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20 January 2025, Volume 41 Issue 1
Topic: Fine Grain Optical Transport Network
2025-01-07
2025, 41(1):  1-2. 
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Application analysis of fgOTN in power communication network
Jianming LIU
2025, 41(1):  3-15.  doi:10.11959/j.issn.1000-0801.2025023
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With the steady advancement of new power system construction and the development of smart grids, the power communication network, as an important part of a power system, its technology selection and network architecture design are crucial to the reliability of the power system. For the application of fine grain optical transport network (fgOTN) technology in power communication network, the evolution of fgOTN technology and its characteristics were deeply analyzed, and compared with synchronous digital hierarchy (SDH) and optical transport network (OTN), it was found that fgOTN had powerful management and control capabilities, flexible networking and service bearing capabilities, reliable protection mechanisms, and good compatibility and evolution capabilities, which were suitable for communication network applications in industries such as electric power.

Research on key technologies and applications of fgOTN for the new electric power system
Rui TANG, Zejing GUANG, Jia TANG, Xiaoxi GUO, Junfeng ZHAO
2025, 41(1):  16-25.  doi:10.11959/j.issn.1000-0801.2025019
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The development of the new electric power system for the future computing power access and computing power interconnection, many challenges are posed in the carrying capacity, access flexibility and multi-service adaptability of the power communication network. In view of the problems of low carrier efficiency for customer signals below 1 Gbit/s in existing optical transport network (OTN) networks, the fine grain optical transport network (fgOTN) technical system that provides fine grain service bearers had been analyzed, and the technical advantages and feasibility of fgOTN based on key technical solutions and experimental data had also been validated. The results show that fgOTN has obvious advantages in many aspects compared with the current virtual container (VC)/packet transmission (PKT)/ optical channel data unit (ODU) multi-plane OTN. How to deploy fgOTN in the existing network and network evolution will be the focus of future research.

Review of the application of fgOTN in the interconnection of artificial intelligence data centers
Qingna SHI, Jiaxue WANG, Shiyu LI, Mengru CAI, Xiaodong LIU, Shan YIN, Shanguo HUANG
2025, 41(1):  26-41.  doi:10.11959/j.issn.1000-0801.2025022
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With the rapid growth of data traffic and service requirements in artificial intelligence data centers, efficient and flexible network solutions have become critical. The fine grain optical transport network (fgOTN), which serves as a continuation of synchronous digital hierarchy (SDH) technology and an extension of optical transport network (OTN) technology, is applied in the interconnection of artificial intelligence data centers to meet their multiple requirements for flexible scheduling, efficient transmission, strict security isolation, and low latency. Firstly, the basic concepts, technical architecture, and application scenarios of fgOTN were introduced. Subsequently, the related concepts, architectures, key technologies, and application scenarios of artificial intelligence data centers were elaborated. Based on these foundations, the application of fgOTN in interconnection of artificial intelligence data centers was discussed in detail, aiming to promote efficient and reliable data transmission between artificial intelligence data centers. Finally, the research directions and development trends were discussed.

Research on key technology and network deployment of fgOTN
Shangjin LIAO
2025, 41(1):  42-53.  doi:10.11959/j.issn.1000-0801.2025021
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With the development of 5G+ vertical industries and high-quality government-enterprise dedicated lines, the demand for fine particle business still maintains strong vitality. Starting with the technical development of fine grain optical transport network (fgOTN), the key technical schemes of fgOTN were focused on, network planning was studied, and the application scenarios of fgOTN were explored. The research provided reference ideas for operators how to deploy fgOTN in combination with the live network, so as to effectively protect network investment. Finally the deployment and application of fgOTN in domestic networks were expected to promote.

Research on the application of fgOTN in the new electric power system
Sunsheng CHEN, Yi WANG, Mingqi LIN, Shaobin LU, Qihan YANG, Jian ZHENG
2025, 41(1):  54-64.  doi:10.11959/j.issn.1000-0801.2025018
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With the development of new electric power systems, various emerging businesses are growing rapidly, which puts higher demands on the service granularity, bandwidth, latency, and reliability of communication transmission networks. Compared to traditional synchronous digital hierarchy (SDH) and optical transport network (OTN) technologies, fine grain optical transport network (fgOTN) technology is more suitable for the current development needs of new electric power systems. Based on this background, the standard evolution of fgOTN was described, the technical principles of fgOTN were elaborated, the application advantages of fgOTN were introduced. Finally, the adaptability of fgOTN to power system services was discussed and experimentally tested, and the test results were analyzed. The research aims to provide data references and insights for the future promotion and application of fgOTN in the electric power system.

