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Signal Detection and Channel Estimation in OTFS NAIKOTI Ashwitha, CHOCKALINGAM Ananthanarayanan ZTE Communications    2021, 19 (4): 16-33.   DOI: 10.12142/ZTECOM.202104003 Abstract （367）   HTML （10）    PDF （2749KB）（572）       Knowledge map    Save Orthogonal time frequency space (OTFS) modulation is a recently proposed modulation scheme that exhibits robust performance in high-Doppler environments. It is a two-dimensional modulation scheme where information symbols are multiplexed in the delay-Doppler (DD) domain. Also, the channel is viewed in the DD domain where the channel response is sparse and time-invariant for a long time. This simplifies channel estimation in the DD domain. This paper presents an overview of the state-of-the-art approaches in OTFS signal detection and DD channel estimation. We classify the signal detection approaches into three categories, namely, low-complexity linear detection, approximate maximum a posteriori (MAP) detection, and deep neural network (DNN) based detection. Similarly, we classify the DD channel estimation approaches into three categories, namely, separate pilot approach, embedded pilot approach, and superimposed pilot approach. We compile and present an overview of some of the key algorithms under these categories and illustrate their performance and complexity attributes. Table and Figures | Reference | 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）（399）       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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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）（352）       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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Recent Progress in Research and Development of Reconfigurable Intelligent Surface YUAN Yifei, GU Qi, WANG Anna, WU Dan, LI Ya ZTE Communications    2022, 20 (1): 3-13.   DOI: 10.12142/ZTECOM.202201002 Abstract （149）   HTML （24）    PDF （2269KB）（351）       Knowledge map    Save We aim to provide a comprehensive overview of the progress in research and development of the reconfigurable intelligent surface (RIS) over the last 2–3 years in this paper, especially when the RIS is used as relays in next-generation mobile networks. Major areas of research in academia are outlined, including fundamental performance, channel estimation, joint optimization with antenna precoding at base stations, propagation channel modeling and meta-material devices of RIS elements. Development in industry is surveyed from the aspects of performance potentials and issues, realistic joint optimization algorithms, control mechanisms, field trials and related activities in standardization development organizations (SDOs). Our views on how to carry out the engineering-aspect study on RIS for 6G systems are also presented, which cover the realistic performance, the comparison with other topological improvements, approaches for channel modeling, factors for designing control mechanisms and the timeline for RIS standardization. Table and Figures | Reference | Related Articles | Metrics

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A Survey on Low Complexity Detectors for OTFS Systems ZHANG Zhengquan, LIU Heng, WANG Qianli, FAN Pingzhi ZTE Communications    2021, 19 (4): 3-15.   DOI: 10.12142/ZTECOM.202104002 Abstract （173）   HTML （11）    PDF （1427KB）（346）       Knowledge map    Save The newly emerging orthogonal time frequency space (OTFS) modulation can obtain delay-Doppler diversity gain to significantly improve the system performance in high mobility wireless communication scenarios such as vehicle-to-everything (V2X), high-speed railway and unmanned aerial vehicles (UAV), by employing inverse symplectic finite Fourier transform (ISFFT) and symplectic finite Fourier transform (SFFT). However, OTFS modulation will dramatically increase system complexity, especially at the receiver side. Thus, designing low complexity OTFS receiver is a key issue for OTFS modulation to be adopted by new-generation wireless communication systems. In this paper, we review low complexity OTFS detectors and provide some insights on future researches. We firstly present the OTFS system model and basic principles, followed by an overview of OTFS detector structures, classifications and comparative discussion. We also survey the principles of OTFS detection algorithms. Furthermore, we discuss the design of hybrid OTFS and orthogonal frequency division multiplexing (OFDM) detectors in single user and multi-user multi-waveform communication systems. Finally, we address the main challenges in designing low complexity OTFS detectors and identify some future research directions. 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）（321）       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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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 （181）   HTML （19）    PDF （1865KB）（306）       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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Dual‑Polarized RIS‑Based STBC Transmission with Polarization Coupling Analysis ZHOU Mingyong, CHEN Xiangyu, TANG Wankai, KE Jun Chen, JIN Shi, CHENG Qiang, CUI Tie Jun ZTE Communications    2022, 20 (1): 63-75.   DOI: 10.12142/ZTECOM.202201009 Abstract （166）   HTML （21）    PDF （1409KB）（285）       Knowledge map    Save The rapid development of the reconfigurable intelligent surface (RIS) technology has given rise to a new paradigm of wireless transmitters. At present, most research works on RIS-based transmitters focus on single-polarized RISs. In this paper, we propose a dual-polarized RIS-based transmitter, which realizes 4-transmit space-time block coding (STBC) transmission by properly partitioning RIS’s unit cells and utilizing the degree of freedom of polarization. The proposed scheme is evaluated through a prototype system that utilizes a fabricated dual-polarized phase-adjustable RIS. In particular, the polarization coupling phenomenon in each unit cell of the employed dual-polarized RIS is modeled and analyzed. The experimental results are in good agreement with the theoretical modeling and analysis results, and an initial research effort is made on characterizing the polarization coupling property in the dual-polarized RIS. Table and Figures | Reference | Related Articles | Metrics

