FITEE 2022 Issue 1 publishes a special topic on “Intellicise Wireless Network Theory and Technology”. Academician Zhang Ping from Beijing University of Posts and Telecommunications serves as the chief editor, and Professor Peng Mugeng from Beijing University of Posts and Telecommunications serves as the executive editor. Guest editors include Professor Cui Shuguang from The Chinese University of Hong Kong (Shenzhen), Professor Zhang Chaoyang from Zhejiang University, Professor Mao Guoqiang from Xi’an University of Electronic Science and Technology, Professor Quan Zhi from Shenzhen University, Professor Tony Q. S. Quek from Singapore University of Technology and Design, and Researcher Rong Bo from the Canadian Communications Research Centre. The issue includes 1 editorial, 1 review, and 5 research papers. Scan the QR code to download the full PDF.
Table of Contents for the Special Topic on “Intellicise Wireless Network Theory and Technology”
1. Theory and Techniques for Intellicise Wireless Networks (Editorial)
2. Intelligent Radio Access Networks: Architectures, Key Techniques, and Experimental Platforms (Review)
3. Ultra-Low-Power Backscatter-Based Software-Defined Radio Design for Intellicise IoT Networks
4. Beamforming and Fronthaul Compression Design for Intelligent Reflecting Surface Aided Cloud Radio Access Networks
5. Multi-Agent Deep Reinforcement Learning for End-Edge Orchestrated Resource Allocation in Industrial Wireless Networks
6. Coverage Performance Analysis of Multilayer UAV-Terrestrial Heterogeneous Networks with CoMP Transmission Mechanism
7. Joint Uplink and Downlink Resource Allocation for Low-Latency Mobile Virtual Reality Delivery in Fog Radio Access Networks
1. Theory and Techniques for “Intellicise” Wireless Networks
Intellicise Wireless Network Theory and Technology
Zhang Ping1, Peng Mugeng1, Cui Shuguang2, Zhang Chaoyang3, Mao Guoqiang4, Quan Zhi5, Tony Q.S. Quek6, Rong Bo7
1Beijing University of Posts and Telecommunications, State Key Laboratory of Networking and Switching Technology, Beijing, 100876, China2The Chinese University of Hong Kong (Shenzhen), School of Science and Engineering, Shenzhen, 518172, China3Zhejiang University, College of Information Science and Electronic Engineering, Hangzhou, 310027, China4Xi’an University of Electronic Science and Technology, Intelligent Transportation Research Institute, Xi’an, 710071, China5Shenzhen University, College of Electronics and Information Engineering, Shenzhen, 518060, China6Singapore University of Technology and Design, Information Systems Technology and Design, Singapore, 4873727Canadian Communications Research Centre, Ottawa, K2K 2Y7, Canada
Abstract:The evolution from 5G to 6G requires adaptation to more stringent and diverse application scenarios, stricter energy constraints, and more flexible multi-dimensional resource orchestration, while avoiding the sharp increase in resource demand and excessive complexity of network architecture and protocols brought about by network expansion. These challenges seek a new paradigm of intellicise wireless networks. Here, “intellicise” is a new adjective proposed in response to the characteristics and application demands of 6G, representing “intelligent endogenous and inherently simple”. Based on the integration of artificial intelligence and next-generation networking technologies, intellicise wireless networks continuously explore and utilize new intelligent primitives (e.g., semantic bases in semantic communication), actively aiming for global optimization with system entropy reduction as the goal, and adaptively reshaping the core model of information systems to ultimately achieve their own intelligent endogeneity and inherent simplicity. Against this backdrop, the journal “Frontiers of Information Technology & Electronic Engineering” (FITEE) organized this special topic on “Intellicise Wireless Network Theory and Technology”. The topic covers information theory, architectural design, and intellicise wireless networks, involving integrated applications across air, ground, and sea, resource management, hardware testing platforms, etc. Furthermore, the topic aims to review the progress in the field of intellicise wireless networks and look forward to future research directions.See the Special Topic Introduction.https://doi.org/10.1631/FITEE.2210000
