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Services and Key Technologies of the Internet of Things Xing Xiaojiang, Wang Jianli, Li Mingdong ZTE Communications    2010, 8 (2): 26-29.   Abstract （884）      PDF （451KB）（1205）       Knowledge map    Save This article introduces the services and development of the Internet of Things, and analyzes the driving forces and obstacles behind such development. Looking at application types and the different development stages of the Internet of Things, this article categorizes its services into four types: identity related services, information aggregation services, collaborative-aware services, and ubiquitous services. For the first two types of services, applications and system framework are discussed; for the last two types, development trends are discussed. Services provided by the Internet of Things will gradually be integrated into human life and society; with the development of the Internet of Things, applications will evolve from relatively simple identity-related and information aggregation-related applications, to collaboratively-aware, and finally ubiquitous applications. It will then be possible for the Internet of Things to be fully integrated with Internet and telecommunications networks. Related Articles | Metrics

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Cloud Computing: Concept, Model, and Key Technologies Kevin Yin ZTE Communications    2010, 8 (4): 21-26.   Abstract （494）      PDF （468KB）（875）       Knowledge map    Save Cloud computing is a new network computing paradigm based on IP architecture, and its potential lies in new ICT business applications. For the majority of operators and enterprises, the main task associated with cloud computing is next generation data center transformation. This will ensure cloud computing becomes more widespread among enterprises, institutions, organizations, and operators. Cloud computing not only provides traditional IT resource usage and application services, but also supports full resource usage and application services such as IT, communications, video, mobile, and Internet of Things using a converged network infrastructure. Key cloud computing technologies include unified fabric, unified virtualization, and unified computing system. The formation of an open industry alliance and promotion of open technology standards will be critical for the future development of cloud computing. Related Articles | Metrics

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Reliable and Privacy-Preserving Federated Learning with Anomalous Users ZHANG Weiting, LIANG Haotian, XU Yuhua, ZHANG Chuan ZTE Communications    2023, 21 (1): 15-24.   DOI: 10.12142/ZTECOM.202301003 Abstract （70）   HTML （11）    PDF （1351KB）（400）       Knowledge map    Save Recently, various privacy-preserving schemes have been proposed to resolve privacy issues in federated learning (FL). However, most of them ignore the fact that anomalous users holding low-quality data may reduce the accuracy of trained models. Although some existing works manage to solve this problem, they either lack privacy protection for users’ sensitive information or introduce a two-cloud model that is difficult to find in reality. A reliable and privacy-preserving FL scheme named reliable and privacy-preserving federated learning (RPPFL) based on a single-cloud model is proposed. Specifically, inspired by the truth discovery technique, we design an approach to identify the user’s reliability and thereby decrease the impact of anomalous users. In addition, an additively homomorphic cryptosystem is utilized to provide comprehensive privacy preservation (user’s local gradient privacy and reliability privacy). We give rigorous theoretical analysis to show the security of RPPFL. Based on open datasets, we conduct extensive experiments to demonstrate that RPPEL compares favorably with existing works in terms of efficiency and accuracy. Table and Figures | Reference | Related Articles | Metrics

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Boundary Data Augmentation for Offline Reinforcement Learning SHEN Jiahao, JIANG Ke, TAN Xiaoyang ZTE Communications    2023, 21 (3): 29-36.   DOI: 10.12142/ZTECOM.202303005 Abstract （185）   HTML （20）    PDF （1865KB）（310）       Knowledge map    Save Offline reinforcement learning (ORL) aims to learn a rational agent purely from behavior data without any online interaction. One of the major challenges encountered in ORL is the problem of distribution shift, i.e., the mismatch between the knowledge of the learned policy and the reality of the underlying environment. Recent works usually handle this in a too pessimistic manner to avoid out-of-distribution (OOD) queries as much as possible, but this can influence the robustness of the agents at unseen states. In this paper, we propose a simple but effective method to address this issue. The key idea of our method is to enhance the robustness of the new policy learned offline by weakening its confidence in highly uncertain regions, and we propose to find those regions by simulating them with modified Generative Adversarial Nets (GAN) such that the generated data not only follow the same distribution with the old experience but are very difficult to deal with by themselves, with regard to the behavior policy or some other reference policy. We then use this information to regularize the ORL algorithm to penalize the overconfidence behavior in these regions. Extensive experiments on several publicly available offline RL benchmarks demonstrate the feasibility and effectiveness of the proposed method. Table and Figures | Reference | Related Articles | Metrics

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Introduction to Cloud Manufacturing Li Bohu, Zhang Lin, Chai Xudong ZTE Communications    2010, 8 (4): 6-9.   Abstract （1295）      PDF （640KB）（832）       Knowledge map    Save Cloud manufacturing is a new, networked and intelligent manufacturing model that is service-oriented, knowledge based, high performance, and energy efficient. In this model, state-of-the-art technologies such as informatized manufacturing, cloud computing, Internet of Things, semantic Web, and high-performance computing are integrated in order to provide secure, reliable, and high quality on-demand services at low prices for those involved in the whole manufacturing lifecycle. As an important part of cloud manufacturing, cloud simulation technology based on the COSIM-CSP platform has primarily been applied in the design of a multidisciplinary virtual prototype of a flight vehicle. This lays the foundation for further research into cloud manufacturing. Related Articles | Metrics