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OTFS Enabled NOMA for MMTC Systems over LEO Satellite MA Yiyan, MA Guoyu, WANG Ning, ZHONG Zhangdui, AI Bo ZTE Communications    2021, 19 (4): 63-70.   DOI: 10.12142/ZTECOM.202104007 Abstract （113）   HTML （6）    PDF （528KB）（268）       Knowledge map    Save As a complement of terrestrial networks, non-terrestrial networks (NTN) have advantages of wide-area coverage and service continuity. The NTN is potential to play an important role in the 5G new radio (NR) and beyond. To enable the massive machine type communications (mMTC), the low earth orbit (LEO) satellite is preferred due to its lower transmission delay and path loss. However, the LEO satellite may generate notable Doppler shifts to degrade the system performance. Recently, orthogonal time frequency space (OTFS) modulation has been proposed. It provides the opportunity to allocate delay Doppler (DD) domain resources, which is promising for mitigating the effect of high mobility. Besides, as the LEO satellite constellation systems such as Starlink are thriving, the space spectrum resources have become increasingly scarce. Therefore, non-orthogonal multiple access (NOMA) is considered as a candidate technology to realize mMTC with limited spectrum resources. In this paper, the application of OTFS enabled NOMA for mMTC over the LEO satellite is investigated. The LEO satellite based mMTC system and the OTFS-NOMA schemes are described. Subsequently, the challenges of applying OTFS and NOMA into LEO satellite mMTC systems are discussed. Finally, the potential technologies for the systems are investigated. Table and Figures | Reference | Related Articles | Metrics

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Orthogonal Time Frequency Space Modulation in Multiple-Antenna Systems WANG Dong, WANG Fanggang, LI Xiran, YUAN Pu, JIANG Dajie ZTE Communications    2021, 19 (4): 71-78.   DOI: 10.12142/ZTECOM.202104008 Abstract （68）   HTML （3）    PDF （1729KB）（250）       Knowledge map    Save The application of the orthogonal time frequency space (OTFS) modulation in multiple-antenna systems is investigated. The diversity and/or the multiplexing gain can be achieved by deploying various multiple-antenna techniques, and thus the reliability and/or the spectral efficiency are improved correspondingly. We provide two classes of OTFS-based multiple-antenna approaches for both the open-loop and the closed-loop systems. Specifically, in the open-loop system, a transmitting diversity approach, which resembles the space-time coding technique, is proposed by allocating the information symbols appropriately in the delay-Doppler domain. In the closed-loop system, we adopt the Tomlinson-Harashima precoding in our derived delay-Doppler equivalent transmission model. Numerical evaluations demonstrate the advantages of applying the multiple-antenna techniques to the OTFS. At last, several challenges and opportunities are presented. Table and Figures | Reference | Related Articles | Metrics

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Editorial: Special Topic on OTFS Modulation for 6G and Future High Mobility Communications YUAN Jinhong, FAN Pingzhi, BAI Baoming, AI Bo ZTE Communications    2021, 19 (4): 1-2.   DOI: 10.12142/ZTECOM.202104001 Abstract （57）   HTML （11）    PDF （365KB）（246）       Knowledge map    Save Reference | Related Articles | Metrics