2. Intelligent Radio Access Networks: Architectures, Key Techniques, and Experimental Platforms
Intelligent Radio Access Networks: Architectures, Key Techniques, and Experimental Platforms
Wang Zeyu, Sun Yaohua, Yuan ShuoBeijing University of Posts and Telecommunications, State Key Laboratory of Networking and Switching Technology, Beijing, 100876, ChinaAbstract:Intelligent Radio Access Networks (RANs) are a promising paradigm that can better meet various application needs and support various service scenarios. This paper summarizes the latest advancements in intelligent RANs. First, it summarizes the work of standard organizations and operators, introducing several intelligent RAN architectures proposed by academia, such as intent-driven RANs and networks with enhanced data analytics capabilities. Then, it summarizes enabling technologies, including AI-driven network slicing, intent awareness, intelligent operation and maintenance, AI-based cloud-edge collaborative networking, and intelligent multi-dimensional resource allocation. Additionally, recent advancements in open experimental platforms are introduced. Finally, given the broadness of the research field, future directions are discussed, including standard open datasets, AI-enabled computing networks, edge intelligence, and software-defined intelligent terrestrial satellite networks.Keywords:Intelligent Network Architecture; Artificial Intelligence; Experimental Platformshttps://doi.org/10.1631/FITEE.2100305
3. Ultra-Low-Power Backscatter-Based Software-Defined Radio for Intelligent and Simplified IoT Network
Ultra-Low-Power Backscatter-Based Software-Defined Radio Design for Intellicise IoT Networks
Dong Huixin1, Kuang Wei1, Xiao Fei2, Liu Lihai3, Xiang Feng4, Wang Wei1, He Jianhua51Huazhong University of Science and Technology, School of Electronics and Information Engineering, Wuhan, 430074, China2Huazhong University of Science and Technology, School of Management, Wuhan, 430074, China2China Railway Fourth Survey and Design Institute Group Co., Ltd., Wuhan, 430063, China3Wuhan Shipbuilding Communication Research Institute, Wuhan, 430079, China3University of Essex, School of Computer Science and Electronic Engineering, Colchester, CO4 3SQ, UK
Abstract:In recent years, there has been a surge in demand for intelligent and simplified communication IoT networks that provide ultra-low power for numerous miniaturized devices. Although researchers have begun to design communication protocols for these networks, there is a lack of a low-power, high-efficiency software-defined radio (SDR) development platform for rapid implementation and experimental evaluation. Existing SDR platforms work well only in active scenarios and are not suitable for miniaturized IoT devices with highly constrained hardware conditions and energy. This paper attempts to realize an ultra-low-power SDR platform that meets the communication R&D needs of ultra-low-power or even passive IoT nodes. To achieve this goal, µW-level backscatter communication technology is effectively integrated into the SDR platform, avoiding the use of high-power active RF front-end devices. A novel circuit containing energy harvesting and power management is designed, and methods to eliminate harmonic and image frequency interference caused by backscatter are proposed. The SDR performance under different modulation schemes is evaluated, achieving a high communication rate of 100 kb/s, with the node consuming less than 200 µW in the awake state and 10 µW in the sleep state. A railway inspection case study is conducted using this platform, achieving a passive data transmission efficiency of 1 kb/s at a distance of 50 meters in a real environment. Additionally, two cases of smart factories and logistics distribution are provided to explore the applications of the proposed platform.
