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Separate Source Channel Coding Is Still What You Need: An LLM-Based Rethinking REN Tianqi, LI Rongpeng, ZHAO Mingmin, CHEN Xianfu, LIU Guangyi, YANG Yang, ZHAO Zhifeng, ZHANG Honggang ZTE Communications    2025, 23 (1): 30-44.   DOI: 10.12142/ZTECOM.202501005 Abstract （319）   HTML （201）    PDF （1269KB）（336）       Knowledge map    Save Along with the proliferating research interest in semantic communication (SemCom), joint source channel coding (JSCC) has dominated the attention due to the widely assumed existence in efficiently delivering information semantics. Nevertheless, this paper challenges the conventional JSCC paradigm and advocates for adopting separate source channel coding (SSCC) to enjoy a more underlying degree of freedom for optimization. We demonstrate that SSCC, after leveraging the strengths of the Large Language Model (LLM) for source coding and Error Correction Code Transformer (ECCT) complemented for channel coding, offers superior performance over JSCC. Our proposed framework also effectively highlights the compatibility challenges between SemCom approaches and digital communication systems, particularly concerning the resource costs associated with the transmission of high-precision floating point numbers. Through comprehensive evaluations, we establish that assisted by LLM-based compression and ECCT-enhanced error correction, SSCC remains a viable and effective solution for modern communication systems. In other words, separate source channel coding is still what we need. Table and Figures | Reference | Related Articles | Metrics

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Doppler Rate Estimation for OTFS via Large-Scale Antenna Array SHAN Yaru, WANG Fanggang, HAO Yaxing, HUA Jian, XIN Yu ZTE Communications    2025, 23 (1): 115-122.   DOI: 10.12142/ZTECOM.202501015 Abstract （300）   HTML （12）    PDF （1355KB）（115）       Knowledge map    Save Orthogonal time frequency space (OTFS) can resist the Doppler effect and guarantee reliable communication in high-speed scenarios. However, the Doppler rate induced by the relative acceleration between the transmitter and receiver degrades the performance of the OTFS. So far, the impact of the Doppler rate on OTFS systems has not been addressed. In this paper, we first introduce the Doppler rate in the OTFS system and derive the delay-Doppler domain input-output relation. In addition, the impact of the Doppler rate on the effective delay-Doppler domain channel is characterized by utilizing the first mean value theorem for definite integrals to avoid complicated integrals. To mitigate the effect of the Doppler rate, a large-scale antenna array is arranged at the receiver to separate each path of the multi-path channel through a high-resolution spatial matched filter beamformer. Next, the Doppler rate estimation scheme for an arbitrary order Doppler rate is proposed based on the successive interference cancellation pattern and the maximization of the spectrum of the ratio of high-order moments between the received samples in the identified branch and the transmitted samples. Finally, the estimation accuracy of the Doppler rate and the error performance of the proposed transceiver are validated by the numerical results. Table and Figures | Reference | Related Articles | Metrics

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Endogenous Security Through AI-Driven Physical-Layer Authentication for Future 6G Networks MENG Rui, FAN Dayu, XU Xiaodong, LYU Suyu, TAO Xiaofeng ZTE Communications    2025, 23 (1): 18-29.   DOI: 10.12142/ZTECOM.202501004 Abstract （285）   HTML （199）    PDF （949KB）（236）       Knowledge map    Save To ensure the access security of 6G, physical-layer authentication (PLA) leverages the randomness and space-time-frequency uniqueness of the channel to provide unique identity signatures for transmitters. Furthermore, the introduction of artificial intelligence (AI) facilitates the learning of the distribution characteristics of channel fingerprints, effectively addressing the uncertainties and unknown dynamic challenges in wireless link modeling. This paper reviews representative AI-enabled PLA schemes and proposes a graph neural network (GNN)-based PLA approach in response to the challenges existing methods face in identifying mobile users. Simulation results demonstrate that the proposed method outperforms six baseline schemes in terms of authentication accuracy. Furthermore, this paper outlines the future development directions of PLA. Table and Figures | Reference | Related Articles | Metrics

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A Basis Function Generation Based Digital Predistortion Concurrent Neural Network Model for RF Power Amplifiers SHAO Jianfeng, HONG Xi, WANG Wenjie, LIN Zeyu, LI Yunhua ZTE Communications    2025, 23 (1): 71-77.   DOI: 10.12142/ZTECOM.202501009 Abstract （281）   HTML （2）    PDF （749KB）（111）       Knowledge map    Save This paper proposes a concurrent neural network model to mitigate non-linear distortion in power amplifiers using a basis function generation approach. The model is designed using polynomial expansion and comprises a feedforward neural network (FNN) and a convolutional neural network (CNN). The proposed model takes the basic elements that form the bases as input, defined by the generalized memory polynomial (GMP) and dynamic deviation reduction (DDR) models. The FNN generates the basis function and its output represents the basis values, while the CNN generates weights for the corresponding bases. Through the concurrent training of FNN and CNN, the hidden layer coefficients are updated, and the complex multiplication of their outputs yields the trained in-phase/quadrature (I/Q) signals. The proposed model was trained and tested using 300 MHz and 400 MHz broadband data in an orthogonal frequency division multiplexing (OFDM) communication system. The results show that the model achieves an adjacent channel power ratio (ACPR) of less than –48 dB within a 100 MHz integral bandwidth for both the training and test datasets. Table and Figures | Reference | Related Articles | Metrics