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Learning-Based Admission Control for Low-Earth-Orbit Satellite Communication Networks CHENG Lei, QIN Shuang, FENG Gang ZTE Communications    2023, 21 (3): 54-62.   DOI: 10.12142/ZTECOM.202303008 Abstract （75）   HTML （14）    PDF （1188KB）（227）       Knowledge map    Save Satellite communications has been regarded as an indispensable technology for future mobile networks to provide extremely high data rates, ultra-reliability, and ubiquitous coverage. However, the high dynamics caused by the fast movement of low-earth-orbit (LEO) satellites bring huge challenges in designing and optimizing satellite communication systems. Especially, admission control, deciding which users with diversified service requirements are allowed to access the network with limited resources, is of paramount importance to improve network resource utilization and meet the service quality requirements of users. In this paper, we propose a dynamic channel reservation strategy based on the Actor-Critic algorithm (AC-DCRS) to perform intelligent admission control in satellite networks. By carefully designing the long-term reward function and dynamically adjusting the reserved channel threshold, AC-DCRS reaches a long-run optimal access policy for both new calls and handover calls with different service priorities. Numerical results show that our proposed AC-DCRS outperforms traditional channel reservation strategies in terms of overall access failure probability, the average call success rate, and channel utilization under various dynamic traffic conditions. Table and Figures | Reference | Related Articles | Metrics

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A Novel 28 GHz Phased Array Antenna for 5G Mobile Communications LI Yezhen, REN Yongli, YANG Fan, XU Shenheng, ZHANG Jiannian ZTE Communications    2020, 18 (3): 20-25.   DOI: 10.12142/ZTECOM.202003004 Abstract （189）   HTML （74）    PDF （3130KB）（488）       Knowledge map    Save A novel phased array antenna consisting of 256 elements is presented and experimentally verified for 5G millimeter-wave wireless communications. The antenna integrated with a wave control circuit can perform real-time beam scanning by reconfiguring the phase of an antenna unit. The unit, designed at 28 GHz using a simple patch structure with one PIN diode, can be electronically controlled to generate 1 bit phase quantization. A prototype of the antenna is fabricated and measured to demonstrate the feasibility of this approach. The measurement results indicate that the antenna achieves high gain and fast beam-steering, with the scan beams within ±60° range and the maximum gain up to 21.7 dBi. Furthermore, it is also tested for wireless video transmission. In ZTE Shanghai, the antenna was used for the 5G New Radio (NR) test. The error vector magnitude (EVM) is less than 3% and the adjacent channel leakage ratio (ACLR) less than -35 dBc, which can meet 5G system requirements. Compared with the conventional phased array antenna, the proposed phased array has the advantages of low power consumption, low cost and conformal geometry. Due to these characteristics, the antenna is promising for wide applications in 5G millimeter-wave communication systems. Table and Figures | Reference | Related Articles | Metrics

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Multi-Agent Hierarchical Graph Attention Reinforcement Learning for Grid-Aware Energy Management FENG Bingyi, FENG Mingxiao, WANG Minrui, ZHOU Wengang, LI Houqiang ZTE Communications    2023, 21 (3): 11-21.   DOI: 10.12142/ZTECOM.202303003 Abstract （76）   HTML （14）    PDF （1238KB）（184）       Knowledge map    Save The increasing adoption of renewable energy has posed challenges for voltage regulation in power distribution networks. Grid-aware energy management, which includes the control of smart inverters and energy management systems, is a trending way to mitigate this problem. However, existing multi-agent reinforcement learning methods for grid-aware energy management have not sufficiently considered the importance of agent cooperation and the unique characteristics of the grid, which leads to limited performance. In this study, we propose a new approach named multi-agent hierarchical graph attention reinforcement learning framework (MAHGA) to stabilize the voltage. Specifically, under the paradigm of centralized training and decentralized execution, we model the power distribution network as a novel hierarchical graph containing the agent-level topology and the bus-level topology. Then a hierarchical graph attention model is devised to capture the complex correlation between agents. Moreover, we incorporate graph contrastive learning as an auxiliary task in the reinforcement learning process to improve representation learning from graphs. Experiments on several real-world scenarios reveal that our approach achieves the best performance and can reduce the number of voltage violations remarkably. Table and Figures | Reference | Related Articles | Metrics

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Double Deep Q-Network Decoder Based on EEG Brain-Computer Interface REN Min, XU Renyu, ZHU Ting ZTE Communications    2023, 21 (3): 3-10.   DOI: 10.12142/ZTECOM.202303002 Abstract （135）   HTML （14）    PDF （1551KB）（172）       Knowledge map    Save Brain-computer interfaces (BCI) use neural activity as a control signal to enable direct communication between the human brain and external devices. The electrical signals generated by the brain are captured through electroencephalogram (EEG) and translated into neural intentions reflecting the user's behavior. Correct decoding of the neural intentions then facilitates the control of external devices. Reinforcement learning-based BCIs enhance decoders to complete tasks based only on feedback signals (rewards) from the environment, building a general framework for dynamic mapping from neural intentions to actions that adapt to changing environments. However, using traditional reinforcement learning methods can have challenges such as the curse of dimensionality and poor generalization. Therefore, in this paper, we use deep reinforcement learning to construct decoders for the correct decoding of EEG signals, demonstrate its feasibility through experiments, and demonstrate its stronger generalization on motion imaging (MI) EEG data signals with high dynamic characteristics. Table and Figures | Reference | Related Articles | Metrics