Keywords:Backscatter; Ultra-Low-Power Software-Defined Radio; IoT Network
https://doi.org/10.1631/FITEE.2100321
4. Beamforming and Fronthaul Compression Design for Intelligent Reflecting Surface Aided Cloud Radio Access Networks
Beamforming and Fronthaul Compression Design for Intelligent Reflecting Surface Aided Cloud Radio Access Networks
Zhang Yu1,2, Wu Xuelu1, Peng Hong1, Zhong Caijun3, Chen Xiaoming31Zhejiang University, College of Information Engineering, Hangzhou, 310023, China2Southeast University, National Key Laboratory of Mobile Communication, Nanjing, 210096, China3Zhejiang University, College of Information and Electronic Engineering, Hangzhou, 310027, ChinaAbstract:Thanks to the current central information processing and resource management capabilities, Cloud Radio Access Networks (C-RAN) are a promising network structure for the simplified sixth generation (6G) wireless networks. However, to further enhance the capacity and coverage of C-RAN, more Remote Radio Heads (RRHs) and high-fidelity, low-latency fronthaul links need to be deployed, which leads to higher implementation costs. To address this issue, this paper proposes the use of Intelligent Reflecting Surfaces (IRS) as a low-cost and energy-efficient alternative to enhance C-RAN. Specifically, we consider multi-antenna users communicating uplink through multi-antenna RRHs to a baseband unit (BBU) pool, deploying multiple IRS between users and RRHs. RRHs can perform point-to-point compression or Wyner-Ziv coding to compress the received signals and then forward them to the BBU pool through the fronthaul link. The joint optimization of user transmission beamforming, passive beamforming of intelligent reflecting surfaces, and the covariance matrix of fronthaul compression noise is studied under the constraint of fronthaul link capacity to maximize the total uplink rate under point-to-point or Wyner-Ziv coding compression. By utilizing the Arimoto-Blahut algorithm and semi-definite relaxation (SDR), a continuous convex approximation method is proposed to solve the above non-convex problem, providing two iterative algorithms corresponding to point-to-point compression and Wyner-Ziv coding, respectively. Numerical simulation results verify the performance gains brought by deploying intelligent reflecting surfaces in C-RAN and the advantages of the proposed joint design.Keywords:Cloud Radio Access Network; Intelligent Reflecting Surface; Transmission Beamforming; Fronthaul Compressionhttps://doi.org/10.1631/FITEE.2100307
5. Multi-Agent Deep Reinforcement Learning for End–Edge Orchestrated Resource Allocation in Industrial Wireless Networks
Multi-Agent Deep Reinforcement Learning for End-Edge Coordinated Resource Allocation in Industrial Wireless Networks
Liu Xiaoyu1,2,3,4, Xu Chi1,2,3, Yu Haibin1,2,3, Zeng Peng1,2,31Shenyang Institute of Automation, Chinese Academy of Sciences, National Key Laboratory of Robotics, Shenyang, 110016, China2Chinese Academy of Sciences, Key Laboratory of Networked Control Systems, Shenyang, 110016, China3Chinese Academy of Sciences, Institute of Robotics and Intelligent Manufacturing, Shenyang, 110169, China4University of Chinese Academy of Sciences, Beijing, 100049, China
Abstract:Edge artificial intelligence empowers industrial wireless networks to support complex and dynamic industrial tasks by collaboratively utilizing limited network and computing resources on the device and edge sides. For resource-constrained industrial wireless networks, we propose a Multi-Agent Deep Reinforcement Learning Resource Allocation (MADRL-RA) algorithm that achieves end-edge coordinated resource allocation, supporting compute-intensive and delay-sensitive industrial applications. First, an end-edge coordinated industrial wireless network system model is established, treating industrial devices with perception capabilities as self-learning intelligent agents. Then, the end-edge resource allocation problem is formally described using a Markov decision process, establishing a minimum system cost problem for joint optimization of delay and energy consumption. Next, multi-agent deep reinforcement learning is utilized to overcome the curse of dimensionality while learning effective resource allocation strategies regarding computation decisions, computing power allocation, and transmission power. To break the temporal correlation of training data and accelerate the MADRL-RA learning process, an experience replay method with experience weighting is designed to classify, store, and sample experiences. Based on this, a stepwise ε-greedy method is proposed to balance the intelligent agents’ utilization of experiences and exploration. Finally, extensive comparative experiments validate the effectiveness of the MADRL-RA algorithm compared to various baseline algorithms. Experimental results show that MADRL-RA converges quickly and learns effective resource allocation strategies to achieve minimal system cost.