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Message Passing Based Detection for Orthogonal Time Frequency Space Modulation YUAN Zhengdao, LIU Fei, GUO Qinghua, WANG Zhongyong ZTE Communications    2021, 19 (4): 34-44.   DOI: 10.12142/ZTECOM.202104004 Abstract （226）   HTML （7）    PDF （2103KB）（240）       Knowledge map    Save The orthogonal time frequency space (OTFS) modulation has emerged as a promising modulation scheme for wireless communications in high-mobility scenarios. An efficient detector is of paramount importance to harvesting the time and frequency diversities promised by OTFS. Recently, some message passing based detectors have been developed by exploiting the features of the OTFS channel matrices. In this paper, we provide an overview of some recent message passing based OTFS detectors, compare their performance, and shed some light on potential research on the design of message passing based OTFS receivers. Table and Figures | Reference | Related Articles | Metrics

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Some Observations and Thoughts about Reconfigurable Intelligent Surface Application for 5G Evolution and 6G HOU Xiaolin, LI Xiang, WANG Xin, CHEN Lan, SUYAMA Satoshi ZTE Communications    2022, 20 (1): 14-20.   DOI: 10.12142/ZTECOM.202201003 Abstract （176）   HTML （19）    PDF （1684KB）（226）       Knowledge map    Save Reconfigurable intelligent surface (RIS) is one of the hottest research topics for 5G evolution and 6G. It is expected that RIS can improve the system capacity and coverage with low cost and power consumption. This paper first discusses typical applications of RIS for 5G evolution and 6G, including RIS-aided smart channels and RIS-aided mega multiple-input multiple-output (MIMO). Then, several observations from RIS trials and system-level simulations are presented, especially those on the deployment strategy and the potential performance gain of RIS for coverage enhancement. The near-field effect and a two-step dynamic RIS beamforming method are also discussed. Finally, we summarize the challenges and opportunities of the RIS technology for 5G evolution and 6G, including hardware design, system and channel modeling, algorithm design and optimization, and standardization. We also suggest a step-by-step commercialization strategy as a conclusion. Table and Figures | Reference | 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 （74）   HTML （14）    PDF （1188KB）（225）       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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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 （153）   HTML （11）    PDF （1924KB）（221）       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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Performance of LDPC Coded OTFS Systems over High Mobility Channels ZHANG Chong, XING Wang, YUAN Jinhong, ZHOU Yiqing ZTE Communications    2021, 19 (4): 45-53.   DOI: 10.12142/ZTECOM.202104005 Abstract （80）   HTML （12）    PDF （1808KB）（207）       Knowledge map    Save The upcoming 6G wireless networks have to provide reliable communications in high-mobility scenarios at high carrier frequencies. However, high-mobility or high carrier frequencies will bring severe inter-carrier interference (ICI) to conventional orthogonal frequency-division multiplexing (OFDM) modulation. Orthogonal time frequency space (OTFS) modulation is a recently developing multi-carrier transmission scheme for wireless communications in high-mobility environments. This paper evaluates the performance of coded OTFS systems. In particular, we consider 5G low density parity check (LDPC) codes for OTFS systems based on 5G OFDM frame structures over high mobility channels. We show the performance of the OTFS systems with 5G LDPC codes when sum-product detection algorithm and iterative detection and decoding are employed. We also illustrate the effect of channel estimation error on the performance of the LDPC coded OTFS systems. Table and Figures | Reference | Related Articles | Metrics

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Multi-Cell Uplink Interference Management: A Distributed Power Control Method HU Huimin, LIU Yuan, GE Yiyang, WEI Ning, XIONG Ke ZTE Communications    2022, 20 (S1): 56-63.   DOI: 10.12142/ZTECOM.2022S1008 Abstract （69）   HTML （7）    PDF （1395KB）（202）       Knowledge map    Save This paper investigates a multi-cell uplink network, where the orthogonal frequency division multiplexing (OFDM) protocol is considered to mitigate the intra-cell interference. An optimization problem is formulated to maximize the user supporting ratio for the uplink multi-cell system by optimizing the transmit power. This paper adopts the user supporting ratio as the main performance metric. Our goal is to improve the user supporting ratio of each cell. Since the formulated optimization problem is non-convex, it cannot be solved by using traditional convex-based optimization methods. Thus, a distributed method with low complexity and a small amount of multi-cell interaction is proposed. Numerical results show that a notable performance gain achieved by our proposed scheme compared with the traditional one is without inter-cell interaction. 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）（181）       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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End-to-End Chinese Entity Recognition Based on BERT-BiLSTM-ATT-CRF LI Daiyi, TU Yaofeng, ZHOU Xiangsheng, ZHANG Yangming, MA Zongmin ZTE Communications    2022, 20 (S1): 27-35.   DOI: 10.12142/ZTECOM.2022S1005 Abstract （206）   HTML （13）    PDF （436KB）（180）       Knowledge map    Save Traditional named entity recognition methods need professional domain knowledge and a large amount of human participation to extract features, as well as the Chinese named entity recognition method based on a neural network model, which brings the problem that vector representation is too singular in the process of character vector representation. To solve the above problem, we propose a Chinese named entity recognition method based on the BERT-BiLSTM-ATT-CRF model. Firstly, we use the bidirectional encoder representations from transformers (BERT) pre-training language model to obtain the semantic vector of the word according to the context information of the word; Secondly, the word vectors trained by BERT are input into the bidirectional long-term and short-term memory network embedded with attention mechanism (BiLSTM-ATT) to capture the most important semantic information in the sentence; Finally, the conditional random field (CRF) is used to learn the dependence between adjacent tags to obtain the global optimal sentence level tag sequence. The experimental results show that the proposed model achieves state-of-the-art performance on both Microsoft Research Asia (MSRA) corpus and people’s daily corpus, with F1 values of 94.77% and 95.97% respectively. Table and Figures | Reference | Related Articles | Metrics