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Modulation Techniques for Li-Fi Mohamed Sufyan Islim, Harald Haas ZTE Communications    2016, 14 (2): 29-40.   DOI: 10.3969/j.issn.1673-5188.2016.02.004 Abstract （1696）      PDF （476KB）（993）       Knowledge map    Save Modulation techniques for light fidelity (Li-Fi) are reviewed in this paper. Li-Fi is the fully networked solution for multiple users that combines communication and illumination simultaneously. Light emitting diodes (LEDs) are used in Li-Fi as visible light transmitters, therefore, only intensity modulated direct detected modulation techniques can be achieved. Single carrier modulation techniques are straightforward to be used in Li-Fi, however, computationally complex equalization processes are required in frequency selective Li-Fi channels. On the other hand, multicarrier modulation techniques offer a viable solution for Li-Fi in terms of power, spectral and computational efficiency. In particular, orthogonal frequency division multiplexing (OFDM) based modula-tion techniques offer a practical solution for Li-Fi, especially when direct current (DC) wander, and adaptive bit and power loading techniques are considered. Li-Fi modulation techniques need to also satisfy illumination requirements. Flickering avoidance and dimming control are considered in the variant modulation techniques presented. This paper surveys the suitable modulation techniques for Li-Fi including those which explore time, frequency and colour domains. Related Articles | Metrics

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Enabling Energy Efficiency in 5G Network LIU Zhuang, GAO Yin, LI Dapeng, CHEN Jiajun, HAN Jiren ZTE Communications    2021, 19 (1): 20-29.   DOI: 10.12142/ZTECOM.202101004 Abstract （203）   HTML （5）    PDF （1356KB）（460）       Knowledge map    Save The mobile Internet and Internet of Things are considered the main driving forces of 5G, as they require an ultra-dense deployment of small base stations to meet the increasing traffic demands. 5G new radio (NR) access is designed to enable denser network deployments, while leading to a significant concern about the network energy consumption. Energy consumption is a main part of network operational expense (OPEX), and base stations work as the main energy consumption equipment in the radio access network (RAN). In order to achieve RAN energy efficiency (EE), switching off cells is a strategy to reduce the energy consumption of networks during off-peak conditions. This paper introduces NR cell switching on/off schemes in 3GPP to achieve energy efficiency in 5G RAN, including intra-system energy saving (ES) scheme and inter-system ES scheme. Additionally, NR architectural features including central unit/distributed unit (CU/DU) split and dual connectivity (DC) are also considered in NR energy saving. How to apply artificial intelligence (AI) into 5G networks is a new topic in 3GPP, and we also propose a machine learning (ML) based scheme to save energy by switching off the cell selected relying on the load prediction. According to the experiment results in the real wireless environment, the ML based ES scheme can reduce more power consumption than the conventional ES scheme without load prediction. Table and Figures | Reference | Related Articles | Metrics

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Differential Quasi-Yagi Antenna and Array ZHU Zhihao, ZHANG Yueping ZTE Communications    2023, 21 (3): 37-44.   DOI: 10.12142/ZTECOM.202303006 Abstract （204）   HTML （11）    PDF （2723KB）（152）       Knowledge map    Save A novel differential quasi-Yagi antenna is first presented and compared with a normal single-ended counterpart. The simulated and measured results show that the differential quasi-Yagi antenna outperforms the conventional single-ended one. The differential quasi-Yagi antenna is then used as an element for linear arrays. A study of the coupling mechanism between the two differential and the two single-ended quasi-Yagi antennas is conducted, which reveals that the TE0 mode is the dominant mode, and the driver is the decisive part to account for the mutual coupling. Next, the effects of four decoupling structures are respectively evaluated between the two differential quasi-Yagi antennas. Finally, the arrays with simple but effective decoupling structures are fabricated and measured. The measured results demonstrate that the simple slit or air-hole decoupling structure can reduce the coupling level from -18 dB to -25 dB and meanwhile maintain the impedance matching and radiation patterns of the array over the broad bandwidth. The differential quasi-Yagi antenna should be a promising antenna candidate for many applications. Table and Figures | Reference | Related Articles | Metrics

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A Survey of Federated Learning on Non-IID Data HAN Xuming, GAO Minghan, WANG Limin, HE Zaobo, WANG Yanze ZTE Communications    2022, 20 (3): 17-26.   DOI: 10.12142/ZTECOM.202203003 Abstract （144）   HTML （13）    PDF （3213KB）（187）       Knowledge map    Save Federated learning (FL) is a machine learning paradigm for data silos and privacy protection，which aims to organize multiple clients for training global machine learning models without exposing data to all parties. However, when dealing with non-independently identically distributed (non-IID) client data, FL cannot obtain more satisfactory results than centrally trained machine learning and even fails to match the accuracy of the local model obtained by client training alone. To analyze and address the above issues, we survey the state-of-the-art methods in the literature related to FL on non-IID data. On this basis, a motivation-based taxonomy, which classifies these methods into two categories, including heterogeneity reducing strategies and adaptability enhancing strategies, is proposed. Moreover, the core ideas and main challenges of these methods are analyzed. Finally, we envision several promising research directions that have not been thoroughly studied, in hope of promoting research in related fields to a certain extent. Table and Figures | Reference | Related Articles | Metrics