Keywords:Multi-Agent Deep Reinforcement Learning; End-Edge Coordination; Industrial Wireless Networks; Delay; Energy Consumptionhttps://doi.org/10.1631/FITEE.2100331
6. Coverage Performance of the Multilayer UAV-Terrestrial HetNet with CoMP Transmission Scheme
Coverage Performance Analysis of Multilayer UAV-Terrestrial Heterogeneous Networks with CoMP Transmission Mechanism
Wang Weihao, Jiang Yifan, Fei Zesong, Guo JingBeijing Institute of Technology, School of Information and Electronics, Beijing, 100081, ChinaAbstract:To meet the ubiquitous connectivity demands of sixth-generation mobile communications, drones play a key role as a major component of future communication networks. Interference caused by spectrum sharing and line-of-sight link transmission is a major issue in drone communications. In recent years, multi-point coordinated transmission technology has been proposed to reduce interference in drone-terrestrial heterogeneous networks. This paper proposes a three-dimensional multilayer UAV-terrestrial heterogeneous network, where drones are deployed as aerial base stations at different heights. Using stochastic geometry theory, a manageable mathematical framework is proposed to evaluate the interference statistical characteristics and coverage probability of this heterogeneous network. Numerical results show that the multi-point coordinated transmission mechanism can effectively alleviate interference in the network, especially when the base station density is high. Furthermore, the system parameters of aerial base stations deployed at higher altitudes are the main factors affecting the coverage performance of the proposed three-dimensional heterogeneous network.Keywords:UAV; Poisson Point Process; Multi-Point Coordination; Interference Statistical Characteristics; Coverage Performancehttps://doi.org/10.1631/FITEE.2100310
7. Joint Uplink and Downlink Resource Allocation for Low-Latency Mobile Virtual Reality Delivery in Fog Radio Access Networks
Joint Uplink and Downlink Resource Allocation for Low-Latency Mobile Virtual Reality Delivery in Fog Radio Access Networks
Dang Tian, Liu Chenxi, Liu Xiqing, Yan ShiBeijing University of Posts and Telecommunications, State Key Laboratory of Networking and Switching Technology, Beijing, 100876, China
Abstract:In Fog Radio Access Networks (F-RAN), fog access nodes are equipped with communication, caching, and computing capabilities, making F-RAN a wireless network architecture that can enable mobile virtual reality (VR) applications. To achieve mobile VR delivery, efficient downlink resource allocation strategies have been widely studied, but the equally important uplink resource allocation problem for VR delivery has received little attention. This paper studies a mobile VR delivery framework based on F-RAN, considering the impacts of both uplink and downlink transmissions. First, by characterizing the system round-trip delay, the impacts of communication, caching, and computing resources are revealed. Based on this, considering the constraints of caching and computing capacity as well as uplink and downlink link transmission capacity, a simple and efficient round-trip delay minimization algorithm is proposed. Simulation results show that the proposed algorithm can effectively reduce round-trip delay compared to other benchmark methods, clarifying the impacts of communication, caching, and computing resources on round-trip delay performance.
Keywords:Virtual Reality Delivery; Fog Radio Access Networks; Round-Trip Delay; Resource Allocation
https://doi.org/10.1631/FITEE.2100308
8. Dynamic Grouping of Heterogeneous Agents for Exploration and Strike Mission
Dynamic Grouping Strategy of Heterogeneous Intelligent Agents for Exploration and Strike Missions
Chen Chen1, Wu Xiaocheng1, Chen Jie1,2, Panos M. Pardalos3, Ding Shuxin41Beijing Institute of Technology, School of Automation, Beijing, 100081, China2Tongji University, Department of Control Science and Engineering, Shanghai, 200092, China3University of Florida, Department of Industrial and Systems Engineering, Gainesville, FL 32611, USA4China Academy of Railway Sciences, Communication Signal Research Institute, Beijing, 100081, ChinaAbstract:Dynamic environmental changes and complex combat tasks pose new requirements for the construction of task groups of unmanned combat intelligent agents. This paper aims to address the dynamic construction of task groups under new demands. Given the heterogeneity of agents, the group formation method must dynamically form new groups while continuously exploring tasks. A grouping strategy that integrates heuristic rules and response threshold models is proposed to dynamically adjust the members of task groups to adapt to new task requirements. The matching degree between task requirements and group capabilities, as well as the networking cost of the group, are taken as indicators to evaluate team quality. The response threshold method and ant colony algorithm are selected as comparative algorithms in the simulation experiments. The results show that the proposed method has certain advantages in solving the dynamic task group formation problem.Keywords:Multi-Agent; Dynamic Combat Tasks; Task Group Formation; Heuristic Rules; Networking Costhttps://doi.org/10.1631/FITEE.2000352