Research and Development
DOA estimation method for time-varying metasurface based on asynchronous modulation
Ming YI, Ming CHEN, Zhou ZHONG, Liang JIN
2025, 41(1):  65-74.  doi:10.11959/j.issn.1000-0801.2025005
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In response to the challenge of spectral aliasing in target signals, which arose from constraints on the temporal modulation rate in existing time-domain direction of arrival (DOA) estimation methods, a novel asynchronous control-based DOA estimation technique was proposed. This approach significantly increased the modulation rate, effectively mitigating the problem of spectral aliasing and consequently broadening the signal processing bandwidth. This novel approach capitalized on the inherent persistence of unit states over a duration, without necessitating any alterations to the hardware constraints of the time-varying metasurface (TVM). By staggering the initiation of state changes across various column units, the method enabled the acquisition of multiple distinct responses within a single state’s temporal window. The asynchronous modulation strategy effectively augmented the virtual channel count under the limitations imposed by material properties, thereby enhancing the precision of DOA estimation. Empirical simulation outcomes substantiated the efficacy of this approach, demonstrating a significant enhancement in DOA estimation performance compared to existing synchronous modulation techniques, closely approximating the theoretical optimum for DOA estimation outcomes.

Drone detection method based on K-Medoids to extract channel state characteristics
Lingyu SONG, Peng PAN, Tianle LIU
2025, 41(1):  75-87.  doi:10.11959/j.issn.1000-0801.2025008
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Effective management of low-altitude targets is key to promot the development of the low-altitude economy. In urban environments, strong clutter and building occlusion make it difficult for traditional radar detection methods to effectively monitor low-speed drones. Based on this, a new approach of drone detection was proposed, which involved identifying changes in channel state characteristics to determine whether a drone was presented in a specified area. The core of this method lied in utilizing the already widely deployed mobile base stations and other external radiation sources in cities, capturing the impact of drone presence on the number of multipath channel paths by using the K-Medoids clustering algorithm, to achieve drone perception. This method did not require the construction of an accurate reference signal nor the use of Doppler systems to suppress strong clutter. Simulation results show that the proposed method can achieve detection probabilities of over 80% within a range of 1 square kilometer, and the detection probability can reach about 90% as the range decreases. Therefore, it is capable of effectively detecting low-altitude, slow-moving drones in urban scenarios.

Performance optimization of active RIS-assisted near-shore dual-function radar communicaiton system
Miao XU, Dianwu YUE, Yu SUN, Xiangkai WU, Meng YUAN
2025, 41(1):  88-98.  doi:10.11959/j.issn.1000-0801.2025007
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To address the issues of poor communication quality, high demand for radar detection, and scarce scarcity of spectrum resources for maritime users in coastal waters, an offshore dual-function radar communication (DFRC) system assisted by a shipborne active reconfigurable intelligent surface (ARIS) was studied. In order to align with the characteristics of maritime channels, a three-path loss model and a two wave with diffuse power (TWDP) channel considering the evaporative duct over the sea was employed. An alternating optimization algorithm based on fractional programming theory and the Lagrangian operator method was proposed. Under the constraint of radar detection power, the user’s weighting and rate were maximized by optimizing the beamforming of the base station and the reflection matrix vector of the ARIS. Simulation results show that the proposed algorithm has good convergence properties. Compared with the DFRC system assisted by a passive reflective intelligent surface (RIS), the ARIS-assisted coastal DFRC system can significantly improve the weighted sum rate of maritime users while maintaining the same detection power.