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Efficient Spatio-Temporal Predictive Learning for Massive MIMO CSI Prediction CHENG Jiaming, CHEN Wei, LI Lun, AI Bo ZTE Communications    2025, 23 (1): 3-10.   DOI: 10.12142/ZTECOM.202501002 Abstract （267）   HTML （211）    PDF （1023KB）（344）       Knowledge map    Save Accurate channel state information (CSI) is crucial for 6G wireless communication systems to accommodate the growing demands of mobile broadband services. In massive multiple-input multiple-output (MIMO) systems, traditional CSI feedback approaches face challenges such as performance degradation due to feedback delay and channel aging caused by user mobility. To address these issues, we propose a novel spatio-temporal predictive network (STPNet) that jointly integrates CSI feedback and prediction modules. STPNet employs stacked Inception modules to learn the spatial correlation and temporal evolution of CSI, which captures both the local and the global spatio-temporal features. In addition, the signal-to-noise ratio (SNR) adaptive module is designed to adapt flexibly to diverse feedback channel conditions. Simulation results demonstrate that STPNet outperforms existing channel prediction methods under various channel conditions. Table and Figures | Reference | Related Articles | Metrics

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Efficient PSS Detection Algorithm Aided by CNN LI Lanlan ZTE Communications    2025, 23 (1): 63-70.   DOI: 10.12142/ZTECOM.202501008 Abstract （266）   HTML （3）    PDF （678KB）（387）       Knowledge map    Save In a 5G mobile communication system, cell search is the initial step in establishing downlink synchronization between user equipment (UE) and base stations (BS). Primary synchronization signal (PSS) detection is a crucial part of this process, and enhancing PSS detection speed can reduce communication latency and improve overall quality. This paper proposes a fast PSS detection algorithm based on the correlation characteristics of PSS time-domain superposition signals. Conducting PSS signal correlation within a smaller range can reduce computational complexity and accelerates communication speed. Additionally, frequency offset can impact the accuracy of calculations during the PSS detection process. To address this issue, we propose applying convolutional neural networks (CNN) for frequency offset estimation of synchronization signals. By compensating for the frequency of related signals, the accuracy of PSS detection is improved. Finally, the analysis and simulation results demonstrate the effectiveness of the proposed approach. Table and Figures | Reference | Related Articles | Metrics

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Liquid Neural Networks: Next-Generation AI for Telecom from First Principles ZHU Fenghao, WANG Xinquan, ZHU Chen, HUANG Chongwen ZTE Communications    2025, 23 (2): 76-84.   DOI: 10.12142/ZTECOM.202502008 Abstract （255）   HTML （15）    PDF （1875KB）（122）       Knowledge map    Save Recently, a novel type of neural networks, known as liquid neural networks (LNNs), has been designed from first principles to address robustness and interpretability challenges facing artificial intelligence (AI) solutions. The potential of LNNs in telecommunications is explored in this paper. First, we illustrate the mechanisms of LNNs and highlight their unique advantages over traditional networks. Then we explore the opportunities that LNNs bring to future wireless networks. Furthermore, we discuss the challenges and design directions for the implementation of LNNs. Finally, we summarize the performance of LNNs in two case studies. Table and Figures | Reference | Related Articles | Metrics

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Special Topic on Native Intelligence at the Physical Layer ZTE Communications    2025, 23 (1): 1-2.   DOI: 10.12142/ZTECOM.202501001 Abstract （252）   HTML （6）    PDF （351KB）（128）       Knowledge map    Save Reference | Related Articles | Metrics

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Exploration of NWDAF Development Architecture for 6G AI-Native Networks HE Shiwen, PENG Shilin, DONG Haolei, WANG Liangpeng, AN Zhenyu ZTE Communications    2025, 23 (1): 45-52.   DOI: 10.12142/ZTECOM.202501006 Abstract （245）   HTML （7）    PDF （938KB）（197）       Knowledge map    Save Artificial intelligence (AI)-native communication is considered one of the key technologies for the development of 6G mobile communication networks. This paper investigates the architecture for developing the network data analytics function (NWDAF) in 6G AI-native networks. The architecture integrates two key components: data collection and management, and model training and management. It achieves real-time data collection and management, establishing a complete workflow encompassing AI model training, deployment, and intelligent decision-making. The architecture workflow is evaluated through a vertical scaling use case by constructing an AI-native network testbed on Kubernetes. Within this proposed NWDAF, several machine learning (ML) models are trained to make vertical scaling decisions for user plane function (UPF) instances based on data collected from various network functions (NFs). These decisions are executed through the Kubernetes API, which dynamically allocates appropriate resources to UPF instances. The experimental results show that all implemented models demonstrate satisfactory predictive capabilities. Moreover, compared with the threshold-based method in Kubernetes, all models show a significant advantage in response time. This study not only introduces a novel AI-native NWDAF architecture but also demonstrates the potential of AI models to significantly improve network management and resource scaling in 6G networks. Table and Figures | Reference | Related Articles | Metrics

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From Function Calls to MCPs for Securing AI Agent Systems: Architecture, Challenges and Countermeasures WANG Wei, LI Shaofeng, DONG Tian, MENG Yan, ZHU Haojin ZTE Communications    2025, 23 (3): 27-37.   DOI: 10.12142/ZTECOM.202503004 Abstract （222）   HTML （10）    PDF （1290KB）（138）       Knowledge map    Save With the widespread deployment of large language models (LLMs) in complex and multimodal scenarios, there is a growing demand for secure and standardized integration of external tools and data sources. The Model Context Protocol (MCP), proposed by Anthropic in late 2024, has emerged as a promising framework. Designed to standardize the interaction between LLMs and their external environments, it serves as a “USB-C interface for AI”. While MCP has been rapidly adopted in the industry, systematic academic studies on its security implications remain scarce. This paper presents a comprehensive review of MCP from a security perspective. We begin by analyzing the architecture and workflow of MCP and identify potential security vulnerabilities across key stages including input processing, decision-making, client invocation, server response, and response generation. We then categorize and assess existing defense mechanisms. In addition, we design a real-world attack experiment to demonstrate the feasibility of tool description injection within an actual MCP environment. Based on the experimental results, we further highlight underexplored threat surfaces and propose future directions for securing AI agent systems powered by MCP. This paper aims to provide a structured reference framework for researchers and developers seeking to balance functionality and security in MCP-based systems. Table and Figures | Reference | Related Articles | Metrics

