Pub Date : 2023-11-01DOI: 10.23919/jcc.ea.2020-0684.202302
Yongkai Fan, Wanyu Zhang, Jianrong Bai, Xia Lei, Kuan-Ching Li
In the analysis of big data, deep learning is a crucial technique. Big data analysis tasks are typically carried out on the cloud since it offers strong computer capabilities and storage areas. Nevertheless, there is a contradiction between the open nature of the cloud and the demand that data owners maintain their privacy. To use cloud resources for privacy-preserving data training, a viable method must be found. A privacy-preserving deep learning model (PPDLM) is suggested in this research to address this preserving issue. To preserve data privacy, we first encrypted the data using homomorphic encryption (HE) approach. Moreover, the deep learning algorithm's activation function—the sigmoid function—uses the least-squares method to process nonaddition and non-multiplication operations that are not allowed by homomorphic. Finally, experimental results show that PPDLM has a significant effect on the protection of data privacy information. Compared with Non-Privacy Preserving Deep Learning Model (NPPDLM), PPDLM has higher computational efficiency.
{"title":"Privacy-preserving deep learning on big data in cloud","authors":"Yongkai Fan, Wanyu Zhang, Jianrong Bai, Xia Lei, Kuan-Ching Li","doi":"10.23919/jcc.ea.2020-0684.202302","DOIUrl":"https://doi.org/10.23919/jcc.ea.2020-0684.202302","url":null,"abstract":"In the analysis of big data, deep learning is a crucial technique. Big data analysis tasks are typically carried out on the cloud since it offers strong computer capabilities and storage areas. Nevertheless, there is a contradiction between the open nature of the cloud and the demand that data owners maintain their privacy. To use cloud resources for privacy-preserving data training, a viable method must be found. A privacy-preserving deep learning model (PPDLM) is suggested in this research to address this preserving issue. To preserve data privacy, we first encrypted the data using homomorphic encryption (HE) approach. Moreover, the deep learning algorithm's activation function—the sigmoid function—uses the least-squares method to process nonaddition and non-multiplication operations that are not allowed by homomorphic. Finally, experimental results show that PPDLM has a significant effect on the protection of data privacy information. Compared with Non-Privacy Preserving Deep Learning Model (NPPDLM), PPDLM has higher computational efficiency.","PeriodicalId":9814,"journal":{"name":"China Communications","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68734715","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 : 2023-11-01DOI: 10.23919/jcc.fa.2022-0509.202311
Xiuzhang Yang, Guojun Peng, Dongni Zhang, Yuhang Gao, Chenguang Li
PowerShell has been widely deployed in fileless malware and advanced persistent threat (APT) attacks due to its high stealthiness and live-off-the-land technique. However, existing works mainly focus on deobfuscation and malicious detection, lacking the malicious PowerShell families classification and behavior analysis. Moreover, the state-of-the-art methods fail to capture fine-grained features and semantic relationships, resulting in low robustness and accuracy. To this end, we propose PowerDetector, a novel malicious PowerShell script detector based on multimodal semantic fusion and deep learning. Specifically, we design four feature extraction methods to extract key features from character, token, abstract syntax tree (AST), and semantic knowledge graph. Then, we intelligently design four embeddings (i.e., Char2Vec, Token2Vec, AST2Vec, and Rela2Vec) and construct a multi-modal fusion algorithm to concatenate feature vectors from different views. Finally, we propose a combined model based on transformer and CNN-BiLSTM to implement PowerShell family detection. Our experiments with five types of PowerShell attacks show that PowerDetector can accurately detect various obfuscated and stealth PowerShell scripts, with a 0.9402 precision, a 0.9358 recall, and a 0.9374 F-score. Furthermore, through single-modal and multi-modal comparison experiments, we demonstrate that PowerDetector's multi-modal embedding and deep learning model can achieve better accuracy and even identify more unknown attacks.