Performance analysis of high-rate generalized space code index modulation system
Lina BIAN, Qianyu ZHANG, Jiayan WU
2025, 41(1):  99-110.  doi:10.11959/j.issn.1000-0801.2025011
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Traditional code index modulation (CIM) systems only carry information through spreading codes and constellation symbols, with low energy efficiency and spectral efficiency. However, adding phase as a unique modulation symbol to carry information has the advantage of low transmission power consumption. To fully utilize the multi-antenna lead to improve spectral efficiency, a high-rate generalized space code index modulation (HR-GS-CIM) system with low-power design was proposed. The traditional modulation symbols were replaced with the additional phase by the HR-GS-CIM system, and the genetic algorithm (GA) was used to optimize the design of the additional phase, which could acquire high energy efficiency advantage and performance advantage. At the same time, the methods of generalized and spatial indexing were introduced to jointly map select the additional phase, spreading code, and antenna lead, and a low-complexity joint mapping selection algorithm was adopted to greatly improve the system’s spectral efficiency. Furthermore, the theoretical performance of the HR-GS-CIM system was analyzed and the consistency between the theoretical and simulated performance was verified. Finally, compared with traditional CIM systems, the simulation results show that the proposed HR-GS-CIM system has significant performance gain.

Dual-channel attribute graph clustering beyond the homogeneity assumption
Junxiu AN, Yuan LIU, Linwang YANG
2025, 41(1):  111-124.  doi:10.11959/j.issn.1000-0801.2025009
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In recent years, significant progress has been made in the research of attribute graph clustering. However, existing methods are mostly based on the homogeneity assumption, thereby neglecting the application scenarios of heterogeneous graphs, leading to the loss of high-frequency information and poor clustering results during the clustering process. To address this issue, a novel dual-channel attribute graph clustering (DCAGC) method was proposed. A mixture of Gaussian models was used to predict the homogeneity of node connections and two views of homogeneous and heterogeneous were built, based on this prediction to capture low-frequency and high-frequency information in the graph from different perspectives. Simultaneously, by integrating contrastive learning and clustering, more precise node embeddings were achieved. Compared to other methods, DCAGC demonstrates significant clustering performance when handling heterogeneous graph datasets and exhibits strong resilience to anomalous connections.

Homocentric sphere model: a novel network architecture supporting 6G dense deployment and high-speed mobility scenarios
Guoqing LI, Peibo WANG, Li CHEN, Bo HU, Shanzhi CHEN
2025, 41(1):  125-136.  doi:10.11959/j.issn.1000-0801.2025015
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5G ultra-dense network (UDN) was introduced to improve throughput, especially for static and low-speed scenarios, and thus cannot meet the demands that require high throughput and high mobile speed at the same time. For the new 6G scenarios that need to support both high-capacity and high-speed mobility in the future, a homocentric sphere model (HSM) network architecture was proposed, which adopted the control-plane/user-plane data separation and multiple transmission and reception point (TRP) cooperative transmission method to deal with the problem in densely deployed networks. The HSM was an effective method to improve the network capacity and cope with high-speed mobility in dense deployment networks by adopting control-plane/user-plane data separation and multiple TRP co-transmission to deal with the problems of high Doppler frequency shift effect and frequent switching of TRP in the dense deployment networks. The results demonstrate that the proposed homocentric sphere model can effectively reduce the Doppler shift effect in the high-speed mobility scenario of a densely organized network, and can provide higher network traversal spectrum efficiency.

Sequential recommendation based on contrast enhanced time-aware self-attention mechanism
Yang YU, Ruiqin WANG
2025, 41(1):  137-147.  doi:10.11959/j.issn.1000-0801.2025003
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The existing sequence recommendation models have shortcomings in utilizing absolute interaction time, resulting in inaccurate modeling of user preferences. Sequential recommendation based on contrast enhanced time-aware self-attention mechanism (CTiSASRec) was proposed. Firstly, the calculation process of attention weights integrated rating data, absolute interaction time, location information, and project popularity. Secondly, the absolute interaction time and location order of the project were integrated to generate a new project location embedding. Finally, during the training process, contrast learning based on the results of two modeling sequences was used to distinguish the similarities and differences between samples, thereby improving the accuracy and robustness of the model. Experimental studies conducted on six datasets of different fields and scales show that CTiSASRec outperforms state-of-the-art sequential recommendation models.

