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    20 April 2023, Volume 39 Issue 4
    Overview of programmable data plane technology
    Xinxin TANG, Xuewen ZENG, Zhiyuan LING, Lei SONG
    2023, 39(4):  1-16.  doi:10.11959/j.issn.1000-0801.2023093
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    In software defined network, the programmability provided by the programmable data plane is the cornerstone of network function virtualization.The core of programmable data plane technology is programmability and packet processing performance.Firstly, the packet processing abstraction of existing data planes from the programmability of data planes was explored.Then, the existing data plane related technologies were discussed in detail in terms of the target platforms and related algorithms for data plane implementation, respectively.Finally, the key challenges of high-performance data plane technologies were discussed.

    Research and Development
    Research on collaborative resource optimization technology based on convergence of computing, control and communication in Internet of vehicles
    Zhilong ZHANG, Tianqi ZHANG, Xuefei LI, Danpu LIU
    2023, 39(4):  17-30.  doi:10.11959/j.issn.1000-0801.2023090
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    Internet of vehicles is highly dynamic and has diverse application types, including both security and non-security applications.How to satisfy differentiated requirements at the same time is one of the major challenges that Internet of vehicles face.Therefore, the convergence of computing, control and communication in Internet of vehicles was investigated, and the necessity of the collaborative management of multi-dimensional resources was outlined to improve both the driving safety and the quality of experience.Specifically, the control and communication convergence mechanism for autonomous driving, the computing and communication resource collaborative management mechanism for infotainment application, and the multi-dimensional resource collaborative management mechanism for differentiated application concurrency were introduced respectively according to the application characteristics.Finally, the technology development trend of this field was discussed based on related challenge analysis.

    Distributed IOS-SM transmission scheme with joint antenna and IOS unit selection for high-speed railway scenario
    Qingfeng DING, Song WANG
    2023, 39(4):  31-42.  doi:10.11959/j.issn.1000-0801.2023092
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    A distributed intelligent omni-surface (IOS) -assisted spatial modulation (SM) transmission scheme was proposed to address the problem of transmission rate degradation caused by the high signal penetration loss in closed carriages in the high-speed railway scenarios.Firstly, SM technology was utilized to ensure that the indexed information section was not affected by penetration loss.Then, to reduce the high path loss and power loss of the long-range IOS windows, the distributed IOS was selected by traversal algorithm according to the principle of maximizing the received signal-to-noise ratio, and the best IOS window was activated to transmit the SM modulated information.Finally, to reduce the impact of the missing direct view path gain on the overall system performance, the antenna removal principle and the sequential selection method were used to dynamically and selectively activate the receiving antenna and IOS unit under the power consumption model.The simulation results show that the proposed scheme is more suitable for the high-speed railway wireless communication scenario than the conventional relay-forwarding and reconfigurable intelligence surface -SM (RIS-SM) schemes.And with the power loss model, the distributed IOS-SM scheme chosen by the combined antenna and IOS unit is still able to guarantee high performance transmission of the system.

    Research on multi-domain collaboration based method of TDD large-scale networking
    Xiaoyun WANG, Wei DENG, Long ZHANG, Qi SUN
    2023, 39(4):  43-51.  doi:10.11959/j.issn.1000-0801.2023085
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    How to maximize the network service capability under the constraints of massive nodes and multi-domainresources is the core problem faced by TDD large-scale networking.The method of TDD large-scale networking under fully collaborative optimization architecture were innovatively proposed, which could maximize network service capabilities through inter layer and intra layer collaboration among wireless connection layer, signal processing layer and service control layer.Aiming at efficient use of wireless resources, the method of multi-domain conversion in wireless connection layer were put forward, including the principles and mechanism of space-time-frequency-code multi-domain conversion.The results of practical verification in 4G/5G existing network show that the proposed architecture and method of TDD large-scale networking can effectively control the interference while improving utilization of multi-domain resourcesto maximize network capacity.