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Coded Orthogonal Time Frequency Space Modulation LIU Mengmeng, LI Shuangyang, ZHANG Chunqiong, WANG Boyu, BAI Baoming ZTE Communications    2021, 19 (4): 54-62.   DOI: 10.12142/ZTECOM.202104006 Abstract （80）   HTML （7）    PDF （1327KB）（171）       Knowledge map    Save Orthogonal time frequency space (OTFS) modulation is a novel two-dimensional modulation scheme for high-Doppler fading scenarios, which is implemented in the delay-Doppler (DD) domain. In time and frequency selective channels, OTFS modulation is more robust than the popular orthogonal frequency division multiplexing (OFDM) modulation technique. To further improve transmission reliability, some channel coding schemes are used in the OTFS modulation system. In this paper, the coded OTFS modulation system is considered and introduced in detail. Furthermore, the performance of the uncoded/coded OTFS system and OFDM system is analyzed with different relative speeds, modulation schemes, and iterations. Simulation results show that the OTFS system has the potential of full diversity gain and better robustness under high mobility scenarios. 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）（169）       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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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 （143）   HTML （13）    PDF （3213KB）（164）       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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Resource Allocation for Two‑Tier RIS‑Assisted Heterogeneous NOMA Networks XU Yongjun, YANG Zhaohui, HUANG Chongwen, YUEN Chau, GUI Guan ZTE Communications    2022, 20 (1): 36-47.   DOI: 10.12142/ZTECOM.202201006 Abstract （82）   HTML （2）    PDF （1761KB）（155）       Knowledge map    Save Reconfigurable intelligent surface (RIS) as a promising technology has been proposed to change weak communication environments. However, most of the current resource allocation (RA) schemes have focused on RIS-assisted homogeneous networks, and there is still no open works about RA schemes of RIS-assisted heterogeneous networks (HetNets). In this paper, we design an RA scheme for a RIS-assisted HetNet with non-orthogonal multiple access to improve spectrum efficiency and transmission rates. In particular, we jointly optimize the transmit power of the small-cell base station and the phase-shift matrix of the RIS to maximize the sum rates of all small-cell users, subject to the unit modulus constraint, the minimum signal-to-interference-plus-noise ratio constraint, and the cross-tier interference constraint for protecting communication quality of microcell users. An efficient suboptimal RA scheme is proposed based on the alternating iteration approach, and successive convex approximation and logarithmic transformation approach. Simulation results verify the effectiveness of the proposed scheme in terms of data rates. 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 （203）   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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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 （175）   HTML （11）    PDF （5135KB）（150）       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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Markovian Cascaded Channel Estimation for RIS Aided Massive MIMO Using 1‑Bit ADCs and Oversampling SHAO Zhichao, YAN Wenjing, YUAN Xiaojun ZTE Communications    2022, 20 (1): 48-56.   DOI: 10.12142/ZTECOM.202201007 Abstract （90）   HTML （8）    PDF （1115KB）（149）       Knowledge map    Save A reconfigurable intelligent surface (RIS) aided massive multiple-input multiple-output (MIMO) system is considered, where the base station employs a large antenna array with low-cost and low-power 1-bit analog-to-digital converters (ADCs). To compensate for the performance loss caused by the coarse quantization, oversampling is applied at the receiver. The main challenge for the acquisition of cascaded channel state information in such a system is to handle the distortion caused by the 1-bit quantization and the sample correlation caused by oversampling. In this work, Bussgang decomposition is applied to deal with the coarse quantization, and a Markov chain is developed to characterize the banded structure of the oversampling filter. An approximate message-passing based algorithm is proposed for the estimation of the cascaded channels. Simulation results demonstrate that our proposed 1-bit systems with oversampling can approach the 2-bit systems in terms of the mean square error performance while the former consumes much less power at the receiver. Table and Figures | Reference | Related Articles | Metrics