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Barcelona Smart City: The Heaven on Earth (Internet of Things: Technological God) Somayya Madakam, Ramaswamy Ramachandran ZTE Communications    2015, 13 (4): 3-9.   DOI: 10.3969/j.issn.1673-5188.2015.04.001 Abstract （278）      PDF （564KB）（342）       Knowledge map    Save Cities are the most preferable dwelling places, having with better employment opportunities, educational hubs, medical services, recreational facilities, theme parks, and shopping malls etc. Cities are the driving forces for any national economy too. Unfortunately now a days, these cities are producing circa 70% of pollutants, even though they only occupy 2% of surface of the Earth. Public utility services cannot meet the demands of unexpected growth. The filthiness in cities causing decreasing of Quality of Life. In this light our research paper is giving more concentration on necessity of “Smart Cities”, which are the basis for civic centric services. This article is throwing light on Smart Cities and its important roles. The beauty of this manuscript is scribbling “Smart Cities” concepts in pictorially. Moreover this explains on“Barcelona Smart City”using Internet of Things Technologies”. It is a good example in urban paradigm shift. Bracelona is like the heaven on the earth with by providing Quality of Life to all urban citizens. The GOD is Interenet of Things. Related Articles | Metrics

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Standardization of Fieldbus and Industrial Ethernet CHEN Jinghe, ZHANG Hesheng ZTE Communications    2019, 17 (2): 51-58.   DOI: 10.12142/ZTECOM.201902008 Abstract （107）   HTML （16）    PDF （296KB）（216）       Knowledge map    Save Fieldbus and industrial Ethernet standards can guide the specification and coordinate bus optimization. The standards are the basis for the development of fieldbus and industrial Ethernet. In this paper, we review complex standard systems all over the world. We discuss 18 fieldbus standards, including the International Electrotechnical Commission (IEC) 61158, the IEC 61784 standard matched with IEC 61158, the controller and device interface standard IEC 62026 for low voltage distribution and control devices, and the International Organization for Standardization (ISO) 11898 and ISO 11519 standards related to the controller area network (CAN) bus. We also introduce the standards of China, Europe, Japan and America. This paper provides a reference to develop fieldbus and industrial Ethernet products for Chinese enterprises. Table and Figures | Reference | Related Articles | Metrics

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Intelligent 6G Wireless Network with Multi-Dimensional Information Perception YANG Bei, LIANG Xin, LIU Shengnan, JIANG Zheng, ZHU Jianchi, SHE Xiaoming ZTE Communications    2023, 21 (2): 3-10.   DOI: 10.12142/ZTECOM.202302002 Abstract （121）   HTML （3）    PDF （737KB）（103）       Knowledge map    Save Intelligence and perception are two operative technologies in 6G scenarios. The intelligent wireless network and information perception require a deep fusion of artificial intelligence (AI) and wireless communications in 6G systems. Therefore, fusion is becoming a typical feature and key challenge of 6G wireless communication systems. In this paper, we focus on the critical issues and propose three application scenarios in 6G wireless systems. Specifically, we first discuss the fusion of AI and 6G networks for the enhancement of 5G-advanced technology and future wireless communication systems. Then, we introduce the wireless AI technology architecture with 6G multi-dimensional information perception, which includes the physical layer technology of multi-dimensional feature information perception, full spectrum fusion technology, and intelligent wireless resource management. The discussion of key technologies for intelligent 6G wireless network networks is expected to provide a guideline for future research. Table and Figures | Reference | Related Articles | Metrics

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Signal Processing Techniques for 5G: An Overview Fa-Long Luo ZTE Communications    2015, 13 (1): 20-27.   DOI: 10.3969/j.issn.1673-5188.2015.01.003 Abstract （234）      PDF （401KB）（269）       Knowledge map    Save This paper gives an outline of the algorithms and implementation of the main signal processing techniques being developed for 5G wireless communication. The first part contains a review and comparison of six orthogonal and non-orthogonal waveform-generation and modulation schemes: generalized frequency-division multiplexing (GFDM), filter-bank multicarrier (FBMC), universal filtered multicarrier (UFMC), bi-orthogonal frequency-division multiplexing (BFDM), sparse-code multiple-access (SCMA), and non-orthogo-nal multiple access (NOMA). The second part discusses spatial signal processing algorithms and implementations for massive multiple-input multiple-output (massive-MIMO), 3D beamforming and diversity, and orbital angular momentum (OAM) based multi-plexing. The last part gives an overview of signal processing aspects of other emerging techniques in 5G, such as millimeter-wave, cloud radio access networks, full duplex mode, and digital radio-frequency processing. Related Articles | Metrics

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Log Anomaly Detection Through GPT-2 for Large Scale Systems JI Yuhe, HAN Jing, ZHAO Yongxin, ZHANG Shenglin, GONG Zican ZTE Communications    2023, 21 (3): 70-76.   DOI: 10.12142/ZTECOM.202303010 Abstract （72）   HTML （7）    PDF （537KB）（137）       Knowledge map    Save As the scale of software systems expands, maintaining their stable operation has become an extraordinary challenge. System logs are semi-structured text generated by the recording function in the source code and have important research significance in software service anomaly detection. Existing log anomaly detection methods mainly focus on the statistical characteristics of logs, making it difficult to distinguish the semantic differences between normal and abnormal logs, and performing poorly on real-world industrial log data. In this paper, we propose an unsupervised framework for log anomaly detection based on generative pre-training-2 (GPT-2). We apply our approach to two industrial systems. The experimental results on two datasets show that our approach outperforms state-of-the-art approaches for log anomaly detection. Table and Figures | Reference | Related Articles | Metrics