Enhanced zebra optimization algorithm and applications of power allocation in SDWN
Jiajia LI, Ligang DONG, Xian JIANG
2025, 41(1):  148-163.  doi:10.11959/j.issn.1000-0801.2025017
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To address the issue of interference caused by shared resources in multi-user communications in software defined wireless network (SDWN), an enhanced zebra optimization algorithm (EZOA) was proposed to achieve power allocation that maximizes the secrecy rate. By introducing exploration factors and perturbation parameters into the zebra optimization algorithm, EZOA enhanced global search and local exploitation capabilities, while also improving the foraging strategy to increase algorithm diversity. Experimental results demonstrate that EZOA exhibits superior competitiveness compared to six other well-established algorithms on the IEEE CEC 2014 benchmark function set. In the SDWN power allocation problem, EZOA achieves an average improvement of 5.46% in user secrecy rate and the fastest convergence speed compared to five other algorithms.

Unsupervised intrusion detection model based on temporal convolutional network
Jinju LIAO, Jiawei DING, Guanghui FENG
2025, 41(1):  164-173.  doi:10.11959/j.issn.1000-0801.2025001
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Most existing intrusion detection models rely on long short-term memory (LSTM) networks to consider time-dependencies among data. However, LSTM’s sequential data processing significantly increases computational complexity and memory consumption during training. Therefore, unsupervised intrusion detection model based on multi-head attention mechanism and temporal convolutional network (UDMT) was proposed. UDMT didn’t rely on LSTM networks. Instead, it used temporal convolutional network and multi-head attention mechanism in the generative adversarial network generator and discriminator networks to enable more computation parallelization, and reduced computational complexity. Moreover, UDMT was capable of detecting both known and zero-day attacks without relying on labeled attack data. In addition, UDMT can adopt different privacy layer modes, and the configuration was flexible to meet the requirements of different detection rates and detection delays. Experiment results show that the proposed UDMT has higher detection rate and lower detection latency than two state-of-the-art intrusion detection models.

Engineering and Application
Research on power communication private network based on interleaved digital-analog hybrid modulation
Jun ZHANG, Xiang XU, Wenjun RUI, Weisheng HU
2025, 41(1):  174-183.  doi:10.11959/j.issn.1000-0801.2025006
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Power communication network is an important part to ensure the safe, stable, and economical operation of power grid. The optical fiber transmission system is widely used in the power communication network to provide wide bandwidth. However, there is a signal-to-noise ratio obstacle for high-fidelity transmission. Based on this, an interleaved digital-analog hybrid modulation scheme was proposed. At the transmitter, the original waveform was divided into a discrete digital part and a continuous analog part. At the receiver, the link noise in the digital part was removed by rounding operation, and the spectral efficiency was improved by the linear combination of analog part. Besides, the time-domain interleaving of in-phase and quadrature components reduced the peak-to-average power ratio, and enhanced the effective signal-to-noise ratio under the peak power constraint. In the direct detection-based experiment, after 1 km standard single-mode fiber transmission, the recovered signal-to-noise ratio of 68 GBd signal with interleaved digital-analog modulation could achieve 33.0 dB, which supports the 1 024-ary quadrature amplitude modulation (1 024-QAM) signal with 17 GHz bandwidth. The corresponding bitrate was 170 Gbit/s, and the common public radio interface-equivalent rate was 1 Tbit/s. Both simulation and experimental results indicate that the interleaved digital-analog modulation scheme exhibits a signal-to-noise ratio gain compared with the conventional modulation scheme, and offers a feasible scheme for low-cost, high-bandwidth and high-fidelity power communication network.

A method for detecting abnormal electricity prices at charging stations based on two rounds of clustering
Xiaohui XUE, Wen ZHANG, Jing ZHANG, Yan CHEN, Chun ZHOU, Liang CHEN, Zengwei CAO
2025, 41(1):  184-190.  doi:10.11959/j.issn.1000-0801.2025004
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Due to the complexity of electricity pricing policies, multiple implementation steps, and difficulty in regulation, errors in electricity pricing implementation occur from time to time. This not only damages the fairness and efficiency of the electricity market but also affects the economic benefits of power enterprises and the electricity costs of users. A method was proposed for detecting electricity price anomalies at charging stations based on secondary clustering. Firstly, the electricity price anomalies were classified and the electricity consumption characteristics were analyzed. Secondly,the K-means clustering algorithm was used to extract electric vehicle users. Then, in the second clustering, the density-based spatial clustering of applications with noise (DBSCAN) algorithm was used to accurately identify more complex default situations,such as high price and low connection. The proposed method improves the accuracy and efficiency of electricity price implementation through two rounds of cluster analysis, and has certain theoretical significance and application value.