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Poison-Only and Targeted Backdoor Attack Against Visual Object Tracking GU Wei, SHAO Shuo, ZHOU Lingtao, QIN Zhan, REN Kui ZTE Communications    2025, 23 (3): 3-14.   DOI: 10.12142/ZTECOM.202503002 Abstract （220）   HTML （5）    PDF （1597KB）（126）       Knowledge map    Save Visual object tracking (VOT), aiming to track a target object in a continuous video, is a fundamental and critical task in computer vision. However, the reliance on third-party resources (e.g., dataset) for training poses concealed threats to the security of VOT models. In this paper, we reveal that VOT models are vulnerable to a poison-only and targeted backdoor attack, where the adversary can achieve arbitrary tracking predictions by manipulating only part of the training data. Specifically, we first define and formulate three different variants of the targeted attacks: size-manipulation, trajectory-manipulation, and hybrid attacks. To implement these, we introduce Random Video Poisoning (RVP), a novel poison-only strategy that exploits temporal correlations within video data by poisoning entire video sequences. Extensive experiments demonstrate that RVP effectively injects controllable backdoors, enabling precise manipulation of tracking behavior upon trigger activation, while maintaining high performance on benign data, thus ensuring stealth. Our findings not only expose significant vulnerabilities but also highlight that the underlying principles could be adapted for beneficial uses, such as dataset watermarking for copyright protection. Table and Figures | Reference | Related Articles | Metrics

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RIS Enabled Simultaneous Transmission and Key Generation with PPO: Exploring Security Boundary of RIS Phase Shift FAN Kaiqing, YAO Yuze, GAO Ning, LI Xiao, JIN Shi ZTE Communications    2025, 23 (1): 11-17.   DOI: 10.12142/ZTECOM.202501003 Abstract （217）   HTML （197）    PDF （622KB）（135）       Knowledge map    Save Due to the broadcast nature of wireless channels and the development of quantum computers, the confidentiality of wireless communication is seriously threatened. In this paper, we propose an integrated communications and security (ICAS) design to enhance communication security using reconfigurable intelligent surfaces (RIS), in which the physical layer key generation (PLKG) rate and the data transmission rate are jointly considered. Specifically, to deal with the threat of eavesdropping attackers, we focus on studying the simultaneous transmission and key generation (STAG) by configuring the RIS phase shift. Firstly, we derive the key generation rate of the RIS assisted PLKG and formulate the optimization problem. Then, in light of the dynamic wireless environments, the optimization problem is modeled as a finite Markov decision process. We put forward a policy gradient-based proximal policy optimization (PPO) algorithm to optimize the continuous phase shift of the RIS, which improves the convergence stability and explores the security boundary of the RIS phase shift for STAG. The simulation results demonstrate that the proposed algorithm outperforms the benchmark method in convergence stability and system performance. By reasonably allocating the weight factors for the data transmission rate and the key generation rate, “one-time pad” communication can be achieved. The proposed method has about 90% performance improvement for “one-time pad” communication compared with the benchmark methods. Table and Figures | Reference | Related Articles | Metrics

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Measurement and Analysis of Radar-Cross-Section of UAV at 21–26 GHz Frequency Band AN Hao, LIU Ting, HE Danping, MA Yihua, DOU Jianwu ZTE Communications    2025, 23 (1): 107-114.   DOI: 10.12142/ZTECOM.202501014 Abstract （210）   HTML （5）    PDF （1717KB）（126）       Knowledge map    Save With the emergence of the 6G technology, integrated sensing and communication (ISAC) has become a hot-spot vertical application. The low-altitude scenario is considered to be a significant use case of the ISAC. However, the existing channel model is hard to meet the demands of the sensing function. The radar-cross-section (RCS) is a critical feature for the sensing part, while accurate RCS data for the typical frequency band of ISAC are still lacking. Therefore, this paper conducts measurements and analysis of the RCS data of the unmanned aerial vehicles (UAVs) under multiple poses and angles in real flying conditions. The echo from a UAV is acquired in an anechoic chamber, and the RCS values are calculated. The results of different flying attitudes are analyzed, providing RCS features for the ISAC applications. Table and Figures | Reference | Related Articles | Metrics

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VOTI: Jailbreaking Vision-Language Models via Visual Obfuscation and Task Induction ZHU Yifan, CHU Zhixuan, REN Kui ZTE Communications    2025, 23 (3): 15-26.   DOI: 10.12142/ZTECOM.202503003 Abstract （210）   HTML （4）    PDF （6551KB）（113）       Knowledge map    Save In recent years, large vision-language models (VLMs) have achieved significant breakthroughs in cross-modal understanding and generation. However, the safety issues arising from their multimodal interactions become prominent. VLMs are vulnerable to jailbreak attacks, where attackers craft carefully designed prompts to bypass safety mechanisms, leading them to generate harmful content. To address this, we investigate the alignment between visual inputs and task execution, uncovering locality defects and attention biases in VLMs. Based on these findings, we propose VOTI, a novel jailbreak framework leveraging visual obfuscation and task induction. VOTI subtly embeds malicious keywords within neutral image layouts to evade detection, and breaks down harmful queries into a sequence of subtasks. This approach disperses malicious intent across modalities, exploiting VLMs’ over-reliance on local visual cues and their fragility in multi-step reasoning to bypass global safety mechanisms. Implemented as an automated framework, VOTI integrates large language models as red-team assistants to generate and iteratively optimize jailbreak strategies. Extensive experiments across seven mainstream VLMs demonstrate VOTI’s effectiveness, achieving a 73.46% attack success rate on GPT-4o-mini. These results reveal critical vulnerabilities in VLMs, highlighting the urgent need for improving robust defenses and multimodal alignment. Table and Figures | Reference | Supplementary Material | Related Articles | Metrics