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Study on Security of 5G and Satellite Converged Communication Network YAN Xincheng, TENG Huiyun, PING Li, JIANG Zhihong, ZHOU Na ZTE Communications    2021, 19 (4): 79-89.   DOI: 10.12142/ZTECOM.202104009 Abstract （154）   HTML （11）    PDF （1924KB）（222）       Knowledge map    Save The 5G and satellite converged communication network (5G SCCN) is an important component of the integration of satellite-terrestrial networks, the national science, and technology major projects towards 2030. Security is the key to ensuring its operation, but at present, the research in this area has just started in our country. Based on the network characteristics and security risks, we propose the security architecture of the 5G SCCN and systematically sort out the key protection technologies and improvement directions. In particular, unique thinking on the security of lightweight data communication and design reference for the 5G SCCN network architecture is presented. It is expected to provide a piece of reference for the follow-up 5G SCCN security technology research, standard evolution, and industrialization. Table and Figures | Reference | Related Articles | Metrics

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An OS for Internet of Everything: Early Experience from A Smart Home Prototype CAO Jie, XU Lanyu, Raef Abdallah, SHI Weisong ZTE Communications    2017, 15 (4): 12-22.   DOI: 10.3969/j.issn.1673-5188.2017.04.002 Abstract （106）   HTML （26）    PDF （543KB）（207）       Knowledge map    Save The proliferation of the Internet of Everything (IoE) has pulled computing to the edge of the network, such as smart homes, autonomous vehicles, robots, and so on. The operating system as the manager of the computing resources, is also facing new challenges. For IoE systems and applications, an innovative operating system is missing to support services, collect data, and manage the things. However, IoE applications are all around us and increasingly becoming a necessity rather than a luxury. Therefore, it is important that the process of configuring and adding devices to the IoE is not a complex one. The ease of installation, operation, and maintenance of devices on the network unarguably plays an important role in the wide spread use of IoE devices in smart homes and everywhere else. In this paper, we propose Sofie, which is a smart operating system for the IoE. We also give the design of Sofie. Sofie can be implemented via different IoT systems, such as Home Assistant, openHAB, and so on. In order to implement Sofie to get some early experience, we leverage Home Assistant to build a prototype for the smart home. Our work shows that Sofie could be helpful for practitioners to better manage their IoE systems. Table and Figures | Reference | Related Articles | Metrics

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Time Sensitive Networking Technology Overview and Performance Analysis FU Shousai, ZHANG Hesheng, CHEN Jinghe ZTE Communications    2018, 16 (4): 57-64.   DOI: 10.19729/j.cnki.1673-5188.2018.04.009 Abstract （124）   HTML （7）    PDF （519KB）（216）       Knowledge map    Save Time sensitive networking (TSN) is a set of standards developed on the basis of audio video bridging (AVB). It has a promising future in the Industrial Internet of Things and vehicle-mounted multimedia, with such advantages as high bandwidth, interoperability and low cost. In this paper, the TSN protocol stack is described and key technologies of network operation are summarized, including time synchronization, scheduling and flow shaping, flow management and fault tolerant mechanism. The TSN network model is then established. Its performance is illustrated to show how the frame priority works and also show the influence of IEEE802.1Qbv time-aware shaper and IEEE802.1Qbu frame preemption on network and time-sensitive data. Finally, we briefly discuss the challenges faced by TSN and the focus of future research. Table and Figures | Reference | Related Articles | Metrics

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Kinetic Energy Harvesting Toward Battery-Free IoT: Fundamentals, Co-Design Necessity and Prospects LIANG Junrui, LI Xin, YANG Hailiang ZTE Communications    2021, 19 (1): 48-60.   DOI: 10.12142/ZTECOM.202101007 Abstract （130）   HTML （9）    PDF （1567KB）（494）       Knowledge map    Save Energy harvesting (EH) technology is developed with the purpose of harnessing ambient energy in different physical forms. Although the available ambient energy is usually tiny, not comparable to the centralized power generation, it brings out the convenience of on-site power generation by drawing energy from local sources, which meets the emerging power demand of long-lasting, extensively-deployed, and maintenance-free Internet of Things (IoT). Kinetic energy harvesting (KEH) is one of the most promising EH solutions toward the realization of battery-free IoT. The KEH-based battery-free IoT can be extensively deployed in the smart home, smart building, and smart city scenarios, enabling perceptivity, intelligence, and connectivity in many infrastructures. This paper gives a brief introduction to the configurations and basic principles of practical KEH-IoT systems, including their mechanical, electrical, and computing parts. Although there are already a few commercial products in some specific application markets, the understanding and practice in the co-design and optimization of a single KEH-IoT device are far from mature, let alone the conceived multiagent energy-autonomous intelligent systems. Future research and development of the KEH-IoT system beckons for more exchange and collaboration among mechanical, electrical, and computer engineers toward general design guidelines to cope with these interdisciplinary engineering problems. Table and Figures | Reference | Related Articles | Metrics