{"title":"PowerDetector: Malicious PowerShell script family classification based on multi-modal semantic fusion and deep learning","authors":"Xiuzhang Yang, Guojun Peng, Dongni Zhang, Yuhang Gao, Chenguang Li","doi":"10.23919/jcc.fa.2022-0509.202311","DOIUrl":"https://doi.org/10.23919/jcc.fa.2022-0509.202311","url":null,"abstract":"PowerShell has been widely deployed in fileless malware and advanced persistent threat (APT) attacks due to its high stealthiness and live-off-the-land technique. However, existing works mainly focus on deobfuscation and malicious detection, lacking the malicious PowerShell families classification and behavior analysis. Moreover, the state-of-the-art methods fail to capture fine-grained features and semantic relationships, resulting in low robustness and accuracy. To this end, we propose PowerDetector, a novel malicious PowerShell script detector based on multimodal semantic fusion and deep learning. Specifically, we design four feature extraction methods to extract key features from character, token, abstract syntax tree (AST), and semantic knowledge graph. Then, we intelligently design four embeddings (i.e., Char2Vec, Token2Vec, AST2Vec, and Rela2Vec) and construct a multi-modal fusion algorithm to concatenate feature vectors from different views. Finally, we propose a combined model based on transformer and CNN-BiLSTM to implement PowerShell family detection. Our experiments with five types of PowerShell attacks show that PowerDetector can accurately detect various obfuscated and stealth PowerShell scripts, with a 0.9402 precision, a 0.9358 recall, and a 0.9374 F-score. Furthermore, through single-modal and multi-modal comparison experiments, we demonstrate that PowerDetector's multi-modal embedding and deep learning model can achieve better accuracy and even identify more unknown attacks.","PeriodicalId":9814,"journal":{"name":"China Communications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135609007","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}
In this paper, an integrated substrate gap waveguide (ISGW) filtering antenna is proposed at millimeter wave band, whose surface wave and spurious modes are simultaneously suppressed. A second-order filtering response is obtained through a coupling feeding scheme using one uniform impedance resonator (UIR) and two stepped-impedance resonators (SIRs). To increase the stopband width of the antenna, the spurious modes are suppressed by selecting the appropriate sizes of the ISGW unit cell. Furthermore, the ISGW is implemented to improve the radiation performance of the antenna by alleviating the propagation of surface wave. And an equivalent circuit is investigated to reveal the working principle of ISGW. To demonstrate this methodology, an ISGW filtering antenna operating at a center frequency of 25 GHz is designed, fabricated, and measured. The results show that the antenna achieves a stopband width of 1.6 f 0 (center frequency), an out-of-band suppression level of 21 dB, and a peak realized gain of 8.5 dBi.
{"title":"An ISGW filtering antenna with spurious modes and surface wave suppression for millimeter wave communications","authors":"Lihui Wang, Dongya Shen, Qiuhua Lin, Zhiyong Luo, Wenjian Wang, Jianpei Chen, Zhao Gao, Wei Zhang","doi":"10.23919/jcc.fa.2023-0255.202311","DOIUrl":"https://doi.org/10.23919/jcc.fa.2023-0255.202311","url":null,"abstract":"In this paper, an integrated substrate gap waveguide (ISGW) filtering antenna is proposed at millimeter wave band, whose surface wave and spurious modes are simultaneously suppressed. A second-order filtering response is obtained through a coupling feeding scheme using one uniform impedance resonator (UIR) and two stepped-impedance resonators (SIRs). To increase the stopband width of the antenna, the spurious modes are suppressed by selecting the appropriate sizes of the ISGW unit cell. Furthermore, the ISGW is implemented to improve the radiation performance of the antenna by alleviating the propagation of surface wave. And an equivalent circuit is investigated to reveal the working principle of ISGW. To demonstrate this methodology, an ISGW filtering antenna operating at a center frequency of 25 GHz is designed, fabricated, and measured. The results show that the antenna achieves a stopband width of 1.6 f <inf xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">0</inf> (center frequency), an out-of-band suppression level of 21 dB, and a peak realized gain of 8.5 dBi.","PeriodicalId":9814,"journal":{"name":"China Communications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135610543","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 : 2023-11-01DOI: 10.23919/jcc.ea.2020-0701.202302
Yuchen Zhou, Jian Chen, Lu Lyu, Bingtao He
To promote the application of edge computing in wireless blockchain networks, this paper presents a business ecosystem, where edge computing is introduced to assist blockchain users in implementing the mining process. This paper exploits resource trading and miner competition to enable secure and efficient transactions in the presented business ecosystem. The resource trading problem is formulated as a Stackelberg game between miner candidates and edge computing servers, where computing, caching, and communication resources are jointly optimized to maximize the potential profit. Partial offloading is introduced to further enhance the system performance when compared with the existing work. We analyze the existence and uniqueness of the Nash equilibrium and Stackelberg equilibrium. Based on the optimization result, winners are selected from the set of miner candidates by bidding and constitute the mining network. Simulation results demonstrate that the proposal is able to improve the social welfare of blockchain miners, thus stimulating more blockchain users to join the mining network.