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Dataset Copyright Auditing for Large Models: Fundamentals, Open Problems, and Future Directions DU Linkang, SU Zhou, YU Xinyi ZTE Communications    2025, 23 (3): 38-47.   DOI: 10.12142/ZTECOM.202503005 Abstract （200）   HTML （3）    PDF （511KB）（117）       Knowledge map    Save The unprecedented scale of large models, such as large language models (LLMs) and text-to-image diffusion models, has raised critical concerns about the unauthorized use of copyrighted data during model training. These concerns have spurred a growing demand for dataset copyright auditing techniques, which aim to detect and verify potential infringements in the training data of commercial AI systems. This paper presents a survey of existing auditing solutions, categorizing them across key dimensions: data modality, model training stage, data overlap scenarios, and model access levels. We highlight major trends, including the prevalence of black-box auditing methods and the emphasis on fine-tuning rather than pre-training. Through an in-depth analysis of 12 representative works, we extract four key observations that reveal the limitations of current methods. Furthermore, we identify three open challenges and propose future directions for robust, multimodal, and scalable auditing solutions. Our findings underscore the urgent need to establish standardized benchmarks and develop auditing frameworks that are resilient to low watermark densities and applicable in diverse deployment settings. Table and Figures | Reference | Related Articles | Metrics

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VFabric: A Digital Twin Emulator for Core Switching Equipment WANG Qianglin, ZHANG Xiaoning, YANG Yi, FAN Chenyu, YUE Yangyang, WU Wei, DUAN Wei ZTE Communications    2025, 23 (1): 90-100.   DOI: 10.12142/ZTECOM.202501012 Abstract （196）   HTML （2）    PDF （938KB）（275）       Knowledge map    Save The proliferation of heterogeneous networks, such as the Internet of Things (IoT), unmanned aerial vehicle (UAV) networks, and edge networks, has increased the complexity of network operation and administration, driving the emergence of digital twin networks (DTNs) that create digital-physical network mappings. While DTNs enable performance analysis through emulation testbeds, current research focuses on network-level systems, neglecting equipment-level emulation of critical components like core switches and routers. To address this issue, we propose vFabric (short for virtual switch), a digital twin emulator for high-capacity core switching equipment. This solution implements virtual switching and network processor (NP) chip models through specialized processes, deployable on single or distributed servers via socket communication. The vFabric emulator can realize the accurate emulation for the core switching equipment with 720 ports and 100 Gbit/s per port on the largest scale. To our knowledge, this represents the first digital twin emulation framework specifically designed for large-capacity core switching equipment in communication networks. Table and Figures | Reference | Related Articles | Metrics

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A Wide Passband Frequency Selective Surface with Angular Stability TANG Xingyang, SUI Jia, FU Jiahui, YANG Kaiwen, ZHAO Zhipeng ZTE Communications    2025, 23 (1): 78-84.   DOI: 10.12142/ZTECOM.202501010 Abstract （195）   HTML （4）    PDF （1184KB）（103）       Knowledge map    Save A wide passband frequency selective surface (FSS) is proposed using a five-layer stacked structure. The proposed structure applies four layers of dielectric plates and five layers of metal patches to provide a passband and exhibits more stable frequency responses and lower insertion loss under wide-angle oblique incidence compared with the typical three-layer metal-dielectric structure. According to the simulation results, the proposed FSS can achieve a passband range of 1.7–2.7 GHz with an insertion loss of less than 0.5 dB and a relative bandwidth of 44.1%, and it can preserve stable transmission characteristics with the incident angle ranging from 0° to 45°. Table and Figures | Reference | Related Articles | Metrics

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A Machine Learning-Based Channel Data Enhancement Platform for Digital Twin Channels AI Bo, ZHANG Yuxin, YANG Mi, HE Ruisi, GUO Rongge ZTE Communications    2025, 23 (2): 20-30.   DOI: 10.12142/ZTECOM.202502004 Abstract （195）   HTML （12）    PDF （2951KB）（97）       Knowledge map    Save Reliable channel data helps characterize the limitations and performance boundaries of communication technologies accurately. However, channel measurement is highly costly and time-consuming, and taking actual measurement as the only channel data source may reduce efficiency because of the constraints of high testing difficulty and limited data volume. Although existing standard channel models can generate channel data, their authenticity and diversity cannot be guaranteed. To address this, we use deep learning methods to learn the attributes of limited measured data and propose a generative model based on generative adversarial networks to rapidly synthesize data. A software simulation platform is also established to verify that the proposed model can generate data that are statistically similar to the measured data while maintaining necessary randomness. The proposed algorithm and platform can be applied to channel data enhancement and serve channel modeling and algorithm evaluation applications with urgent needs for data. Table and Figures | Reference | Related Articles | Metrics