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Payload Encoding Representation from Transformer for Encrypted Traffic Classification HE Hongye, YANG Zhiguo, CHEN Xiangning ZTE Communications    2021, 19 (4): 90-97.   DOI: 10.12142/ZTECOM.202104010 Abstract （201）   HTML （23）    PDF （965KB）（322）       Knowledge map    Save Traffic identification becomes more important, yet more challenging as related encryption techniques are rapidly developing nowadays. Unlike recent deep learning methods that apply image processing to solve such encrypted traffic problems, in this paper, we propose a method named Payload Encoding Representation from Transformer (PERT) to perform automatic traffic feature extraction using a state-of-the-art dynamic word embedding technique. By implementing traffic classification experiments on a public encrypted traffic data set and our captured Android HTTPS traffic, we prove the proposed method can achieve an obvious better effectiveness than other compared baselines. To the best of our knowledge, this is the first time the encrypted traffic classification with the dynamic word embedding has been addressed. Table and Figures | Reference | Related Articles | Metrics

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Massive Unsourced Random Access Under Carrier Frequency Offset XIE Xinyu, WU Yongpeng, YUAN Zhifeng, MA Yihua ZTE Communications    2023, 21 (3): 45-53.   DOI: 10.12142/ZTECOM.202303007 Abstract （59）   HTML （8）    PDF （1438KB）（115）       Knowledge map    Save Unsourced random access (URA) is a new perspective of massive access which aims at supporting numerous machine-type users. With the appearance of carrier frequency offset (CFO), joint activity detection and channel estimation, which is vital for multiple-input and multiple-output URA, is a challenging task. To handle the phase corruption of channel measurements under CFO, a novel compressed sensing algorithm is proposed, leveraging the parametric bilinear generalized approximate message passing framework with a Markov chain support model that captures the block sparsity structure of the considered angular domain channel. An uncoupled transmission scheme is proposed to reduce system complexity, where slot-emitted messages are reorganized relying on clustering unique user channels. Simulation results reveal that the proposed transmission design for URA under CFO outperforms other potential methods. Table and Figures | Reference | Related Articles | Metrics

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A Practical Reinforcement Learning Framework for Automatic Radar Detection YU Junpeng, CHEN Yiyu ZTE Communications    2023, 21 (3): 22-28.   DOI: 10.12142/ZTECOM.202303004 Abstract （39）   HTML （4）    PDF （456KB）（98）       Knowledge map    Save At present, the parameters of radar detection rely heavily on manual adjustment and empirical knowledge, resulting in low automation. Traditional manual adjustment methods cannot meet the requirements of modern radars for high efficiency, high precision, and high automation. Therefore, it is necessary to explore a new intelligent radar control learning framework and technology to improve the capability and automation of radar detection. Reinforcement learning is popular in decision task learning, but the shortage of samples in radar control tasks makes it difficult to meet the requirements of reinforcement learning. To address the above issues, we propose a practical radar operation reinforcement learning framework, and integrate offline reinforcement learning and meta-reinforcement learning methods to alleviate the sample requirements of reinforcement learning. Experimental results show that our method can automatically perform as humans in radar detection with real-world settings, thereby promoting the practical application of reinforcement learning in radar operation. Table and Figures | Reference | Related Articles | Metrics

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Big-Data Processing Techniques and Their Challenges in Transport Domain Aftab Ahmed Chandio, Nikos Tziritas, Cheng-Zhong Xu ZTE Communications    2015, 13 (1): 50-59.   DOI: 10.3969/j.issn.1673-5188.2015.01.007 Abstract （351）      PDF （453KB）（272）       Knowledge map    Save This paper describes the fundamentals of cloud computing and current big-data key technologies. We categorize big-data processing as batch-based, stream-based, graph-based, DAG-based, interactive-based, or visual-based according to the processing technique. We highlight the strengths and weaknesses of various big-data cloud processing techniques in order to help the big-data community select the appropriate processing technique. We also provide big data research challenges and future directions in aspect to transportation management systems. Related Articles | Metrics

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Recent Developments of Transmissive Reconfigurable Intelligent Surfaces: A Review TANG Junwen, XU Shenheng, YANG Fan, LI Maokun ZTE Communications    2022, 20 (1): 21-27.   DOI: 10.12142/ZTECOM.202201004 Abstract （177）   HTML （15）    PDF （1869KB）（360）       Knowledge map    Save Reconfigurable intelligent surface (RIS) is considered as one of the key technologies for the next-generation mobile communication systems. The transmissive RIS is able to achieve dynamic beamforming capability while transmitting an in-band RF signal through its aperture, and has promising prospects in various practical application scenarios. This paper reviews some of the latest developments of the transmissive RIS. The approaches for transmissive RIS designs are classified and described briefly. Numerous designs with different phase resolutions, such as 1-bit, 2-bit or continuous 360° phase shifts, are presented, with detailed discussions on their operating mechanisms and transmission performances. The design solutions for various transmissive RIS elements are summarized and compared. Table and Figures | Reference | Related Articles | Metrics

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Special Topic on Reinforcement Learning and Intelligent Decision GAO Yang ZTE Communications    2023, 21 (3): 1-2.   DOI: 10.12142/ZTECOM.202303001 Abstract （43）   HTML （10）    PDF （334KB）（94）       Knowledge map    Save Reference | Related Articles | Metrics