    Decomposition of exponential sums based on subspace and its application in channel estimation
    Zhiwei WU, Haiquan WANG, Meihui LI, Xinyu ZHANG, Taoxin QIAN
    2023, 39(4):  52-59.  doi:10.11959/j.issn.1000-0801.2023086
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    The problem of the decomposition of an exponential sum sequence is a classical mathematical problem.Prony method and Prony-Kung method are the classical methods to solve this problem.The Prony-Kung method was analyzed in detail from the point of view of support subspace.On this basis, it was proved theoretically that the problem of the decomposition of an exponential sum sequence could be reduced to the determination of the support subspace, and a Lloyd-like algorithm with low-complexity for searching the support subspace for contaminated exponential sum sequence by noised was proposed.Finally, the above algorithm was applied to estimate millimeter wave channel, and the simulation results show the effectiveness of this application.

    Satellite remote sensing and the integration of 6G communication and remote sensing
    Wenjia XU, Yixu WANG, Mugen PENG
    2023, 39(4):  60-70.  doi:10.11959/j.issn.1000-0801.2023089
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    Satellite remote sensing is an important means for humans to achieve high-resolution earth observation, and it has gradually become an important component supporting economic and social development as well as national defense and security.6G pursues deep integration of communication, perception, and computation, and communication and remote sensing integration has become an important feature of it.The development of satellite remote sensing at home and abroad were reviewed, the existing system architecture of satellite remote sensing systems and the integrated system architecture of communication and remote sensing in the 6G era were outlined, and the typical satellite remote sensing technologies and the latest research progress driven by artificial intelligence were elaborated on.In response to the trend of integrating satellite communication and remote sensing in the 6G era, the technical challenges and development trends of realizing the combination of “one satellite, multiple uses, multi-satellite networking, multi-network integration, and intelligent services” were discussed.

    1D-Concatenate based channel estimation DNN model optimization method
    Min LU, Zehao QIN, Zhihui CHEN, Min ZHANG, Guangxue YUE
    2023, 39(4):  71-86.  doi:10.11959/j.issn.1000-0801.2023097
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    In order to improve the channel estimation accuracy of DNN model in wireless communication, a DNN model optimization method based on 1D-Concatenate was proposed.In this method, Concatenate performs one-dimensional data transformation, the DNN model was introduced by hopping connection, the gradient disappearance problem was suppressed, and 1D-Concatenate was used to restore the data features lost during network training to improve the accuracy of DNN channel estimation.In order to verify the effectiveness of the optimization method, a typical DNN-based wireless communication channel estimation model was selected for comparative simulation experiments.Experimental results show that the estimated gain of the existing DNN model can be increased by 77.10% by the proposed optimization method, and the channel gain can be increased by up to 3 dB under high signal-to-noise ratio.This optimization method can effectively improve the channel estimation accuracy of DNN model in wireless communication, especially the improvement effect is significant under high signal-to-noise ratio.

    Community detection algorithm of hybrid node analysis and edge analysis in complex networks
    Kun DENG, Qingfeng JIANG, Xingyan LIU
    2023, 39(4):  87-100.  doi:10.11959/j.issn.1000-0801.2023091
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    The community detection of hybrid node analysis and edge analysis in complex networks (CDHNE), a novel community detection algorithm, was proposed aiming at the problem that both edge community detection and node-based community detection algorithms had corresponding shortcomings in the process of detecting communities, which affected the quality of complex network community detection.The relatively stable characteristics of the edge in the networks were firstly used by the algorithm to construct a more accurate community structure through edge community detection at the early stage of algorithm execution.Then, after the formation of the edge communities, the flexible characteristics of the node were used to accurately detect the boundary of edge communities, so as to more accurately detect the community structure in the complex networks.In the computer-generated network experiments, when the community structure of the network gradually became fuzzy, the number of overlapping nodes and the number of communities to which the overlapping nodes belonged kept increasing.Compared to traditional algorithms, the accuracy of community detection and overlapping nodes detection were improved by an average of 10% and 15%, respectively, by the CDHNE algorithm.In the real network experiments, the tightness of the community structure detected by the CDHNE algorithm was better.Especially when facing large-scale networks with more than 100 000 nodes, the detection task was completed by the CDHNE algorithm with high quality, and the EQ value reached 0.412 1.The experimental results show that the CDHNE algorithm has advantages in operational stability and handling large-scale networks.