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Channel Knowledge Maps for 6G Wireless Networks: Construction, Applications, and Future Challenges LIU Xingchen, SUN Shu, TAO Meixia, KAUSHIK Aryan, YAN Hangsong ZTE Communications    2025, 23 (2): 46-59.   DOI: 10.12142/ZTECOM.202502006 Abstract （195）   HTML （6）    PDF （1292KB）（375）       Knowledge map    Save The advent of 6G wireless networks promises unprecedented connectivity, supporting ultra-high data rates, low latency, and massive device connectivity. However, these ambitious goals introduce significant challenges, particularly in channel estimation due to complex and dynamic propagation environments. This paper explores the concept of channel knowledge maps (CKMs) as a solution to these challenges. CKMs enable environment-aware communications by providing location-specific channel information, reducing reliance on real-time pilot measurements. We categorize CKM construction techniques into measurement-based, model-based, and hybrid methods, and examine their key applications in integrated sensing and communication (ISAC) systems, beamforming, trajectory optimization of unmanned aerial vehicles (UAVs), base station (BS) placement, and resource allocation. Furthermore, we discuss open challenges and propose future research directions to enhance the robustness, accuracy, and scalability of CKM-based systems in the evolving 6G landscape. Table and Figures | Reference | Related Articles | Metrics

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Analysis of Feasible Solutions for Railway 5G Network Security Assessment XU Hang, SUN Bin, DING Jianwen, WANG Wei ZTE Communications    2025, 23 (3): 59-70.   DOI: 10.12142/ZTECOM.202503007 Abstract （192）   HTML （1）    PDF （502KB）（89）       Knowledge map    Save The Fifth Generation of Mobile Communications for Railways (5G-R) brings significant opportunities for the rail industry. However, alongside the potential and benefits of the railway 5G network are complex security challenges. Ensuring the security and reliability of railway 5G networks is therefore essential. This paper presents a detailed examination of security assessment techniques for railway 5G networks, focusing on addressing the unique security challenges in this field. In this paper, various security requirements in railway 5G networks are analyzed, and specific processes and methods for conducting comprehensive security risk assessments are presented. This study provides a framework for securing railway 5G network development and ensuring its long-term sustainability. Table and Figures | Reference | Related Articles | Metrics

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Dual-Polarized 2D Beam-Scanning Antenna Based on Reconfigurable Reflective Elements LIU Zhipeng, LI Kexin, CAI Yuanming, LIU Feng, GUO Jiayin ZTE Communications    2025, 23 (1): 85-89.   DOI: 10.12142/ZTECOM.202501011 Abstract （192）   HTML （3）    PDF （1213KB）（129）       Knowledge map    Save In this paper, a dual-polarized antenna operating at 3.5 GHz is presented with 2D beam-scanning performance. The steerable beam is realized based on a 2×2 active reflective metasurface. The active metasurface is composed of folded annular rings and cross dipoles embedded with voltage-controlled varactor diodes. By tuning the capacitance values of the varactors, the reflective phase of the metasurface is reconfigured to tilt the main beam. To verify the scanning performance, a prototype is fabricated and measured. At 3.5 GHz, the measured scanning ranges are from -25° to 29° and -27° to 29° in the XOZ and YOZ planes, respectively. Table and Figures | Reference | Related Articles | Metrics

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StegoAgent: A Generative Steganography Framework Based on GUI Agents SHEN Qiuhong, YANG Zijin, JIANG Jun, ZHANG Weiming, CHEN Kejiang ZTE Communications    2025, 23 (3): 48-58.   DOI: 10.12142/ZTECOM.202503006 Abstract （190）   HTML （2）    PDF （1144KB）（95）       Knowledge map    Save Steganography is a technology that discreetly embeds secret information into the redundant space of a carrier, enabling covert communication. As generative models continue to advance, steganography has evolved from traditional modification-based methods to generative steganography, which includes generative linguistic and image based forms. However, while large model agents are rapidly emerging, no method has exploited the stable redundant space in their action processes. Inspired by this insightful observation, we propose a steganographic method leveraging large model agents, employing their actions to conceal secret messages. In this paper, we introduce StegoAgent, a generative steganography framework based on graphical user interface (GUI) agents, which effectively demonstrates the remarkable potential and effectiveness of large model agent-based steganographic methods. Table and Figures | Reference | Related Articles | Metrics

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Special Topic on Security of Large Models ZTE Communications    2025, 23 (3): 1-2.   DOI: 10.12142/ZTECOM.202503001 Abstract （189）   HTML （3）    PDF （343KB）（105）       Knowledge map    Save Reference | Related Articles | Metrics

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Real-Time 7-Core SDM Transmission System Using Commercial 400 Gbit/s OTN Transceivers and Network Management System CUI Jian, GU Ninglun, CHANG Cheng, SHI Hu, YAN Baoluo ZTE Communications    2025, 23 (3): 81-88.   DOI: 10.12142/ZTECOM.202503009 Abstract （188）   HTML （2）    PDF （3531KB）（84）       Knowledge map    Save Space-division multiplexing (SDM) utilizing uncoupled multi-core fibers (MCF) is considered a promising candidate for next-generation high-speed optical transmission systems due to its huge capacity and low inter-core crosstalk. In this paper, we demonstrate a real-time high-speed SDM transmission system over a field-deployed 7-core MCF cable using commercial 400 Gbit/s backbone optical transport network (OTN) transceivers and a network management system. The transceivers employ a high noise-tolerant quadrature phase shift keying (QPSK) modulation format with a 130 Gbaud rate, enabled by optoelectronic multi-chip module (OE-MCM) packaging. The network management system can effectively manage and monitor the performance of the 7-core SDM OTN system and promptly report failure events through alarms. Our field trial demonstrates the compatibility of uncoupled MCF with high-speed OTN transmission equipment and network management systems, supporting its future deployment in next-generation high-speed terrestrial cable transmission networks. Table and Figures | Reference | Related Articles | Metrics