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Cloud Computing(4) Wang Bai, Xu Liutong ZTE Communications    2010, 8 (4): 57-60.   Abstract （54）      PDF （408KB）（304）       Knowledge map    Save Related Articles | Metrics

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A 220 GHz Frequency-Division Multiplexing Wireless Link with High Data Rate ZHANG Bo, WANG Yihui, FENG Yinian, YANG Yonghui, PENG Lin ZTE Communications    2023, 21 (3): 63-69.   DOI: 10.12142/ZTECOM.202303009 Abstract （57）   HTML （3）    PDF （2704KB）（118）       Knowledge map    Save With the development of wireless communication, the 6G mobile communication technology has received wide attention. As one of the key technologies of 6G, terahertz （THz） communication technology has the characteristics of ultra-high bandwidth, high security and low environmental noise. In this paper, a THz duplexer with a half-wavelength coupling structure and a sub-harmonic mixer operating at 216 GHz and 204 GHz are designed and measured. Based on these key devices, a 220 GHz frequency-division multiplexing communication system is proposed, with a real-time data rate of 10.4 Gbit/s for one channel and a transmission distance of 15 m. The measured constellation diagram of two receivers is clearly visible, the signal-to-noise ratio (SNR) is higher than 22 dB, and the bit error ratio (BER) is less than 10-8. Furthermore, the high definition (HD) 4K video can also be transmitted in real time without stutter. Table and Figures | Reference | Related Articles | Metrics

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Cloud Storage Technology and Its Applications Zhou Ke, Wang Hua, Li Chunhua ZTE Communications    2010, 8 (4): 27-30.   Abstract （434）      PDF （521KB）（316）       Knowledge map    Save Cloud storage employs software that interconnects and facilitates collaboration between different types of storage devices. Compared with traditional storage methods, cloud storage poses new challenges in data security, reliability, and management. This paper introduces four layers of cloud storage architecture: data storage layer (connecting multiple storage components), data management layer (providing common support technology for multiple services), data service layer (sustaining multiple storage applications), and user access layer. A typical cloud storage application—Backup Cloud (B-Cloud)—is examined and its software architecture, characteristics, and main research areas are discussed. Related Articles | Metrics

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An Overview of Non-Orthogonal Multiple Access Anass Benjebbour ZTE Communications    2017, 15 (S1): 21-30.   DOI: 10.3969/j.issn.1673-5188.2017.S1.003 Abstract （480）   HTML （120）    PDF （519KB）（359）       Knowledge map    Save In recent years, non-orthogonal multiple access (NOMA) has attracted a lot of attention as a novel and promising power-domain user multiplexing scheme for Long-Term Evolution (LTE) enhancement and 5G. NOMA is able to contribute to the improvement of the tradeoff between system capacity and user fairness (i.e., cell-edge user experience). This improvement becomes in particular emphasized in a cellular system where the channel conditions vary significantly among users due to the near-far effect. In this article, we provide an overview of the concept, design and performance of NOMA. In addition, we review the potential benefits and issues of NOMA over orthogonal multiple access (OMA) such as orthogonal frequency division multiple access (OFDMA) adopted by LTE, and the status of 3GPP standardization related to NOMA. Table and Figures | Reference | Related Articles | Metrics

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Application of Industrial Internet Identifier in Optical Fiber Industrial Chain SHI Zongsheng, JIANG Jian, JING Sizhe, LI Qiyuan, MA Xiaoran ZTE Communications    2020, 18 (1): 66-72.   DOI: 10.12142/ZTECOM.202001010 Abstract （82）   HTML （3）    PDF （677KB）（102）       Knowledge map    Save The industrial Internet has germinated with the integration of the traditional industry and information technologies. An identifier is the identification of an object in the industrial Internet. The identifier technology is a method to validate the identification of an object and trace it. The identifier is a bridge to connect information islands in the industry, as well as the data basis for building a technology application ecosystem based on identifier resolution. We propose three practical applications and application scenarios of the industrial Internet identifier in this paper. Future applications of identifier resolution in the industrial Internet field are also presented Table and Figures | Reference | Related Articles | Metrics

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Towards Near-Field Communications for 6G: Challenges and Opportunities LIU Mengyu, ZHANG Yang, JIN Yasheng, ZHI Kangda, PAN Cunhua ZTE Communications    2024, 22 (1): 3-15.   DOI: 10.12142/ZTECOM.202401002 Abstract （68）   HTML （4）    PDF （2702KB）（87）       Knowledge map    Save Extremely large-scale multiple-input multiple-output (XL-MIMO) and terahertz (THz) communications are pivotal candidate technologies for supporting the development of 6G mobile networks. However, these techniques invalidate the common assumptions of far-field plane waves and introduce many new properties. To accurately understand the performance of these new techniques, spherical wave modeling of near-field communications needs to be applied for future research. Hence, the investigation of near-field communication holds significant importance for the advancement of 6G, which brings many new and open research challenges in contrast to conventional far-field communication. In this paper, we first formulate a general model of the near-field channel and discuss the influence of spatial nonstationary properties on the near-field channel modeling. Subsequently, we discuss the challenges encountered in the near field in terms of beam training, localization, and transmission scheme design, respectively. Finally, we point out some promising research directions for near-field communications. Table and Figures | Reference | Related Articles | Metrics