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Truly Grant-Free Technologies and Protocols for 6G MA Yihua, YUAN Zhifeng, LI Weimin, LI Zhigang ZTE Communications    2021, 19 (4): 105-110.   DOI: 10.12142/ZTECOM.202104012 Abstract （53）   HTML （3）    PDF （808KB）（144）       Knowledge map    Save The further integration of telecommunications and industry has been considerable and is expected to bring significant benefits to society and economics in 6G. It also forms some evolution trends for next-generation communication systems, including further rises in machine-type communications (MTC), uplink-dominated systems, and decentralized structures. However, the existing access protocols are not friendly to these trends. This paper analyzes the problems of existing access protocols and provides novel access technologies to solve them. These technologies include contention-based non-orthogonal multiple access (NOMA), data features, enhanced pilot design and successive interference cancellation (SIC) of diversity. With these key enablers, truly grant-free access can be realized, and some potential modifications of protocols are then analyzed. Finally, this paper uses massive and critical scenarios in digital transformations to show the great necessity of introducing novel access technologies into future communication protocols. Table and Figures | Reference | Related Articles | Metrics

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Multi-Task Learning with Dynamic Splitting for Open-Set Wireless Signal Recognition XU Yujie, ZHAO Qingchen, XU Xiaodong, QIN Xiaowei, CHEN Jianqiang ZTE Communications    2022, 20 (S1): 44-56.   DOI: 10.12142/ZTECOM.2022S1007 Abstract （87）   HTML （6）    PDF （1899KB）（139）       Knowledge map    Save Open-set recognition (OSR) is a realistic problem in wireless signal recognition, which means that during the inference phase there may appear unknown classes not seen in the training phase. The method of intra-class splitting (ICS) that splits samples of known classes to imitate unknown classes has achieved great performance. However, this approach relies too much on the predefined splitting ratio and may face huge performance degradation in new environment. In this paper, we train a multi-task learning (MTL) network based on the characteristics of wireless signals to improve the performance in new scenes. Besides, we provide a dynamic method to decide the splitting ratio per class to get more precise outer samples. To be specific, we make perturbations to the sample from the center of one class toward its adversarial direction and the change point of confidence scores during this process is used as the splitting threshold. We conduct several experiments on one wireless signal dataset collected at 2.4 GHz ISM band by LimeSDR and one open modulation recognition dataset, and the analytical results demonstrate the effectiveness of the proposed method. Table and Figures | Reference | Related Articles | Metrics

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General Introduction of Non-Terrestrial Networks for New Radio HAN Jiren, GAO Yin ZTE Communications    2022, 20 (S1): 72-78.   DOI: 10.12142/ZTECOM.2022S1010 Abstract （171）   HTML （14）    PDF （1266KB）（136）       Knowledge map    Save In the new radio (NR) access technology, non-terrestrial networks (NTN) are introduced to meet the requirement of anywhere and anytime connections from the world market. With the introduction of NTN, the NR system is able to offer the wide-area coverage and ensure the service availability for users. In this paper, the general aspects of NTN are introduced, including the NTN architecture overview, the impact of NTN on next-generation radio access network (NG-RAN) interface functions, mobility scenarios and other NTN related issues. The current progress in 3GPP Release 17 is also provided. Table and Figures | Reference | 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 （69）   HTML （7）    PDF （537KB）（136）       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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Derivative-Based Envelope Design Technique for Wideband Envelope Tracking Power Amplifier with Digital Predistortion YI Xueya, CHEN Jixin, CHEN Peng, NING Dongfang, YU Chao ZTE Communications    2022, 20 (S1): 22-26.   DOI: 10.12142/ZTECOM.2022S1004 Abstract （119）   HTML （14）    PDF （878KB）（135）       Knowledge map    Save A novel envelope design for an envelope tracking (ET) power amplifier (PA) based on its derivatives is proposed, which can trade well off between bandwidth reduction and tracking accuracy. This paper theoretically analyzes how to choose an envelope design that can track the original envelope closely and reduce its bandwidth, and then demonstrates an example to validate this idea. The generalized memory polynomial (GMP) model is applied to compensate for the nonlinearity of ET PA with the proposed envelope design. Experiments are carried out on an ET system that is operated with the center frequency of 3.5 GHz and excited by a 20 MHz LTE signal, which show that the proposed envelope design can make a good trade-off between envelope bandwidth and efficiency, and satisfactory linearization performance can be realized. Table and Figures | Reference | Related Articles | Metrics

