Pub Date : 2023-08-01DOI: 10.23919/jcc.fa.2022-0496.202308
Xinxing Zheng, Yu Zhao, Joohyun Lee, Wei Chen
Due to the fading characteristics of wireless channels and the burstiness of data traffic, how to deal with congestion in Ad-hoc networks with effective algorithms is still open and challenging. In this paper, we focus on enabling congestion control to minimize network transmission delays through flexible power control. To effectively solve the congestion problem, we propose a distributed cross-layer scheduling algorithm, which is empowered by graph-based multi-agent deep reinforcement learning. The transmit power is adaptively adjusted in real-time by our algorithm based only on local information (i.e., channel state information and queue length) and local communication (i.e., information exchanged with neighbors). Moreover, the training complexity of the algorithm is low due to the regional cooperation based on the graph attention network. In the evaluation, we show that our algorithm can reduce the transmission delay of data flow under severe signal interference and drastically changing channel states, and demonstrate the adaptability and stability in different topologies. The method is general and can be extended to various types of topologies.
{"title":"Multi-agent deep reinforcement learning for cross-layer scheduling in mobile ad-hoc networks","authors":"Xinxing Zheng, Yu Zhao, Joohyun Lee, Wei Chen","doi":"10.23919/jcc.fa.2022-0496.202308","DOIUrl":"https://doi.org/10.23919/jcc.fa.2022-0496.202308","url":null,"abstract":"Due to the fading characteristics of wireless channels and the burstiness of data traffic, how to deal with congestion in Ad-hoc networks with effective algorithms is still open and challenging. In this paper, we focus on enabling congestion control to minimize network transmission delays through flexible power control. To effectively solve the congestion problem, we propose a distributed cross-layer scheduling algorithm, which is empowered by graph-based multi-agent deep reinforcement learning. The transmit power is adaptively adjusted in real-time by our algorithm based only on local information (i.e., channel state information and queue length) and local communication (i.e., information exchanged with neighbors). Moreover, the training complexity of the algorithm is low due to the regional cooperation based on the graph attention network. In the evaluation, we show that our algorithm can reduce the transmission delay of data flow under severe signal interference and drastically changing channel states, and demonstrate the adaptability and stability in different topologies. The method is general and can be extended to various types of topologies.","PeriodicalId":9814,"journal":{"name":"China Communications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136375580","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-05DOI: 10.23919/JCC.fa.2023-0056.202308
Yuntao Wang, Zhou Su
In commercial unmanned aerial vehicle (UAV) applications, one of the main restrictions is UAVs' limited battery endurance when executing persistent tasks. With the mature of wireless power transfer (WPT) technologies, by leveraging ground vehicles mounted with WPT facilities on their proofs, we propose a mobile and collaborative recharging scheme for UAVs in an on-demand manner. Specifically, we first present a novel air-ground cooperative UAV recharging framework, where ground vehicles cooperatively share their idle wireless chargers to UAVs and a swarm of UAVs in the task area compete to get recharging services. Considering the mobility dynamics and energy competitions, we formulate an energy scheduling problem for UAVs and vehicles under practical constraints. A fair online auction-based solution with low complexity is also devised to allocate and price idle wireless chargers on vehicular proofs in real time. We rigorously prove that the proposed scheme is strategy-proof, envy-free, and produces stable allocation outcomes. The first property enforces that truthful bidding is the dominant strategy for participants, the second ensures that no user is better off by exchanging his allocation with another user when the auction ends, while the third guarantees the matching stability between UAVs and UGVs. Extensive simulations validate that the proposed scheme outperforms benchmarks in terms of energy allocation efficiency and UAV's utility.