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Password Pattern and Vulnerability Analysis for Web and Mobile Applications LI Shancang, Imed Romdhani, William Buchanan ZTE Communications    2016, 14 (S0): 32-36.   DOI: 10.3969/j.issn.1673-5188.2016.S0.006 Abstract （134）      PDF （320KB）（144）       Knowledge map    Save Text-based passwords are heavily used to defense for many web and mobile applications. In this paper, we investigated the patterns and vulnerabilities for both web and mobile applications based on conditions of the Shannon entropy, Guessing entropy and Minimum entropy. We show how to substantially improve upon the strength of passwords based on the analysis of text-password entropies. By analyzing the passwords datasets of Rockyou and 163.com, we believe strong password can be designed based on good usability, deployability, rememberbility, and security entropies. Related Articles | Metrics

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Programmable Metasurface for Simultaneously Wireless Information and Power Transfer System CHANG Mingyang, HAN Jiaqi, MA Xiangjin, XUE Hao, WU Xiaonan, LI Long, CUI Tiejun ZTE Communications    2022, 20 (2): 48-62.   DOI: 10.12142/ZTECOM.202202008 Abstract （176）   HTML （11）    PDF （5135KB）（160）       Knowledge map    Save Implementing self-sustainable wireless communication systems is urgent and challenging for 5G and 6G technologies. In this paper, we elaborate on a system solution using the programmable metasurface (PMS) for simultaneous wireless information and power transfers (SWIPT), offering an optimized wireless energy management network. Both transmitting and receiving sides of the proposed solution are presented in detail. On the transmitting side, employing the wireless power transfer (WPT) technique, we present versatile power conveying strategies for near-field or far-field targets, single or multiple targets, and equal or unequal power targets. On the receiving side, utilizing the wireless energy harvesting (WEH) technique, we report our work on multi-functional rectifying metasurfaces that collect the wirelessly transmitted energy and the ambient energy. More importantly, a numerical model based on the plane-wave angular spectrum method is investigated to accurately calculate the radiation fields of PMS in the Fresnel and Fraunhofer regions. With this model, the efficiencies of WPT between the transmitter and the receiver are analyzed. Finally, future research directions are discussed, and integrated PMS for wireless information and wireless power is outlined. Table and Figures | Reference | Related Articles | Metrics

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DDoS Attack Detection Method for Space-Based Network Based on SDN Architecture JIA Min, SHU Yuejie, GUO Qing, GAO Zihe, XIE Suofei ZTE Communications    2020, 18 (4): 18-25.   DOI: 10.12142/ZTECOM.202004004 Abstract （132）   HTML （129）    PDF （1428KB）（174）       Knowledge map    Save With the development of satellite communications, the number of satellite nodes is constantly increasing, which undoubtedly increases the difficulty of maintaining network security. Combining software defined network (SDN) with traditional space-based networks provides a new class of ideas for solving this problem. However, because of the highly centralized network management of the SDN controller, once the SDN controller is destroyed by network attacks, the network it manages will be paralyzed due to loss of control. One of the main security threats to SDN controllers is Distributed Denial of Service (DDoS) attacks, so how to detect DDoS attacks scientifically has become a hot topic among SDN security management. This paper proposes a DDoS attack detection method for space-based networks based on SDN architecture. This attack detection method combines the optimized Long Short-Term Memory (LSTM) deep learning model and Support Vector Machine (SVM), which can not only make classification judgments on the time series, but also achieve the purpose of detecting and judging through the flow characteristics of a period of time. In addition, it can reduce the detection time as well as the system burden. Table and Figures | Reference | Related Articles | Metrics

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A Network Traffic Prediction Method Based on LSTM WANG Shihao, ZHUO Qinzheng, YAN Han, LI Qianmu, QI Yong ZTE Communications    2019, 17 (2): 19-25.   DOI: 10.12142/ZTECOM.201902004 Abstract （291）   HTML （94）    PDF （1526KB）（223）       Knowledge map    Save As the network sizes continue to increase, network traffic grows exponentially. In this situation, how to accurately predict network traffic to serve customers better has become one of the issues that Internet service providers care most about. Current traditional network models cannot predict network traffic that behaves as a nonlinear system. In this paper, a long short-term memory (LSTM) neural network model is proposed to predict network traffic that behaves as a nonlinear system. According to characteristics of autocorrelation, an autocorrelation coefficient is added to the model to improve the accuracy of the prediction model. Several experiments were conducted using real-world data, showing the effectiveness of LSTM model and the improved accuracy with autocorrelation considered. The experimental results show that the proposed model is efficient and suitable for real-world network traffic prediction. Table and Figures | Reference | Related Articles | Metrics

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5G New Radio (NR): Standard and Technology Fa-Long Lu ZTE Communications    2017, 15 (S1): 1-2.   Abstract （216）   HTML （11）    PDF （200KB）（283）       Knowledge map    Save Reference | Related Articles | Metrics

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Special Topic on Evolution of AI Enabled Wireless Networks WANG Ling, GAO Yin ZTE Communications    2023, 21 (2): 1-2.   DOI: 10.12142/ZTECOM.202302001 Abstract （31）   HTML （5）    PDF （416KB）（84）       Knowledge map    Save Reference | Related Articles | Metrics