    VVC coded distortion prediction model based on frame-level transform coefficient modeling of generalized Gaussian distribution
    Yiyin GU, Hongkui WANG, Haibin YIN
    2023, 39(4):  101-110.  doi:10.11959/j.issn.1000-0801.2023088
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    In versatile video coding (VVC), a variety of advanced coding tools work together to achieve excellent coding performance.Compared with high efficient video coding (HEVC), the transform coefficient distribution (TCD) of VVC has sharper peaks.In order to solve this phenomenon, the probability density function (PDF) of frame-level TCD was modeled, and a frame-level coding distortion prediction model based on statistical modeling was proposed, which modeled frame-level distortion as a function of TCD distribution parameters and quantization parameters.The experimental results show that compared with the Laplace distribution and Cauchy distribution, the generalized Gaussian distribution has the best performance in TCD probability density fitting.The prediction results based on the generalized Gaussian distribution distortion prediction model are closest to the actual coding distortion.

    Design method of energy efficiency optimization in PLC-RF wireless transmission networks
    Yueyu JIANG, Haoxin CHENG, Kang WANG, Wenjun DAI, Xiaoyu LIU
    2023, 39(4):  111-119.  doi:10.11959/j.issn.1000-0801.2023100
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    An energy efficiency optimization transmission scheme using angular information-based channel state information (AI-CSI) was proposed for indoor communications, which integrated the power line communication (PLC) with radio frequency (RF) wireless communication.Specifically, by considering that the Wi-Fi wireless network and the PLC network were the primary and secondary networks, an optimization problem was established to maximize the total energy efficiency of the secondary network.Then, in order to solve the problem, the beam forming weight vector was obtained by using zero-forcing method based on AI-CSI, and an optimization algorithm joint Dinkelbach with Lagrange multiplier was further presented to achieve the optimal power allocation.Finally, computer simulations were given to verify the effectiveness and superiority of the proposed scheme.Besides, the influence of key parameters such as the number of employed antennas and served users was also analyzed.

    Delay-sensitive traffic intellisense scheduling based on optimal decision tree
    Xuerong WANG, Zhengzhi TANG, Yinchuan LI, Meiyu QI, Jianbo ZHU, Liang ZHANG
    2023, 39(4):  120-132.  doi:10.11959/j.issn.1000-0801.2023095
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    Currently, network traffic scheduling strategy cannot be intelligent and on-demand, especially in the congestion caused by sudden network failures and escort scenarios of high-value services.They cannot guarantee latency-sensitive service experience on demand.The delay-sensitive attribute requirements of different network traffic were analyzed and studied, and the internal correlation between the behavior characteristics of varying network traffic and its delay sensitivity requirements was explored.Then, AI technology was used to learn this inherent relationship and construct its mapping relationship, realizing a traffic scheduling technical solution based on the intelligent awareness of delay-sensitive traffic.At the same time, considering the practical issues of interpretability and deploy-ability of AI models, reinforcement learning (RL) technology was used to prune and optimize the interpretable decision tree model, which improved the robustness of the model and made model lighter and easier to implement in equipment deployment.Through experiments by the collected real network traffic, the decision tree model optimized by reinforcement learning could improve the awareness accuracy by 1.75% in a single inference case, and the inference performance was improved by about 30%.The experiment also proved that using micro-statistical features for multiple inferences could help improve the model accuracy; in all experiments, the scale of the decision tree model optimized by RL was reduced by about 60.0%~87.2%, and the Saras had better optimization performance than Q-learning.

    Research on 5G base station energy saving system based on DCNN-LSTM load prediction algorithm
    Jianbin WANG, Shuchun WANG, Shangjin LIAO, Shuyuan SHI
    2023, 39(4):  133-141.  doi:10.11959/j.issn.1000-0801.2023101
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    With the rapid construction of the 5G wireless communication network, the energy consumption pressure of operators, and even the overall communication industry, is simultaneously highlighted.Achieving sustainable development of the industry through energy conservation and consumption reduction has become a new research direction for the current 5G network development.Taking the PRB rate as the load evaluation index, LSTM model was improved by using DCNN to extract the depth feature of the cell’s indicators.A set of DCNN-LSTM deep learning model that could predict the future value of PRB rate was proposed.On the basis of the improved algorithm, the network topology of the current 5G access network was optimized.An additional network element and its working system were designed.An intelligent energy-saving system, which ensured the network experience, of 5G base stations was realized.