{"title":"An envy-free online UAV charging scheme with vehicle-mounted mobile wireless chargers","authors":"Yuntao Wang, Zhou Su","doi":"10.23919/JCC.fa.2023-0056.202308","DOIUrl":"https://doi.org/10.23919/JCC.fa.2023-0056.202308","url":null,"abstract":"In commercial unmanned aerial vehicle (UAV) applications, one of the main restrictions is UAVs' limited battery endurance when executing persistent tasks. With the mature of wireless power transfer (WPT) technologies, by leveraging ground vehicles mounted with WPT facilities on their proofs, we propose a mobile and collaborative recharging scheme for UAVs in an on-demand manner. Specifically, we first present a novel air-ground cooperative UAV recharging framework, where ground vehicles cooperatively share their idle wireless chargers to UAVs and a swarm of UAVs in the task area compete to get recharging services. Considering the mobility dynamics and energy competitions, we formulate an energy scheduling problem for UAVs and vehicles under practical constraints. A fair online auction-based solution with low complexity is also devised to allocate and price idle wireless chargers on vehicular proofs in real time. We rigorously prove that the proposed scheme is strategy-proof, envy-free, and produces stable allocation outcomes. The first property enforces that truthful bidding is the dominant strategy for participants, the second ensures that no user is better off by exchanging his allocation with another user when the auction ends, while the third guarantees the matching stability between UAVs and UGVs. Extensive simulations validate that the proposed scheme outperforms benchmarks in terms of energy allocation efficiency and UAV's utility.","PeriodicalId":9814,"journal":{"name":"China Communications","volume":"20 1","pages":"89-102"},"PeriodicalIF":4.1,"publicationDate":"2023-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46455221","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-01DOI: 10.23919/JCC.2023.00.033
Ge Song, Xiaojie Fang, X. Sha
In this paper, we propose an extended hybrid carrier system based on the weighted fractional Fourier transform to ensure the reliability of wireless communication. The proposed scheme improves the dispersion and compensation capabilities of the hybrid carrier system for channel fading through the design of the signal power distribution, which has greatly reduced the probability of high-power distortion of the signal and improved the bit error rate performance as a result. Theoretical analysis has shown the superiority of the extended hybrid carrier system. With a lower cost of computational complexity increment, the proposed scheme obtains a performance improvement without occupying additional time-frequency physical resources. Compared with the existing hybrid carrier scheme, numerical simulation results have shown that the proposed extended hybrid carrier scheme has better anti-fading performance under the doubly-selective channel and improves the reliability of the wireless communication system effectively.
{"title":"Guaranteeing wireless communication reliability via an extended hybrid carrier system","authors":"Ge Song, Xiaojie Fang, X. Sha","doi":"10.23919/JCC.2023.00.033","DOIUrl":"https://doi.org/10.23919/JCC.2023.00.033","url":null,"abstract":"In this paper, we propose an extended hybrid carrier system based on the weighted fractional Fourier transform to ensure the reliability of wireless communication. The proposed scheme improves the dispersion and compensation capabilities of the hybrid carrier system for channel fading through the design of the signal power distribution, which has greatly reduced the probability of high-power distortion of the signal and improved the bit error rate performance as a result. Theoretical analysis has shown the superiority of the extended hybrid carrier system. With a lower cost of computational complexity increment, the proposed scheme obtains a performance improvement without occupying additional time-frequency physical resources. Compared with the existing hybrid carrier scheme, numerical simulation results have shown that the proposed extended hybrid carrier scheme has better anti-fading performance under the doubly-selective channel and improves the reliability of the wireless communication system effectively.","PeriodicalId":9814,"journal":{"name":"China Communications","volume":"20 1","pages":"192-202"},"PeriodicalIF":4.1,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44135645","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-01DOI: 10.23919/JCC.fa.2022-0732.202307
Laiding Zhao, Xun Zhu, Gengxin Zhang, Zhaowen Wang
The main geolocation technology currently used in COSPAS-SARSAT system is TDOA/FDOA or three-star TDOA, the principle is to determine the location of the signal source by using the difference in arrival time and frequency of the wireless signal between different receivers. Therefore, ground monitoring stations need to be equipped with more than two antenna receiving stations, and multiple satellites should be able to simultaneously relay the distress signal from the target source in order to achieve the geolocation function. However, when the ground receiving system has only one antenna receiving station, or the target source is in a heavily obscured environment, the ground side is unable to receive the forwarded signals from multiple satellites at the same time, which will make it impossible to locate. To address these problems, in this paper, a time-sharing single satellite geolocations method based on different orbits is proposed for the first time. This method uses one or several low-earth orbit satellites (LEO) and medium-earth orbit satellites (MEO) in the visible area, and the receiving station only needs one pair of receiving antennas to complete the positioning. It can effectively compensate for the shortcomings of the traditional TDOA using the same moment and have better positioning accuracy compared with the single satellite in the same orbit. Due to the limited experimental conditions, this paper tests the navigation satellite using different orbit time-sharing single satellite geolocations, and proves that the positioning method has high positioning accuracy and has certain promotion and application value.