A multi-feature fusion exercise recommendation method based on knowledge tracking machine
ZHUGE Bin, WANG Ying, XIAO Mengfan, YAN Lei, Wang Bingyan, DONG Ligang, JIANG Xian
Online First: 2024-08-18
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Current Research and Development Trend of 5G Network Technologies
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Telecommunications Science. 2015 Vol. 31 (9): 149-155 doi: 10.11959/j.issn.1000-0801.2015218
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Progress of UAV Ad Hoc Network:A Survey
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Telecommunications Science. 2015 Vol. 31 (4): 127-137 doi: 10.11959/j.issn.1000-0801.2015102
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Edge computing and network slicing technology in 5G
Hongyu XIANG,Yangwen XIAO,Xian ZHANG,Zhuying PIAO,Mugen PENG
Telecommunications Science. 2017 Vol. 33 (6): 54-63 doi: 10.11959/j.issn.1000-0801.2017200
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Analysis in the Present and Developing Status of Cloud Computing
Bingyi Fang,Yunyong Zhang,Ying Cheng,Lei Xu
Telecommunications Science. 2010 Vol. 26 (8A): 1-10 doi: 10.3969/j.issn.1000-0801.2010.8A.001
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Big Data Technology:Current Applications and Prospects
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Telecommunications Science. 2015 Vol. 31 (7): 1-12 doi: 10.11959/j.issn.1000-0801.2015189
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Kubernetes based converged cloud native infrastructure solution and key technologies
Zhenwei HE,Danchi HUANG,Liyun YAN,Yuanzhi LIN,Xinzhang YANG
Telecommunications Science. 2020 Vol. 36 (12): 77-88 doi: 10.11959/j.issn.1000-0801.2020314
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Computing network:a new multi-access edge computing
Bo LEI, Zengyi LIU, Xuliang WANG, Mingchuan ·ANG, ·unqing CHEN
Telecommunications Science. 2019 Vol. 35 (9): 44-51 doi: 10.11959/j.issn.1000-0801.2019209
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A survey of mobile edge computing
Zishu LI,Renchao XIE,Li SUN,Tao HUANG
Telecommunications Science. 2018 Vol. 34 (1): 87-101 doi: 10.11959/j.issn.1000-0801.2018011
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Telecommunications Science. 2020 Vol. 36 (6): 1-13 doi: 10.11959/j.issn.1000-0801.2020181
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Telecommunications Science. 2018 Vol. 34 (10): 124-129 doi: 10.11959/j.issn.1000-0801.2018271
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Key Technologies in Physical Layer of 5G Wireless Communications Network
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Telecommunications Science. 2015 Vol. 31 (12): 40-45 doi: 10.11959/j.issn.1000-0801.2015322
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Status and Development of Aeronautical Ad Hoc Networks
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Telecommunications Science. 2016 Vol. 32 (3): 139-146 doi: 10.11959/j.issn.1000-0801.2016039
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Telecommunications Science. 2017 Vol. 33 (11): 134-140 doi: 10.11959/j.issn.1000-0801.2017296
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Telecommunications Science. 2018 Vol. 34 (4): 1-11
doi: 10.11959/j.issn.1000-0801.2018140
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A survey of mobile edge computing
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Telecommunications Science. 2018 Vol. 34 (1): 87-101
doi: 10.11959/j.issn.1000-0801.2018011
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Telecommunications Science. 2021 Vol. 37 (8): 1-17
doi: 10.11959/j.issn.1000-0801.2021204
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Review of image classification based on deep learning
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Telecommunications Science. 2019 Vol. 35 (11): 58-74
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Telecommunications Science. 2022 Vol. 38 (1): 1-12
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