9. EDVAM: A 3D Eye-Tracking Dataset for Visual Attention Modeling in a Virtual Museum
EDVAM: A 3D Eye-Tracking Dataset for Visual Attention Modeling in a Virtual Museum
Zhou Yunzhan1, Feng Tian2, Shuai Shihui3, Li Xiangdong4, Sun Lingyun5, Du Benlin21Durham University, Department of Computer Science, Durham, DH1 3LE, UK2La Trobe University, School of Computer Science and Information Technology, Victoria, 3086, Australia3Alibaba Group, Hangzhou, 311121, China4Zhejiang University, Department of Digital Media, Hangzhou, 310027, China5Zhejiang University, International Design Research Institute, Hangzhou, 310058, ChinaAbstract:Visual attention prediction can help establish adaptive virtual museum environments, providing context-aware and interactive user experiences. Currently, research utilizing eye-tracking data to explore visual attention mechanisms is still limited to two-dimensional scenes. Researchers have yet to study this issue from both temporal and spatial perspectives in three-dimensional virtual scenes. To this end, we constructed the first 3D eye-tracking dataset for visual attention modeling in virtual museums, named EDVAM. We also established a deep learning model to predict users’ future visual attention areas based on historical eye-tracking trajectories to test EDVAM. This research can provide references for visual attention modeling and context-aware interaction in virtual museums.Keywords:Visual Attention; Virtual Museum; Eye-Tracking Dataset; Fixation Detection; Deep Learninghttps://doi.org/10.1631/FITEE.2000318
10. Motion Detection for High-Speed High-Brightness Objects Based on a Pulse Array Image Sensor
Motion Detection for High-Speed High-Brightness Objects Based on a Pulse Array Image Sensor
Zhang Peiwen1,2, Xu Jiangtao1,2, Nie Huafeng1,2, Gao Zhiyuan1,2, Nie Kaiming1,21Tianjin University, School of Microelectronics, Tianjin, 300072, China2Tianjin Key Laboratory of Imaging and Perception Microelectronics Technology, Tianjin, 300072, ChinaAbstract:A high-speed high-brightness target optical flow extraction method based on a Pulse Array Image Sensor (PAIS) is proposed. PAIS converts optical signals into a series of pulse intervals, mimicking a retina-like image sensor. By accumulating continuous pulses, optical flow is obtained directly from the pulse data stream, filtering out redundant data when the target has a significantly higher brightness than the background. This method fully utilizes the rapid response characteristics of PAIS to high-brightness targets. The method is applied to optical flow extraction of a high-speed rotating disk with different background brightness, conducting experiments in both sensor models and actual shooting data. Under sampling conditions of 2×104 frames/second, a high-speed rotating disk at 1000 revolutions per minute can filter out over 90% of redundant points. Experimental results show that the optical flow extraction algorithm based on pulse data can effectively extract high-brightness target optical flow information without reconstructing grayscale images.Keywords:Optical Flow; Pulse Array Image Sensor; Pulse Triggering; High-Speed Targets; Visual Processinghttps://doi.org/10.1631/FITEE.2000407
11. Identification of Important Factors Influencing Nonlinear Counting Systems
Identification of Important Factors Influencing Nonlinear Counting Systems
Zhang Xinmin, Wang Jingbo, Wei Chihang, Song ZhihuanZhejiang University, State Key Laboratory of Industrial Control Technology, Hangzhou, 310027, ChinaAbstract:Identifying key factors that significantly influence system output from data is one of the most challenging tasks in science and engineering. This paper proposes a sensitivity analysis-based Generalized Gaussian Process Regression (SA-GGPR) modeling method for nonlinear counting systems to identify key factors affecting system output. SA-GGPR employs a GGPR model with Poisson likelihood to describe nonlinear counting systems. The GGPR model inherits the advantages of non-parametric kernel learning and Poisson distribution, making it suitable for handling complex nonlinear counting systems. However, due to the non-parametric kernel learning architecture of the GGPR model, understanding the relationship between inputs and outputs in the GGPR model is challenging. The SA-GGPR method identifies key factors influencing system output by quantitatively assessing the impact of different inputs on system output. Application results in simulating nonlinear counting systems and actual steel rolling processes show that the SA-GGPR method outperforms several advanced methods in terms of identification accuracy.Keywords:Key Factors; Nonlinear Counting Systems; Generalized Gaussian Process Regression; Sensitivity Analysis; Steel Rolling Processhttps://doi.org/10.1631/FITEE.2000324