{"title":"Resource trading and miner competition in wireless blockchain networks with edge computing","authors":"Yuchen Zhou, Jian Chen, Lu Lyu, Bingtao He","doi":"10.23919/jcc.ea.2020-0701.202302","DOIUrl":"https://doi.org/10.23919/jcc.ea.2020-0701.202302","url":null,"abstract":"To promote the application of edge computing in wireless blockchain networks, this paper presents a business ecosystem, where edge computing is introduced to assist blockchain users in implementing the mining process. This paper exploits resource trading and miner competition to enable secure and efficient transactions in the presented business ecosystem. The resource trading problem is formulated as a Stackelberg game between miner candidates and edge computing servers, where computing, caching, and communication resources are jointly optimized to maximize the potential profit. Partial offloading is introduced to further enhance the system performance when compared with the existing work. We analyze the existence and uniqueness of the Nash equilibrium and Stackelberg equilibrium. Based on the optimization result, winners are selected from the set of miner candidates by bidding and constitute the mining network. Simulation results demonstrate that the proposal is able to improve the social welfare of blockchain miners, thus stimulating more blockchain users to join the mining network.","PeriodicalId":9814,"journal":{"name":"China Communications","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68734779","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 : 2023-11-01DOI: 10.23919/jcc.ea.2022-0528.202302
Mao Xu, Guanjun Xu, Youran Dong, Weizhi Wang, Qinyu Zhang, Zhaohui Song
Free space optical (FSO) communication has recently aroused great interest in academia due to its unique features, such as large transmission band, high data rates, and strong anti-electromagnetic interference. With the aim of evaluating the performance of an FSO communication system and extending the line-of-sight transmission distance, we propose an unmanned aerial vehicle (UAV)-assisted dual-hop FSO communication system equipped with amplify-and-forward protocol at the relay node. Specifically, we consider impairments of atmospheric absorption, pointing errors, atmospheric turbulence, and link interruptions due to angle-of-arrival fluctuations in the relay system. The Gamma-Gamma and Malaga distributions are used to model the influence of atmospheric turbulence on the source-to-UAV and UAV-to-destination links, respectively. We derive closed-form expressions of the probability density function (PDF) and cumulative distribution function (CDF) for the proposed communication system, in terms of the Meijer-G function. Based on the precise PDF and CDF, analytical expressions for the outage probability, average bit error rate, and ergodic capacity are proposed with the aid of the extended generalized bivariate Fox's H function. Finally, we show that there is a match between the analytical results and numerical results, and we analyze the influence of the system and channel parameters on the performance.
{"title":"UAV-assisted FSO communication system with amplify-and-forward protocol under AOA fluctuations: A performance analysis","authors":"Mao Xu, Guanjun Xu, Youran Dong, Weizhi Wang, Qinyu Zhang, Zhaohui Song","doi":"10.23919/jcc.ea.2022-0528.202302","DOIUrl":"https://doi.org/10.23919/jcc.ea.2022-0528.202302","url":null,"abstract":"Free space optical (FSO) communication has recently aroused great interest in academia due to its unique features, such as large transmission band, high data rates, and strong anti-electromagnetic interference. With the aim of evaluating the performance of an FSO communication system and extending the line-of-sight transmission distance, we propose an unmanned aerial vehicle (UAV)-assisted dual-hop FSO communication system equipped with amplify-and-forward protocol at the relay node. Specifically, we consider impairments of atmospheric absorption, pointing errors, atmospheric turbulence, and link interruptions due to angle-of-arrival fluctuations in the relay system. The Gamma-Gamma and Malaga distributions are used to model the influence of atmospheric turbulence on the source-to-UAV and UAV-to-destination links, respectively. We derive closed-form expressions of the probability density function (PDF) and cumulative distribution function (CDF) for the proposed communication system, in terms of the Meijer-G function. Based on the precise PDF and CDF, analytical expressions for the outage probability, average bit error rate, and ergodic capacity are proposed with the aid of the extended generalized bivariate Fox's H function. Finally, we show that there is a match between the analytical results and numerical results, and we analyze the influence of the system and channel parameters on the performance.","PeriodicalId":9814,"journal":{"name":"China Communications","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68734868","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 : 2023-11-01DOI: 10.23919/jcc.fa.2023-0321.202311
Ran Liu, Daniel N. Aloi
Vehicle-to-Everything (V2X) communications will be an essential part of the technology in future autonomous drive decision systems. A fundamental procedure is to establish a robust communication channel between end-to-end devices. Due to the antenna placed at different positions on vehicles, the existing cellular electro-magnetic (EM) wave propagation modelling does not fit properly for V2X direct communication application. In order to figure out a feasible understanding of this problem, this paper focuses on the propagation channel analysis in a rural Vehicle-to-Vehicle (V2V) scenario for vehicular communication with antenna position experiments at different heights. By adopting the ray-tracing algorithm, a rural scenario simulation model is built up via the use of a commercial-off-the-shelf (COTS) EM modelling software package, that computes the path loss received power and delay spread for a given propagation channel. Next, a real-world vehicle measurement campaign was performed to verify the simulation results. The simulated and measured receiver power was in good agreement with each other, and the results of this study considered two antenna types located at three different relative heights between the two vehicles. This research provides constructive guidance for the V2V antenna characteristics, antenna placement and vehicle communication channel analysis.