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Device Activity Detection and Channel Estimation Using Score-Based Generative Models in Massive MIMO TANG Chenyue, LI Zeshen, CHEN Zihan, YANG Howard H. ZTE Communications    2025, 23 (1): 53-62.   DOI: 10.12142/ZTECOM.202501007 Abstract （177）   HTML （4）    PDF （886KB）（210）       Knowledge map    Save The growing demand for wireless connectivity has made massive multiple-input multiple-output (MIMO) a cornerstone of modern communication systems. To optimize network performance and resource allocation, an efficient and robust approach is joint device activity detection and channel estimation. In this paper, we present an approach utilizing score-based generative models to address the under-determined nature of channel estimation, which is data-driven and well-suited for the complex and dynamic environment of massive MIMO systems. Our experimental results, based on a comprehensive dataset generated through Monte-Carlo sampling, demonstrate the high precision of our channel estimation approach, with errors reduced to as low as -45 dB, and exceptional accuracy in detecting active devices. Table and Figures | Reference | Related Articles | Metrics

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Precise Location of Passive Intermodulation in Long Cables by Fractional Frequency Based Multi-Range Rulers DONG Anhua, LIANG Haodong, ZHU Shaohao, ZHANG Qi, ZHAO Deshuang ZTE Communications    2025, 23 (1): 101-106.   DOI: 10.12142/ZTECOM.202501013 Abstract （175）   HTML （2）    PDF （689KB）（67）       Knowledge map    Save A novel method is developed by utilizing the fractional frequency based multi-range rulers to precisely position the passive intermodulation (PIM) sources within radio frequency (RF) cables. The proposed method employs a set of fractional frequencies to create multiple measuring rulers with different metric ranges to determine the values of the tens, ones, tenths, and hundredths digits of the distance. Among these rulers, the one with the lowest frequency determines the maximum metric range, while the one with the highest frequency decides the highest achievable accuracy of the position system. For all rulers, the metric accuracy is uniquely determined by the phase accuracy of the detected PIM signals. With the all-phase Fourier transform method, the phases of the PIM signals at all fractional frequencies maintain almost the same accuracy, approximately 1°(about 1/360 wavelength in the positioning accuracy) at the signal-to-noise ratio (SNR) of 10 dB. Numerical simulations verify the effectiveness of the proposed method, improving the positioning accuracy of the cable PIM up to a millimeter level with the highest fractional frequency operating at 200 MHz. Table and Figures | Reference | Related Articles | Metrics

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Key Techniques and Challenges in NeRF-Based Dynamic 3D Reconstruction LU Ping, FENG Daquan, SHI Wenzhe, LI Wan, LIN Jiaxin ZTE Communications    2025, 23 (3): 71-80.   DOI: 10.12142/ZTECOM.202503008 Abstract （168）   HTML （1）    PDF （675KB）（87）       Knowledge map    Save This paper explores the key techniques and challenges in dynamic scene reconstruction with neural radiance fields (NeRF). As an emerging computer vision method, the NeRF has wide application potential, especially in excelling at 3D reconstruction. We first introduce the basic principles and working mechanisms of NeRFs, followed by an in-depth discussion of the technical challenges faced by 3D reconstruction in dynamic scenes, including problems in perspective and illumination changes of moving objects, recognition and modeling of dynamic objects, real-time requirements, data acquisition and calibration, motion estimation, and evaluation mechanisms. We also summarize current state-of-the-art approaches to address these challenges, as well as future research trends. The goal is to provide researchers with an in-depth understanding of the application of NeRFs in dynamic scene reconstruction, as well as insights into the key issues faced and future directions. Table and Figures | Reference | Related Articles | Metrics

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M+MNet: A Mixed-Precision Multibranch Network for Image Aesthetics Assessment HE Shuai, LIU Limin, WANG Zhanli, LI Jinliang, MAO Xiaojun, MING Anlong ZTE Communications    2025, 23 (3): 96-110.   DOI: 10.12142/ZTECOM.202503011 Abstract （164）   HTML （1）    PDF （4795KB）（85）       Knowledge map    Save We propose Mixed-Precision Multibranch Network (M+MNet) to compensate for the neglect of background information in image aesthetics assessment (IAA) while providing strategies for overcoming the dilemma between training costs and performance. First, two exponentially weighted pooling methods are used to selectively boost the extraction of background and salient information during downsampling. Second, we propose Corner Grid, an unsupervised data augmentation method that leverages the diffusive characteristics of convolution to force the network to seek more relevant background information. Third, we perform mixed-precision training by switching the precision format, thus significantly reducing the time and memory consumption of data representation and transmission. Most of our methods specifically designed for IAA tasks have demonstrated generalizability to other IAA works. For performance verification, we develop a large-scale benchmark (the most comprehensive thus far) by comparing 17 methods with M+MNet on two representative datasets: the Aesthetic Visual Analysis (AVA) dataset and FLICKR-Aesthetic Evaluation Subset (FLICKR-AES). M+MNet achieves state-of-the-art performance on all tasks. Table and Figures | Reference | Related Articles | Metrics