{"title":"A positioning method and realization on single satellites in different orbits using TDOA","authors":"Laiding Zhao, Xun Zhu, Gengxin Zhang, Zhaowen Wang","doi":"10.23919/JCC.fa.2022-0732.202307","DOIUrl":"https://doi.org/10.23919/JCC.fa.2022-0732.202307","url":null,"abstract":"The main geolocation technology currently used in COSPAS-SARSAT system is TDOA/FDOA or three-star TDOA, the principle is to determine the location of the signal source by using the difference in arrival time and frequency of the wireless signal between different receivers. Therefore, ground monitoring stations need to be equipped with more than two antenna receiving stations, and multiple satellites should be able to simultaneously relay the distress signal from the target source in order to achieve the geolocation function. However, when the ground receiving system has only one antenna receiving station, or the target source is in a heavily obscured environment, the ground side is unable to receive the forwarded signals from multiple satellites at the same time, which will make it impossible to locate. To address these problems, in this paper, a time-sharing single satellite geolocations method based on different orbits is proposed for the first time. This method uses one or several low-earth orbit satellites (LEO) and medium-earth orbit satellites (MEO) in the visible area, and the receiving station only needs one pair of receiving antennas to complete the positioning. It can effectively compensate for the shortcomings of the traditional TDOA using the same moment and have better positioning accuracy compared with the single satellite in the same orbit. Due to the limited experimental conditions, this paper tests the navigation satellite using different orbit time-sharing single satellite geolocations, and proves that the positioning method has high positioning accuracy and has certain promotion and application value.","PeriodicalId":9814,"journal":{"name":"China Communications","volume":"20 1","pages":"108-121"},"PeriodicalIF":4.1,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46899435","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-01DOI: 10.23919/JCC.2023.00.035
Tao Peng, Chao Yang, Peiliang Zuo, Xinyue Wang, Rongrong Qian, Wenbo Wang
Spectrum prediction plays an important role for the secondary user (SU) to utilize the shared spectrum resources. However, currently utilized prediction methods are not well applied to spectrum with high burstiness, as parameters of prediction models cannot be adjusted properly. This paper studies the prediction problem of bursty bands. Specifically, we first collect real WiFi transmission data in 2.4GHz Industrial, Scientific, Medical (ISM) band which is considered to have bursty characteristics. Feature analysis of the data indicates that the spectrum occupancy law of the data is time-variant, which suggests that the performance of commonly used single prediction model could be restricted. Considering that the match between diverse spectrum states and multiple prediction models may essentially improve the prediction performance, we then propose a deep-reinforcement learning based multilayer perceptron (DRL-MLP) method to address this matching problem. The state space of the method is composed of feature vectors, and each of the vectors contains multi-dimensional feature values. Meanwhile, the action space consists of several multilayer perceptrons (MLPs) that are trained on the basis of multiple classified data sets. We finally conduct experiments with the collected real data and simulations with generated data to verify the performance of the proposed method. The results demonstrate that the proposed method significantly outperforms the state-of-the-art methods in terms of the prediction accuracy.
{"title":"Deep reinforcement learning based spectrum prediction for bursty bands","authors":"Tao Peng, Chao Yang, Peiliang Zuo, Xinyue Wang, Rongrong Qian, Wenbo Wang","doi":"10.23919/JCC.2023.00.035","DOIUrl":"https://doi.org/10.23919/JCC.2023.00.035","url":null,"abstract":"Spectrum prediction plays an important role for the secondary user (SU) to utilize the shared spectrum resources. However, currently utilized prediction methods are not well applied to spectrum with high burstiness, as parameters of prediction models cannot be adjusted properly. This paper studies the prediction problem of bursty bands. Specifically, we first collect real WiFi transmission data in 2.4GHz Industrial, Scientific, Medical (ISM) band which is considered to have bursty characteristics. Feature analysis of the data indicates that the spectrum occupancy law of the data is time-variant, which suggests that the performance of commonly used single prediction model could be restricted. Considering that the match between diverse spectrum states and multiple prediction models may essentially improve the prediction performance, we then propose a deep-reinforcement learning based multilayer perceptron (DRL-MLP) method to address this matching problem. The state space of the method is composed of feature vectors, and each of the vectors contains multi-dimensional feature values. Meanwhile, the action space consists of several multilayer perceptrons (MLPs) that are trained on the basis of multiple classified data sets. We finally conduct experiments with the collected real data and simulations with generated data to verify the performance of the proposed method. The results demonstrate that the proposed method significantly outperforms the state-of-the-art methods in terms of the prediction accuracy.","PeriodicalId":9814,"journal":{"name":"China Communications","volume":"20 1","pages":"241-257"},"PeriodicalIF":4.1,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68734409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-01DOI: 10.23919/JCC.fa.2022-0680.202307