{"title":"A rigorous analysis of vehicle-to-vehicle range performance in a rural channel propagation scenario as a function of antenna type and location via simulation and field trails","authors":"Ran Liu, Daniel N. Aloi","doi":"10.23919/jcc.fa.2023-0321.202311","DOIUrl":"https://doi.org/10.23919/jcc.fa.2023-0321.202311","url":null,"abstract":"Vehicle-to-Everything (V2X) communications will be an essential part of the technology in future autonomous drive decision systems. A fundamental procedure is to establish a robust communication channel between end-to-end devices. Due to the antenna placed at different positions on vehicles, the existing cellular electro-magnetic (EM) wave propagation modelling does not fit properly for V2X direct communication application. In order to figure out a feasible understanding of this problem, this paper focuses on the propagation channel analysis in a rural Vehicle-to-Vehicle (V2V) scenario for vehicular communication with antenna position experiments at different heights. By adopting the ray-tracing algorithm, a rural scenario simulation model is built up via the use of a commercial-off-the-shelf (COTS) EM modelling software package, that computes the path loss received power and delay spread for a given propagation channel. Next, a real-world vehicle measurement campaign was performed to verify the simulation results. The simulated and measured receiver power was in good agreement with each other, and the results of this study considered two antenna types located at three different relative heights between the two vehicles. This research provides constructive guidance for the V2V antenna characteristics, antenna placement and vehicle communication channel analysis.","PeriodicalId":9814,"journal":{"name":"China Communications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135609362","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 : 2023-11-01DOI: 10.23919/jcc.ea.2022-0006.202302
Yongan Guo, Yuao Wang, Qijie Qian
The demand for the Internet of Everything has slowed down network routing efficiency. Traditional routing policies rely on manual configuration, which has limitations and adversely affects network performance. In this paper, we propose an Internet of Things (IoT) Intelligent Edge Network Routing (ENIR) architecture. ENIR uses deep reinforcement learning (DRL) to simulate human learning of empirical knowledge and an intelligent routing closed-loop control mechanism for real-time interaction with the network environment. According to the network demand and environmental conditions, the method can dynamically adjust network resources and perform intelligent routing optimization. It uses blockchain technology to share network knowledge and global optimization of network routing. The intelligent routing method uses the deep deterministic policy gradient (DDPG) algorithm. Our simulation results show that ENIR provides significantly better link utilization and transmission delay performance than various routing methods (e.g., open shortest path first, routing based on Q-learning and DRL-based control framework for traffic engineering).