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Integrated All-Light Network for Air, Space, Land, and Sea LIANG Yingze, WANG Linning, QI Ziqian, LIU Pengzhan, WANG Yongjin ZTE Communications    2025, 23 (2): 109-114.   DOI: 10.12142/ZTECOM.202502012 Abstract （162）   HTML （3）    PDF （2391KB）（49）       Knowledge map    Save To meet the demands of high-speed communication under strong electromagnetic interference, an all-light network (ALN) based on a multi-band optical communication system is proposed. It is designed for cross-scenario interconnection and networking, covering air, space, land, and sea. The ALN integrates four types of optical links: underwater blue light communication, white light illumination communication, solar-blind deep ultraviolet communication, and long-distance laser communication systems. These links are interconnected via Ethernet switches with the Transmission Control Protocol (TCP). Any ALN node supports both wired and wireless device access. The data transmission performance between network nodes was tested, with a maximum transmission delay of 73.3 ms, a maximum packet loss rate of 6.1%, and a maximum jitter of 15 ms. This comprehensive all-light network with all-scenario coverage lays the foundation for the future development of network technologies and the digital economy. Table and Figures | Reference | Related Articles | Metrics

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Channel Measurement and Analysis of Human Body Radar Cross Section in 26 GHz ISAC Systems DUAN Hongyu, WANG Mengyang, DUO Hao, HE Danping, MA Yihua, LU Bin, ZHONG Zhangdui ZTE Communications    2025, 23 (2): 3-10.   DOI: 10.12142/ZTECOM.202502002 Abstract （162）   HTML （5）    PDF （2126KB）（58）       Knowledge map    Save Radar cross section (RCS) plays a critical role in modeling target scattering characteristics and enhancing the precision of target detection and localization in integrated sensing and communication (ISAC) systems. This paper investigates the human body RCS at 26 GHz via multi-angle channel measurements under different clothing conditions. Based on calibrated electromagnetic (EM) parameters, the RCS characteristics of the human body in far-field conditions are analyzed using ray-tracing (RT) simulations. Some suggestions for the design of ISAC systems are also discussed. The results provide a solid theoretical foundation and practical reference for the modeling of target scattering characteristics for ISAC channels. Table and Figures | Reference | Related Articles | Metrics

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Antenna Parameter Calibration for Mobile Communication Base Station via Laser Tracker LI Junqiang, CHEN Shijun, FENG Yujie, FAN Jiancun, CHEN Qiang ZTE Communications    2025, 23 (3): 89-95.   DOI: 10.12142/ZTECOM.202503010 Abstract （152）   HTML （1）    PDF （1386KB）（85）       Knowledge map    Save In the field of antenna engineering parameter calibration for indoor communication base stations, traditional methods suffer from issues such as low efficiency, poor accuracy, and limited applicability to indoor scenarios. To address these problems, a high-precision and high-efficiency indoor base station parameter calibration method based on laser measurement is proposed. We use a high-precision laser tracker to measure and determine the coordinate system transformation relationship, and further obtain the coordinates and attitude of the base station. In addition, we propose a simple calibration method based on point cloud fitting for specific scenes. Simulation results show that using common commercial laser trackers, we can achieve a coordinate correction accuracy of 1 cm and an angle correction accuracy of 0.25°, which is sufficient to meet the needs of wireless positioning. Table and Figures | Reference | Related Articles | Metrics

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GaN-Based Optoelectronic Impact Force Sensor RUAN Junhui, JIANG Chengxiang, XU Shengli, WANG Yongjin, SHI Fan ZTE Communications    2025, 23 (2): 96-102.   DOI: 10.12142/ZTECOM.202502010 Abstract （147）   HTML （7）    PDF （1442KB）（54）       Knowledge map    Save A monolithic integration of the light emitting diode (LED) and photodetector (PD) based on III-nitride is designed and fabricated on a sapphire substrate to act as a transceiver. Due to the coexistence of light emission and detection phenomenon of the multi-quantum well (MQW) structure, the monolithic transceiver can effectively sense environmental changes. By integrating a deformable Polydimethylsiloxane (PDMS) film on the transceiver chip, external force variation can be effectively detected. As the thickness of the PDMS reduces, the sensitivity significantly improves but at the expense of the measuring range. A sensitivity of 2.968 3% per newton for a range of 0–11 N is obtained when a 2 mm-thick PDMS film is packaged. The proposed monolithic GaN transceiver-based sensing system has the advantages of compactness, low cost, and simple assembly, providing an optional method for practical applications. Table and Figures | Reference | Related Articles | Metrics

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Space Network Emulation System Based on a User-Space Network Stack LEI Jianzhe, ZHAO Kanglian, HOU Dongxu, ZHOU Fenlin ZTE Communications    2025, 23 (2): 11-19.   DOI: 10.12142/ZTECOM.202502003 Abstract （137）   HTML （1）    PDF （1891KB）（35）       Knowledge map    Save This paper presents a space network emulation system based on a user-space network stack named Nos to solve space networks' unique architecture and routing issues and kernel stacks' inefficiency and development complexity. Our low Earth orbit satellite scenario emulation verifies the dynamic routing function of the protocol stack. The proposed system uses technologies like Open vSwitch (OVS) and traffic control (TC) to emulate the space network's highly dynamic topology and time-varying link characteristics. The emulation results demonstrate the system's high reliability, and the user-space network stack reduces development complexity and debugging difficulty, providing convenience for the development of space network protocols and network functions. Table and Figures | Reference | Related Articles | Metrics

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6G Digital Twin Enabled Channel Modeling for Beijing Central Business District LU Mengyuan, BAI Lu, HAN Zengrui, HUANG Ziwei, LU Shiliang, CHENG Xiang ZTE Communications    2025, 23 (2): 31-45.   DOI: 10.12142/ZTECOM.202502005 Abstract （135）   HTML （4）    PDF （3130KB）（58）       Knowledge map    Save A novel digital twin (DT) enabled channel model for 6G vehicular communications in Beijing Central Business District (Beijing CBD) is proposed, which can support the design of intelligent transportation systems (ITSs). A DT space for Beijing CBD is constructed, and two typical transportation periods, i.e., peak and off-peak hours, are considered to characterize the vehicular communication channel better. Based on the constructed DT space, a DT-enabled vehicular communication dataset is developed, including light detection and ranging (LiDAR) point clouds, RGB images, and channel information. With the assistance of LiDAR point clouds and RGB images, the scatterer parameters, including number, distance, angle, power, and velocity, are analyzed under different transportation periods. The channel non-stationarity and consistency are mimicked in the proposed model. The key channel statistical properties are derived and simulated. Compared to ray-tracing (RT) results, the accuracy of the proposed model is verified. Table and Figures | Reference | Related Articles | Metrics