12. An Energy-Efficient Reconfigurable Asymmetric Modular Cryptographic Operation Unit for RSA and ECC
An Energy-Efficient Reconfigurable Asymmetric Modular Cryptographic Operation Unit for RSA and ECC
Nie Mengni1, Li Wei1, Chen Tao1, Nan Longmei2, Yang Danyang11University of Information Engineering, Zhengzhou, 450001, China2Fudan University, National Key Laboratory of Application-Specific Integrated Circuits and Systems, Shanghai, 200000, ChinaAbstract:RSA and Elliptic Curve Cryptography (ECC) algorithms are widely used for authentication, data security, and access control. This paper analyzes the basic operations of ECC and RSA algorithms and optimizes the modular multiplication and modular inversion algorithms. A reconfigurable modular operation unit with a hybrid memory unit and dual multiply-accumulate structure is proposed, achieving unification of asymmetric cryptographic algorithms at the operation unit level. The modular operation unit is synthesized using a 55 nm CMOS standard process, occupying 437,801 µm2 of hardware resources, with a maximum clock frequency of 588 MHz. The proposed modular operation unit completes 2048-bit RSA modular multiplication and modular inversion with power consumption of 21.92 mW and 23.36 mW, respectively, and completes 512-bit ECC dual-domain modular multiplication and modular inversion with power consumption of 16.16 mW and 15.88 mW, respectively. It is more efficient and flexible than existing single-algorithm units. Compared to existing multi-algorithm units, the proposed unit demonstrates better performance. The proposed modular operation unit is embedded in a 64-bit RISC-V processor, enabling RSA and ECC key generation, encryption and decryption, and digital signature functionalities. Experimental results show that the proposed design achieves 256-bit ECC point multiplication in 0.224 ms and 0.153 ms on G(p) and G(2m), respectively, and achieves 1024-bit RSA exponentiation in 0.96 ms, meeting high energy efficiency requirements.Keywords:Modular Operation Unit; Reconfigurable; High Energy Efficiencyhttps://doi.org/10.1631/FITEE.2000325
13. A Relation Spectrum Inheriting Taylor Series: Muscle Synergy and Coupling for Hand
A Relation Spectrum Inheriting Taylor Series: Muscle Synergy and Coupling for Hand
Liu Gang, Wang JingXi’an Jiaotong University, Institute of Robotics and Intelligent Systems, Xi’an, 710049, ChinaAbstract:There are two famous function decomposition methods in mathematics: Taylor series and Fourier series. The Fourier series has developed into the Fourier spectrum for signal decomposition and analysis; however, solving the Taylor series requires a known specific function expression, making it rarely applied in engineering fields. This paper develops the Taylor series using dendritic networks to construct a relation spectrum and applies it to model or system decomposition and analysis. Understanding the intuitive connection between muscle activation and finger movement is crucial for developing commercial prosthetics that do not require user pre-training. However, due to the complexity of the human hand, this intuitive connection has not been understood. This study uses relation spectrum analysis to analyze the muscle-finger system. In finger movements, one muscle drives multiple fingers simultaneously, while multiple muscles drive one finger simultaneously. Therefore, this research focuses on muscle synergy and coupling in the hand. This paper has two main contributions: (1) findings related to the hand contribute to the design of prosthetic hands; (2) the relation spectrum makes online models readable, thus unifying online performance and offline results. Open-source code can be found at https://github.com/liugang1234567/Gang-neuron.Keywords:Taylor Series; Relation Spectrum; Dendritic Networks; Prosthetic Hand; Machine Learning; Engineeringhttps://doi.org/10.1631/FITEE.2000578
14. Design and Optimization of a Gate-Controlled Dual Direction Electro-Static Discharge Device for an Industry-Level Fluorescent Optical Fiber Temperature Sensor
Design and Optimization of a Gate-Controlled Dual Direction Electro-Static Discharge Device for an Industry-Level Fluorescent Optical Fiber Temperature Sensor