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IRS‑Enabled Spectrum Sharing: Interference Modeling, Channel Estimation and Robust Passive Beamforming GUAN Xinrong, WU Qingqing ZTE Communications    2022, 20 (1): 28-35.   DOI: 10.12142/ZTECOM.202201005 Abstract （77）   HTML （6）    PDF （1134KB）（134）       Knowledge map    Save Intelligent reflecting surface (IRS), with its unique capability of smartly reconfiguring wireless channels, provides a new solution to improving spectrum efficiency, reducing energy consumption and saving deployment/hardware cost for future wireless networks. In this paper, IRS-enabled spectrum sharing is investigated, from the perspectives of interference modeling, efficient channel estimation and robust passive beamforming design. Specifically, we first characterize the interference in a spectrum sharing system consisting of a single primary user (PU) pair and a single secondary user (SU) pair, and extend it to the large-scale network by leveraging the Poisson point process (PPP). Then, we propose an efficient channel estimation framework based on decoupling the cascaded IRS channels. Moreover, the tradeoff between spectrum efficiency and energy efficiency is derived from the view of channel estimation accuracy. Finally, we discuss the robust passive beamforming design in presence of imperfect channel estimation and nonideal/discrete phase shifts. It is hoped that this paper provides useful guidance for unlocking the full potential of IRS for achieving efficient spectrum sharing for future wireless networks. Table and Figures | Reference | Related Articles | Metrics

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An Improved Parasitic Parameter Extraction Method for InP HEMT DUAN Lanyan, LU Hongliang, QI Junjun, ZHANG Yuming, ZHANG Yimen ZTE Communications    2022, 20 (S1): 1-6.   DOI: 10.12142/ZTECOM.2022S1001 Abstract （95）   HTML （183）    PDF （2023KB）（134）       Knowledge map    Save An improved parasitic parameter extraction method for InP high electron mobility transistor (HEMT) is presented. Parasitic parameter extraction is the first step of model parameter extraction and its accuracy has a great impact on the subsequent internal parameter extraction. It is necessary to accurately determine and effectively eliminate the parasitic effect, so as to avoid the error propagation to the internal circuit parameters. In this paper, in order to obtain higher accuracy of parasitic parameters, parasitic parameters are extracted based on traditional analytical method and optimization algorithm to obtain the best parasitic parameters. The validity of the proposed parasitic parameter extraction method is verified with excellent agreement between the measured and modeled S-parameters up to 40 GHz for InP HEMT. In 0.1–40 GHz InP HEMT, the average relative error of the optimization algorithm is about 9% higher than that of the analysis method, which verifies the validity of the parasitic parameter extraction method. The extraction of parasitic parameters not only provides a foundation for the high-precision extraction of small signal intrinsic parameters of HEMT devices, but also lays a foundation for the high-precision extraction of equivalent circuit model parameters of large signal and noise signals of HEMT devices. Table and Figures | Reference | Related Articles | Metrics

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Special Topic on Federated Learning over Wireless Networks CUI Shuguang, YIN Changchuan, ZHU Guangxu ZTE Communications    2023, 21 (1): 1-2.   DOI: 10.12142/ZTECOM.202301001 Abstract （82）   HTML （14）    PDF （506KB）（134）       Knowledge map    Save Reference | Related Articles | Metrics