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Air-to-Ground Channel Measurement and Modeling for Low-Altitude UAVs: A Survey CHEN Peng, LIU Yajuan, WEI Wentong, WANG Wei, LI Na ZTE Communications    2025, 23 (2): 60-75.   DOI: 10.12142/ZTECOM.202502007 Abstract （131）   HTML （3）    PDF （1491KB）（231）       Knowledge map    Save As important infrastructure for airborne communication platforms, unmanned aerial vehicles (UAVs) are expected to become a key part of 6G wireless networks. Thus, modeling low- and medium-altitude propagation channels has attracted much attention. Air-to-ground (A2G) propagation channel models vary in different scenarios, requiring accurate models for designing and evaluating UAV communication links. Unlike terrestrial models, A2G channel models lack detailed investigation. Therefore, this paper provides an overview of existing A2G channel measurement campaigns, different types of A2G channel models for various environments, and future research directions for UAV air-land channel modeling. This study focuses on the potential of millimeter-wave technology for UAV A2G channel modeling and highlights non-suburban scenarios requiring consideration in future modeling efforts. Table and Figures | Reference | Related Articles | Metrics

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Overview of Cross-Component In-Loop Filters in Video Coding Standards LI Zhaoyu, MENG Xuewei, ZHANG Jiaqi, HUANG Cheng, JIA Chuanmin, MA Siwei, JIANG Yun ZTE Communications    2025, 23 (2): 85-95.   DOI: 10.12142/ZTECOM.202502009 Abstract （130）   HTML （1）    PDF （3093KB）（43）       Knowledge map    Save In-loop filters have been comprehensively explored during the development of video coding standards due to their remarkable noise-reduction capabilities. In the early stage of video coding, in-loop filters, such as the deblocking filter, sample adaptive offset, and adaptive loop filter, were performed separately for each component. Recently, cross-component filters have been studied to improve chroma fidelity by exploiting correlations between the luma and chroma channels. This paper introduces the cross-component filters used in the state-of-the-art video coding standards, including the cross-component adaptive loop filter and cross-component sample adaptive offset. Cross-component filters aim to reduce compression artifacts based on the correlation between different components and provide more accurate pixel reconstruction values. We present their origin, development, and status in the current video coding standards. Finally, we conduct discussions on the further evolution of cross-component filters. Table and Figures | Reference | Related Articles | Metrics

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Intelligent AP Clustering and Receiver Design for Uplink Cell-free Networks AN Zhenyu, HE Shiwen, YANG Li, ZHAN Hang, HUANG Yongming ZTE Communications    2025, 23 (2): 103-108.   DOI: 10.12142/ZTECOM.202502011 Abstract （126）   HTML （2）    PDF （847KB）（43）       Knowledge map    Save Cell-free networks can effectively reduce interference due to diversity gain. Two key technologies, access point (AP) clustering and transceiver design, play key roles in cell-free networks, and they are implemented at different layers of the air interface. To address the issues and obtain global optimal results, this paper proposes an uplink joint AP clustering and receiver optimization algorithm, where a cross-layer optimization model is built based on graph neural networks (GNNs) with low computational complexity. Experimental results show that the proposed algorithm can activate fewer APs for each user with a small performance loss compared with conventional algorithms. Table and Figures | Reference | Related Articles | Metrics

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Special Topic on Digital Twin Online Channel Modeling for 6G and Beyond WANG Chengxiang, HUANG Chen ZTE Communications    2025, 23 (2): 1-2.   DOI: 10.12142/ZTECOM.202502001 Abstract （116）   HTML （5）    PDF （393KB）（43）       Knowledge map    Save Reference | Related Articles | Metrics

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PON Monitoring Scheme Based on TGD-OFDR with High Spatial Resolution and Dynamic Range ZHU Yidai, FAN Xinyu, ZHU Songlin, DONG Jiaxing, LI Guoqiang, HE Zuyuan ZTE Communications    2025, 23 (4): 3-9.   DOI: 10.12142/ZTECOM.202504002 Abstract （73）   HTML （3）    PDF （1293KB）（55）       Knowledge map    Save Conventional optical time-domain reflectometry (OTDR) schemes for passive optical network (PON) link monitoring are limited by insufficient dynamic range and spatial resolution. The expansion of PONs, with increasing optical network units (ONUs) and cascaded splitters, imposes even more stringent demands on the dynamic range of monitoring systems. To address these challenges, we propose a time-gated digital optical frequency-domain reflectometry (TGD-OFDR) system for PON monitoring that effectively decouples the inherent coupling between spatial resolution and pulse width. The proposed system achieves both high spatial resolution (~0.3 m) and high dynamic range (~30 dB) simultaneously, marking a significant advancement in optical link monitoring. Table and Figures | Reference | Related Articles | Metrics

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New Generation FTTR Communication and Networking Technology GE Xiaohu, ZHONG Yi ZTE Communications    2025, 23 (4): 1-2.   DOI: 10.12142/ZTECOM.202504001 Abstract （59）   HTML （6）    PDF （375KB）（33）       Knowledge map    Save Reference | Related Articles | Metrics