Yuanyuan Yao, Dengyang Dong, Sai Huang, Chunyu Pan, Shuo Chen, Xuehua Li
In order to achieve dependable and efficient data acquisition and transmission in the Internet of Remote Things (IoRT), we investigate the optimization scheme of IoRT data acquisition under the unmanned aerial vehicle (UAV)-low earth orbit (LEO) satellite integrated space-air-ground network, in which the UAV acquires data from massive Internet of Things (IoT) devices in special scenarios. To combine with the actual scenario, we consider two different data types, that is, delay-sensitive data and delay-tolerant data, the transmission mode is accordingly divided into two types. For delay-sensitive data, the data will be transmitted via the LEO satellite relay to the data center (DC) in real-time. For delay-tolerant data, the UAV will store and carry the data until the acquisition is completed, and then return to DC. Due to non-convexity and complexity of the formulated problem, a multi-dimensional optimization Rate Demand based Joint Optimization (RDJO) algorithm is proposed. The algorithm first uses successive convex approximation (SCA) technology to solve the non-convexity, and then based on the block coordinate descent (BCD) method, the data acquisition efficiency is maximized by jointly optimizing UAV deployment, the bandwidth allocation of IoRT devices, and the transmission power of the UAV. Finally, the proposed RDJO algorithm is compared with the conventional algorithms. Simulation consequences demonstrate that the efficiency of IoRT data acquisition can be greatly improved by multi-parameter optimization of the bandwidth allocation, UAV deployment and the transmission power.
{"title":"Optimization of the Internet of remote things data acquisition based on satellite UAV integrated network","authors":"Yuanyuan Yao, Dengyang Dong, Sai Huang, Chunyu Pan, Shuo Chen, Xuehua Li","doi":"10.23919/JCC.fa.2022-0680.202307","DOIUrl":"https://doi.org/10.23919/JCC.fa.2022-0680.202307","url":null,"abstract":"In order to achieve dependable and efficient data acquisition and transmission in the Internet of Remote Things (IoRT), we investigate the optimization scheme of IoRT data acquisition under the unmanned aerial vehicle (UAV)-low earth orbit (LEO) satellite integrated space-air-ground network, in which the UAV acquires data from massive Internet of Things (IoT) devices in special scenarios. To combine with the actual scenario, we consider two different data types, that is, delay-sensitive data and delay-tolerant data, the transmission mode is accordingly divided into two types. For delay-sensitive data, the data will be transmitted via the LEO satellite relay to the data center (DC) in real-time. For delay-tolerant data, the UAV will store and carry the data until the acquisition is completed, and then return to DC. Due to non-convexity and complexity of the formulated problem, a multi-dimensional optimization Rate Demand based Joint Optimization (RDJO) algorithm is proposed. The algorithm first uses successive convex approximation (SCA) technology to solve the non-convexity, and then based on the block coordinate descent (BCD) method, the data acquisition efficiency is maximized by jointly optimizing UAV deployment, the bandwidth allocation of IoRT devices, and the transmission power of the UAV. Finally, the proposed RDJO algorithm is compared with the conventional algorithms. Simulation consequences demonstrate that the efficiency of IoRT data acquisition can be greatly improved by multi-parameter optimization of the bandwidth allocation, UAV deployment and the transmission power.","PeriodicalId":9814,"journal":{"name":"China Communications","volume":"20 1","pages":"15-28"},"PeriodicalIF":4.1,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45747214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-01DOI: 10.23919/JCC.fa.2021-0825.202307
Nong Qu, Chao Wang, Zuxing Li, Fuqiang Liu
In highly dynamic and heterogeneous vehicular communication networks, it is challenging to efficiently utilize network resources and ensure demanding performance requirements of safety-related applications. This paper investigates machine-learning-assisted transmission design in a typical multi-user vehicle-to-vehicle (V2V) communication scenario. The transmission process proceeds sequentially along the discrete time steps, where several source nodes intend to deliver multiple different types of messages to their respective destinations within the same spectrum. Due to rapid movement of vehicles, real-time acquirement of channel knowledge and central coordination of all transmission actions are in general hard to realize. We consider applying multi-agent deep reinforcement learning (MADRL) to handle this issue. By transforming the transmission design problem into a stochastic game, a multi-agent proximal policy optimization (MAPPO) algorithm under a centralized training and decentralized execution framework is proposed such that each source decides its own transmission message type, power level, and data rate, based on local observations of the environment and feedback, to maximize its energy efficiency. Via simulations we show that our method achieves better performance over conventional methods.