Wang Yang1, Jin Xiangliang1, Yang Jian1, Yan Feng1, Liu Yujie1, Peng Yan2, Luo Jun2, Yang Jun31Hunan Normal University, College of Physics and Electronics, Changsha, 410081, China2Shanghai University, School of Mechanical Engineering and Automation, Shanghai, 200444, China3Western University, Faculty of Engineering, London, Ontario, N6A3K7, CanadaAbstract:The I/O pins of the readout circuit for industrial-grade fluorescent optical fiber temperature sensors require on-chip integration of high-performance electrostatic discharge (ESD) protection devices. The basic N-type buried gate-controlled thyristor (NBL-GCSCR) manufactured using a 0.18 µm standard BCD process has a failure level that is difficult to meet the requirements. Therefore, based on the same semiconductor process, a novel high-failure-level deep N-well gate-controlled thyristor (DNW-GCSCR) is proposed to effectively solve the above problem. The device characteristics are analyzed using Technology Computer-Aided Design (TCAD) simulation. The thyristor is tested using a transmission line pulse (TLP) to obtain accurate ESD parameters. The holding voltage of the NBL-GCSCR device with a vertical bipolar transistor (BJT) path is significantly higher (24.03 V) than that of the DNW-GCSCR device with the same size lateral thyristor path (5.15 V). The failure current of the NBL-GCSCR device is 1.71 A, while that of the DNW-GCSCR device is 20.99 A. When the gate size of the DNW-GCSCR increases from 2 µm to 6 µm, the holding voltage increases from 3.50 V to 8.38 V. The optimized DNW-GCSCR (gate size 6 µm) can be stably applied to the on-chip electrostatic discharge protection of the target readout circuit.Keywords:Electrostatic Breakdown; Semiconductor Device Reliability; CMOS Processhttps://doi.org/10.1631/FITEE.2000504
Previous Issue Directory
FITEE 2021 Issue 12
FITEE 2021 Issue 11
FITEE 2021 Issue 10
FITEE 2021 Issue 9
FITEE 2021 Issue 8
FITEE 2021 Issue 7
FITEE 2021 Issue 6
FITEE 2021 Issue 5 (First Issue of the “Visual Knowledge” Column)
FITEE 2021 Issue 4 (“High-Throughput Millimeter-Wave Wireless Communication” Special Issue)
FITEE 2021 Issue 3 (“Ultrafast Low-Dimensional Material Devices and Their Control” Special Issue)
FITEE 2021 Issue 2
FITEE 2021 Issue 1 (“Distributed Filtering and Control of Complex Networks and Systems” Special Issue)Journal Updates
The China Association for Science and Technology has released the “Comprehensive Directory of High-Quality Scientific Journals”, and FITEE has been included in the T1 directory of the information and communication field!
The first academic frontier forum in the field of information and electronic engineering was successfully held, led by Academician Duan Baoyan.
The latest impact factor for 2021 has been announced, and FITEE has surpassed 2.0 for the first time.
FITEE’s impact factor has increased by 55%, entering the Q2 zone for the first time.
FITEE has published the first list of outstanding papers/special topics and distinguished editorial board members/communication experts!
List of articles by FITEE editors and editorial board members (2019.1~2021.8)
List of articles by FITEE communication experts (2019.1~2021.8)
Focusing on advanced integrated circuit technology and industrial innovation, the 5th “Chinese Academy of Engineering Information and Electronic Engineering Frontier Forum” was successfully held!
The Chinese Academy of Engineering has released the 10+10 global engineering frontiers in the field of information electronics.
FITEE WeChat has launched a new feature, allowing users to read the Chinese and English abstracts and full texts of each issue without downloading PDFs.
The second expanded meeting of the 2020 editorial board of “Frontiers of Information Technology & Electronic Engineering” (FITEE) was successfully held.
The first meeting of the first batch of communication experts of FITEE was held at Zhejiang University.
The first meeting of the second editorial board of FITEE was held at Zhejiang University.
About This Journal
Frontiers of Information Technology & Electronic Engineering (abbreviated as FITEE, Chinese name 《信息与电子工程前沿（英文）》，ISSN 2095-9184, CN 33-1389/TP) is a comprehensive English academic monthly journal in the field of information electronics, indexed by SCI-E and EI,
with the latest impact factor of 2.161, located in the JCR Q2 zone.
It originated from the English version of the Journal of Zhejiang University C: Computer and Electronics, founded in 2010, and was renamed in 2015. It is currently the only journal of the Information and Electronic Engineering Division of the Chinese Academy of Engineering. It covers fields such as computer science, information and communication, control, electronics, and optics. Article types include research papers, reviews, personal viewpoints, and commentaries. The current editors-in-chief are Academicians Pan Yunhe and Lu Xicheng of the Chinese Academy of Engineering. The journal implements an international peer review system, with initial feedback generally provided within 2-3 months. Once accepted, articles will be published online quickly.
In 2019, it was funded by the “Excellence Action Plan for Chinese Scientific Journals” project launched by the China Association for Science and Technology and other seven ministries (Tiered Journals).
Official website: http://www.jzus.zju.edu.cn
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