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RIS: Spatial‑Wideband Effect Analysis and Off‑Grid Channel Estimation JIAN Mengnan, ZHANG Nan, CHEN Yijian ZTE Communications    2022, 20 (1): 57-62.   DOI: 10.12142/ZTECOM.202201008 Abstract （85）   HTML （6）    PDF （1069KB）（132）       Knowledge map    Save As a critical candidate technology for 5G-advanced and 6G, reconfigurable intelligent surfaces (RIS) have received extensive attention from academia and industry. RIS has the promising features of passiveness, reconfigurable ability, and low cost. RIS channel estimation faces the challenges of high matrix dimension, passive estimation, and spatial-wideband effect. In this article, we analyze the impact of the spatial-wideband effect on the RIS channel to account for the propagation delay across RIS elements and estimate sparse channel parameters such as angle and gain through a super-resolution compressive sensing (CS) algorithm. The simulation results explore the influence of the spatial-wideband effect on the RIS channel and verify the effectiveness of the proposed algorithm. Table and Figures | Reference | Related Articles | Metrics

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Adaptive Retransmission Design for Wireless Federated Edge Learning XU Xinyi, LIU Shengli, YU Guanding ZTE Communications    2023, 21 (1): 3-14.   DOI: 10.12142/ZTECOM.202301002 Abstract （51）   HTML （6）    PDF （1432KB）（118）       Knowledge map    Save As a popular distributed machine learning framework, wireless federated edge learning (FEEL) can keep original data local, while uploading model training updates to protect privacy and prevent data silos. However, since wireless channels are usually unreliable, there is no guarantee that the model updates uploaded by local devices are correct, thus greatly degrading the performance of the wireless FEEL. Conventional retransmission schemes designed for wireless systems generally aim to maximize the system throughput or minimize the packet error rate, which is not suitable for the FEEL system. A novel retransmission scheme is proposed for the FEEL system to make a tradeoff between model training accuracy and retransmission latency. In the proposed scheme, a retransmission device selection criterion is first designed based on the channel condition, the number of local data, and the importance of model updates. In addition, we design the air interface signaling under this retransmission scheme to facilitate the implementation of the proposed scheme in practical scenarios. Finally, the effectiveness of the proposed retransmission scheme is validated through simulation experiments. Table and Figures | Reference | Related Articles | Metrics

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AI-Based Optimization of Handover Strategy in Non-Terrestrial Networks ZHANG Chenchen, ZHANG Nan, CAO Wei, TIAN Kaibo, YANG Zhen ZTE Communications    2021, 19 (4): 98-104.   DOI: 10.12142/ZTECOM.202104011 Abstract （45）   HTML （3）    PDF （674KB）（117）       Knowledge map    Save Complicated radio resource management, e.g., handover condition, will trouble the user in non-terrestrial networks due to the impact of high mobility and hierarchical layouts which co-exist with terrestrial networks or various platforms at different altitudes. It is necessary to optimize the handover strategy to reduce the signaling overhead and improve the service continuity. In this paper, a new handover strategy is proposed based on the convolutional neural network. Firstly, the handover process is modeled as a directed graph. Suppose a user knows its future signal strength, then he/she can search for the best handover strategy based on the graph. Secondly, a convolutional neural network is used to extract the underlying regularity of the best handover strategies of different users, based on which any user can make near-optimal handover decisions according to its historical signal strength. Numerical simulation shows that the proposed handover strategy can efficiently reduce the handover number while ensuring the signal strength. 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）（114）       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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Metric Learning for Semantic‑Based Clothes Retrieval YANG Bo, GUO Caili, LI Zheng ZTE Communications    2022, 20 (1): 76-82.   DOI: 10.12142/ZTECOM.202201010 Abstract （70）   HTML （6）    PDF （1951KB）（113）       Knowledge map    Save Existing clothes retrieval methods mostly adopt binary supervision in metric learning. For each iteration, only the clothes belonging to the same instance are positive samples, and all other clothes are “indistinguishable” negative samples, which causes the following problem. The relevance between the query and candidates is only treated as relevant or irrelevant, which makes the model difficult to learn the continuous semantic similarities between clothes. Clothes that do not belong to the same instance are completely considered irrelevant and are uniformly pushed away from the query by an equal margin in the embedding space, which is not consistent with the ideal retrieval results. Motivated by this, we propose a novel method called semantic-based clothes retrieval (SCR). In SCR, we measure the semantic similarities between clothes and design a new adaptive loss based on these similarities. The margin in the proposed adaptive loss can vary with different semantic similarities between the anchor and negative samples. In this way, more coherent embedding space can be learned, where candidates with higher semantic similarities are mapped closer to the query than those with lower ones. We use Recall@K and normalized Discounted Cumulative Gain (nDCG) as evaluation metrics to conduct experiments on the DeepFashion dataset and have achieved better performance. Table and Figures | Reference | 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）（112）       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