{"title":"A transmission design in dynamic heterogeneous V2V networks through multi-agent deep reinforcement learning","authors":"Nong Qu, Chao Wang, Zuxing Li, Fuqiang Liu","doi":"10.23919/JCC.fa.2021-0825.202307","DOIUrl":"https://doi.org/10.23919/JCC.fa.2021-0825.202307","url":null,"abstract":"In highly dynamic and heterogeneous vehicular communication networks, it is challenging to efficiently utilize network resources and ensure demanding performance requirements of safety-related applications. This paper investigates machine-learning-assisted transmission design in a typical multi-user vehicle-to-vehicle (V2V) communication scenario. The transmission process proceeds sequentially along the discrete time steps, where several source nodes intend to deliver multiple different types of messages to their respective destinations within the same spectrum. Due to rapid movement of vehicles, real-time acquirement of channel knowledge and central coordination of all transmission actions are in general hard to realize. We consider applying multi-agent deep reinforcement learning (MADRL) to handle this issue. By transforming the transmission design problem into a stochastic game, a multi-agent proximal policy optimization (MAPPO) algorithm under a centralized training and decentralized execution framework is proposed such that each source decides its own transmission message type, power level, and data rate, based on local observations of the environment and feedback, to maximize its energy efficiency. Via simulations we show that our method achieves better performance over conventional methods.","PeriodicalId":9814,"journal":{"name":"China Communications","volume":"20 1","pages":"273-289"},"PeriodicalIF":4.1,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47982491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-01DOI: 10.23919/JCC.2023.00.032
Jinhao Du, Tao Yang, Sheping Shi, Xue Chen
Large-scale dense wavelength division multiplexing (DWDM) multi-channel performance monitoring is one of the indispensable technologies for the flexible optical networks. The existing Labelbased monitoring scheme requires expensive optical demultiplexing components/equipment to avoid the influence of stimulated Raman scattering (SRS), which is not only costly and bulky, but also could not monitor the wavelength channels simultaneously. In this paper, a low-cost, high-accuracy monitoring scheme based on Optical Label Method is proposed for DWDM networks, where the optical channel power and node identification (ID), as the main monitoring targets that both can indicate or evaluate the channel connection status, could be efficiently monitored. In the scheme, a novel digital signal processing (DSP) method of SRS mitigation is proposed and demonstrated, and an asynchronous code-division multiple access (A-CDMA) based digital label encoding and decoding method is adopted to distinguish the node ID so that channel initial added node can be accurately verified, thereby wavelength connection status can be reliably monitored by combining the channel power and node ID information. The simulation results show that each wavelength channel power and node ID can be accurately monitored only by low bandwidth photoelectric detector (PD) under the condition of 80 wavelengths and 10 spans at C-band.
{"title":"Optical label-based cost-effective DWDM optical network performance monitoring using low-bandwidth PD with novel SRS mitigation DSP","authors":"Jinhao Du, Tao Yang, Sheping Shi, Xue Chen","doi":"10.23919/JCC.2023.00.032","DOIUrl":"https://doi.org/10.23919/JCC.2023.00.032","url":null,"abstract":"Large-scale dense wavelength division multiplexing (DWDM) multi-channel performance monitoring is one of the indispensable technologies for the flexible optical networks. The existing Labelbased monitoring scheme requires expensive optical demultiplexing components/equipment to avoid the influence of stimulated Raman scattering (SRS), which is not only costly and bulky, but also could not monitor the wavelength channels simultaneously. In this paper, a low-cost, high-accuracy monitoring scheme based on Optical Label Method is proposed for DWDM networks, where the optical channel power and node identification (ID), as the main monitoring targets that both can indicate or evaluate the channel connection status, could be efficiently monitored. In the scheme, a novel digital signal processing (DSP) method of SRS mitigation is proposed and demonstrated, and an asynchronous code-division multiple access (A-CDMA) based digital label encoding and decoding method is adopted to distinguish the node ID so that channel initial added node can be accurately verified, thereby wavelength connection status can be reliably monitored by combining the channel power and node ID information. The simulation results show that each wavelength channel power and node ID can be accurately monitored only by low bandwidth photoelectric detector (PD) under the condition of 80 wavelengths and 10 spans at C-band.","PeriodicalId":9814,"journal":{"name":"China Communications","volume":"20 1","pages":"203-216"},"PeriodicalIF":4.1,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43065265","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-01DOI: 10.23919/JCC.2023.00.040
Xiaorong Zhu, Lingyu Zhao, Jiaming Cao, Jianhong Cai
Fault diagnosis of 5G networks faces the challenges of heavy reliance on human experience and insufficient fault samples and relevant monitoring data. The digital twin technology can realize the interaction between virtual space and physical space through the fusion of model and data, providing a new paradigm for fault diagnosis. In this paper, we first propose a network digital twin model and apply it to 5G network diagnosis. We then use an improved Average Wasserstein GAN with Gradient Penalty (AWGAN-GP) method to discover and predict failures in the twin network. Finally, we use XGBoost algorithm to locate the faults in physical network in real time. Extensive simulation results show that the proposed approach can significantly increase fault prediction and diagnosis accuracy in the case of a small number of labeled failure samples in 5G networks.