    Engineering and Application
    Design and application of multi-dimensional evaluation model of telecommunication network operations and maintenance
    Liang XU, Ye WANG, Ran ZHENG, Jiheng ZHANG, Ping YUAN, Xinyang LI, Yu TIAN
    2023, 39(4):  142-151.  doi:10.11959/j.issn.1000-0801.2023094
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    Telecommunication network operations and maintenance is a basic and critical work for communications service providers (CSP).At present, there is little public operations and maintenance information of CSP.In addition, it is lack of effective evaluation model of telecommunication network operations and maintenance.A multi-dimensional evaluation model of telecommunication network operations and maintenance was proposed, which took abalanced score card as a basis and was combined with long-term operations and maintenance work and research practice.The model was verified by applying different types of CSP, including international large CSP, innovative CSP, and high-growth CSP.

    An eCUA model for integrated computing power and decentralized digital identity and a new business system supporting information framework
    Wen QIAO, Xiaozheng WANG, Gan REN, Aidong YANG, Shoufeng WANG, Peng WANG, Xiaozhou YE, Ye OUYANG
    2023, 39(4):  152-164.  doi:10.11959/j.issn.1000-0801.2023098
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    An enhanced customer-user-account (eCUA) model was proposed.Based on the traditional three-household (customer, user, account) model in telecom industry, an enhanced customer-user-account model and its information framework was constructed by means of virtual digital human and decentralized identity technology, combined with the service demand of task-based computing power.With the globally unique identity, eCUA enables the traditional three-household model to have distributed and decentralized sharing capability.eCUA can solve the problem of information inconsistency in multi-account management, multi-source data synchronization, and multi-channel display of same-origin data.It can effectively support the closed-loop management of the whole process of computing power network business, such as computing power subscription, experience, ordering, and transaction operation.Therefore, the eCUA model proposed can be used as the main data reference frame of the integrated telecommunications service support system.

    Practice on edge cloud security of telecom operators
    Le ZHANG, Hongyuan MA
    2023, 39(4):  165-172.  doi:10.11959/j.issn.1000-0801.2023096
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    Abstact: In the peak period of operator edge cloud construction, in order to realize the “three synchronization” construction strategy, the network edge cloud construction and operation and maintenance management mode were expounded, the security risks and security construction requirements of network edge cloud were discussed firstly.Then, the limitations of the security construction mode in the edge cloud scenario for the traditional cloud were analyzed.Finally, an innovative network edge cloud security construction plan was proposed, and the province’s edge cloud security construction was carried out uniformly.The comparison was completed from the perspective of practical application, and the advantages of the innovative edge cloud construction plan was verified.

    Cellular automata model based power network attack prediction technology
    Lijuan YE, Yiting WANG, Licheng ZHU
    2023, 39(4):  173-179.  doi:10.11959/j.issn.1000-0801.2023099
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    The prediction range of the traditional power network attack range prediction technology was not wide enough, resulting in the poor effect of power network security improvement.For this reason, a power network attack prediction technology based on cellular automata model was proposed.A cellular automata model was built, regarding the cells in the cellular automata as power cells, a cell vitality value conversion rule was established and combined with the attack probability of attackers to predict the development and change of power cells.The power network attack was predicted according to the change trend of central power cells and neighboring power cells.The experimental result shows that, under the influence of time factors, the predicted attack node location of the proposed power network attack prediction technology based on cellular automata model is basically consistent with the original node, and the predicted load removal is always below 100 MW, the proposed technology is more effective.

Copyright Information
Authorized by: China Association for Science and Technology
Sponsored by: China Institute of Communications
Posts and Telecom Press Co., Ltd.
Publisher: Beijing Xintong Media Co., Ltd.
Editor-in-Chief: Chen Shanzhi
Editorial Director: Li Caishan
Address: F2, Beiyang Chenguang Building, Shunbatiao No.1 Courtyard, Fengtai District, Beijing, China
Postal Code: 100079
Tel: 010-53879277
Mailing Code: 2-397
ISSN 1000-0801
CN 11-2103/TN
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