

Large-scale reconfigurable intelligent surfaces (RISs) have emerged as a promising technology for signal strength enhancement and coverage extension in 6G networks. However, as the antenna scale and the bandwidth increase, large-scale RIS-assisted wideband orthogonal frequency division multiplexing (OFDM) communication systems face new challenges due to the near-field range expansion and the beam split effect, complicating the acquisition of channel state information (CSI). To tackle these challenges, in this paper, we present a wideband beam training scheme by utilizing the beam split effect to bypass the CSI acquisition. Specifically, by analyzing the beam split effect in RIS-assisted OFDM communication systems, we propose a beam-split-aware codebook capable of covering both the near and far fields. The coverage of codewords in the proposed codebook is expanded benefiting from the beam split effect, leading to fewer codewords compared to conventional narrow-band codebooks. Utilizing such a codebook, a three-stage beam training mechanism is performed to obtain the optimal codeword with low time overhead, thereby facilitating the beamforming. Simulation results demonstrate that the proposed scheme outperforms existing codebook-based beam training schemes in terms of training overhead and sum rate in the hybrid near-far field.

关键词： Training Upper bound Array signal processing OFDM Simulation Reconfigurable intelligent surfaces Broadband antennas Wideband Faces Channel state information

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Training Samples Selection Method Based on Model-Data-Driven for Maritime Radar Target Detection

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IEEE Sensors Journal 2025年

作者： Chen, Wenhao Li, Zhengzhou Ding, Zhiquan Qin, Tianqi Azeem, Abdullah Gan, Haolin Li, Aoran Chongqing University School of Microelectronics and Communication Engineering Chongqing40044 China Sichuan Institute of Aerospace Electronic Equipment Chengdu610000 China Chongqing University School of Computer Science Chongqing40044 China

Multidimensional feature extraction and fusion algorithms are widely utilized to improve the performance of radar maritime target detection. However, these methods often suffer from underfitting and overfitting issues due to the uneven distribution of training samples. To enhance the performance of maritime target detection while mitigating the issues of underfitting and overfitting, an effective approach is to improve the comprehensiveness of training samples. This study proposes a novel training sample selection method based on model-data-driven maritime radar target detection. A surrogate equation is constructed in this study using existing empirical models and measured data. Subsequently, it dynamically selects training samples exhibiting strong coverage and compactness, guided by the global and local variation characteristics of this surrogate equation. Experimental results show that, when using the same feature and classifier conditions, the feature classifiers formed by the proposed method outperform those built using traditional sample selection approaches (such as random assignment, expert knowledge, and statistical methods). This superiority is evident across various target types, including daily vessels, small fishing boats, and marine buoys, as well as under diverse sea conditions and observation parameters like incidence angles. This approach not only enhances the performance of maritime target detection, but also ensures the generalization ability of the method. © 2025 IEEE.

关键词： Fishing vessels

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Elastic Spectrum Sensing: An Adaptive Sensing Method for Non-Terrestrial communication Under Highly Dynamic Channels

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IEEE Transactions on Wireless communications 2025年第5期24卷 3868-3881页

作者： Xu, Tianheng Xu, Yinjun Zhou, Ting Zhang, Haijun Hu, Honglin Leung, Victor C. M. Shanghai Advanced Research Institute Chinese Academy of Sciences Shanghai201210 China Shanghai Frontier Innovation Research Institute Shanghai201100 China University of Chinese Academy of Sciences School of Electronic Electrical and Communication Engineering Beijing100049 China Shanghai University School of Microelectronics Shanghai200444 China Institute of Artificial Intelligence Beijing Advanced Innovation Center for Materials Genome Engineering Beijing Engineering and Technology Research Center for Convergence Networks and Ubiquitous Services University of Science and Technology Beijing Beijing100083 China Shenzhen University College of Computer Science and Software Engineering Shenzhen518060 China The University of British Columbia Department of Electrical and Computer Engineering VancouverBCV6T1Z4 Canada

With the rapid development of space technology, the role of satellite communications has become progressively significant. Non-terrestrial communication is deemed a critical scenario in the sixth generation (6G) communication systems, which showcases seamless connectivity, minimal geographic constraints and substantial communication capacity. Simultaneously, satellites and terminals spring up, spatial density increases, which further emphasizes the scarcity of spectrum resources. Consequently, to improve spectrum utilization for non-terrestrial communication is a significant concern. Spectrum sensing, which allows dynamic resource reuse, plays an important role in 6G. However, high mobility in non-terrestrial scenarios poses great challenges, such as fast time-varying channels, Doppler effect, etc., which seriously affect sensing accuracy and cannot well support optimal spectrum utilization. Motivated by such circumstances, this paper proposes an elastic sensing method for the downlink non-terrestrial communication scenario. Firstly, we design the system architecture and sensing workflow. To overcome the negative effects raised by high mobility, we propose the elastic sensing criterion and multi-area dividing scheme for the sensing zone. Thresholds affected by the elastic sensing are derived for different areas. Finally, the numerical results show that from -10 dB to -5 dB, the proposed method can improve the total performance by an average of 28.3% while stabilizing the false alarm probability around 0.1 typical level and demonstrating higher constancy compared with traditional technologies from −10 dB to −5 dB. © 2002-2012 IEEE.

关键词： Satellite communication systems

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