{"title":"Fault diagnosis of 5G networks based on digital twin model","authors":"Xiaorong Zhu, Lingyu Zhao, Jiaming Cao, Jianhong Cai","doi":"10.23919/JCC.2023.00.040","DOIUrl":"https://doi.org/10.23919/JCC.2023.00.040","url":null,"abstract":"Fault diagnosis of 5G networks faces the challenges of heavy reliance on human experience and insufficient fault samples and relevant monitoring data. The digital twin technology can realize the interaction between virtual space and physical space through the fusion of model and data, providing a new paradigm for fault diagnosis. In this paper, we first propose a network digital twin model and apply it to 5G network diagnosis. We then use an improved Average Wasserstein GAN with Gradient Penalty (AWGAN-GP) method to discover and predict failures in the twin network. Finally, we use XGBoost algorithm to locate the faults in physical network in real time. Extensive simulation results show that the proposed approach can significantly increase fault prediction and diagnosis accuracy in the case of a small number of labeled failure samples in 5G networks.","PeriodicalId":9814,"journal":{"name":"China Communications","volume":"20 1","pages":"175-191"},"PeriodicalIF":4.1,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47705354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-01DOI: 10.23919/JCC.fa.2022-0865.202307
Yuan-zhi He, Yuan Li, Hao Yin
In recent years, as giant satellite constellations grow rapidly worldwide, the co-existence between constellations has been widely concerned. In this paper, we overview the co-frequency interference (CFI) among the giant non-geostationary orbit (NGSO) constellations. Specifically, we first summarize the CFI scenario and evaluation index among different NGSO constellations. Based on statistics about NGSO constellation plans, we analyse the challenges in mitigation and analysis of CFI. Next, the CFI calculation methods and research progress are systematically sorted out from the aspects of interference risk analysis framework, numerical calculation and link construction. Then, the feasibility of interference mitigation technologies based on space, frequency domain isolation, power control, and interference alignment mitigation in the NGSO mega-constellation CFI scenario are further sorted out. Finally, we present promising directions for future research in CFI analysis and CFI avoidance.
{"title":"Co-frequency interference analysis and avoidance between NGSO constellations: Challenges, techniques, and trends","authors":"Yuan-zhi He, Yuan Li, Hao Yin","doi":"10.23919/JCC.fa.2022-0865.202307","DOIUrl":"https://doi.org/10.23919/JCC.fa.2022-0865.202307","url":null,"abstract":"In recent years, as giant satellite constellations grow rapidly worldwide, the co-existence between constellations has been widely concerned. In this paper, we overview the co-frequency interference (CFI) among the giant non-geostationary orbit (NGSO) constellations. Specifically, we first summarize the CFI scenario and evaluation index among different NGSO constellations. Based on statistics about NGSO constellation plans, we analyse the challenges in mitigation and analysis of CFI. Next, the CFI calculation methods and research progress are systematically sorted out from the aspects of interference risk analysis framework, numerical calculation and link construction. Then, the feasibility of interference mitigation technologies based on space, frequency domain isolation, power control, and interference alignment mitigation in the NGSO mega-constellation CFI scenario are further sorted out. Finally, we present promising directions for future research in CFI analysis and CFI avoidance.","PeriodicalId":9814,"journal":{"name":"China Communications","volume":"20 1","pages":"1-14"},"PeriodicalIF":4.1,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46470001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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