{"title":"Intelligent edge network routing architecture with blockchain for the IoT","authors":"Yongan Guo, Yuao Wang, Qijie Qian","doi":"10.23919/jcc.ea.2022-0006.202302","DOIUrl":"https://doi.org/10.23919/jcc.ea.2022-0006.202302","url":null,"abstract":"The demand for the Internet of Everything has slowed down network routing efficiency. Traditional routing policies rely on manual configuration, which has limitations and adversely affects network performance. In this paper, we propose an Internet of Things (IoT) Intelligent Edge Network Routing (ENIR) architecture. ENIR uses deep reinforcement learning (DRL) to simulate human learning of empirical knowledge and an intelligent routing closed-loop control mechanism for real-time interaction with the network environment. According to the network demand and environmental conditions, the method can dynamically adjust network resources and perform intelligent routing optimization. It uses blockchain technology to share network knowledge and global optimization of network routing. The intelligent routing method uses the deep deterministic policy gradient (DDPG) algorithm. Our simulation results show that ENIR provides significantly better link utilization and transmission delay performance than various routing methods (e.g., open shortest path first, routing based on Q-learning and DRL-based control framework for traffic engineering).","PeriodicalId":9814,"journal":{"name":"China Communications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136018467","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 : 2023-11-01DOI: 10.23919/jcc.ea.2022-0183.202302
Shuchao Mi, Jianyong Zhang, Fengju Fan, Baorui Yan, Muguang Wang
This paper proposes the alternating direction method of multipliers-based infinity-norm (ADMIN) with threshold (ADMIN-T) and with percentage (ADMIN-P) detection algorithms, which make full use of the distribution of the signal to interference plus noise ratio (SINR) for an uplink massive MIMO system. The ADMIN-T and ADMIN-P detection algorithms are improved visions of the ADMIN detection algorithm, in which an appropriate SINR threshold in the ADMIN-T detection algorithm and a certain percentage in the ADMIN-P detection algorithm are designed to reduce the overall computational complexity. The detected symbols are divided into two parts by the SINR threshold which is based on the cumulative probability density function (CDF) of SINR and a percentage, respectively. The symbols in higher SINR part are detected by MMSE. The interference of these symbols is then cancelled by successive interference cancellation (SIC). Afterwards the remaining symbols with low SINR are iteratively detected by ADMIN. The simulation results show that the ADMIIN-T and the ADMIN-P detection algorithms provide a significant performance gain compared with some recently proposed detection algorithms. In addition, the computational complexity of ADMIN-T and ADMIN-P are significantly reduced. Furthermore, in the case of same number of transceiver antennas, the proposed algorithms have a higher performance compared with the case of asymmetric transceiver antennas.
{"title":"Low complexity detection algorithms based on ADMIN for massive MIMO","authors":"Shuchao Mi, Jianyong Zhang, Fengju Fan, Baorui Yan, Muguang Wang","doi":"10.23919/jcc.ea.2022-0183.202302","DOIUrl":"https://doi.org/10.23919/jcc.ea.2022-0183.202302","url":null,"abstract":"This paper proposes the alternating direction method of multipliers-based infinity-norm (ADMIN) with threshold (ADMIN-T) and with percentage (ADMIN-P) detection algorithms, which make full use of the distribution of the signal to interference plus noise ratio (SINR) for an uplink massive MIMO system. The ADMIN-T and ADMIN-P detection algorithms are improved visions of the ADMIN detection algorithm, in which an appropriate SINR threshold in the ADMIN-T detection algorithm and a certain percentage in the ADMIN-P detection algorithm are designed to reduce the overall computational complexity. The detected symbols are divided into two parts by the SINR threshold which is based on the cumulative probability density function (CDF) of SINR and a percentage, respectively. The symbols in higher SINR part are detected by MMSE. The interference of these symbols is then cancelled by successive interference cancellation (SIC). Afterwards the remaining symbols with low SINR are iteratively detected by ADMIN. The simulation results show that the ADMIIN-T and the ADMIN-P detection algorithms provide a significant performance gain compared with some recently proposed detection algorithms. In addition, the computational complexity of ADMIN-T and ADMIN-P are significantly reduced. Furthermore, in the case of same number of transceiver antennas, the proposed algorithms have a higher performance compared with the case of asymmetric transceiver antennas.","PeriodicalId":9814,"journal":{"name":"China Communications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136102771","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}
In this paper, a 5G wideband power amplifier (PA) with bandpass filtering response is synthesized using a bandwidth-extended bandpass filter as the matching network (MN). In this structure, the bandwidth (θC) is defined as a variable in the closed-form equations provided by the microstrip bandpass filter. It can be extended over a wide range only by changing the characteristic impedances of the structure. Different from the other wideband MNs, the extension of bandwidth does not increase the complexity of the structure (order n is fixed). In addition, based on the bandwidth-extended structure, the wideband design of bandpass filtering PA is not limited to the fixed bandwidth of the specific filter structure. The theoretical analysis of the MN and the design flow of the PA are provided in this design. The fabricated bandpass filtering PA can support almost one-octave bandwidth (2–3.8 GHz), covering the two 5G bands (n41 and n78). The drain efficiency of 47%–60% and output power higher than 40 dBm are measured. Good frequency selectivity in S-parameter measurements can be observed.
{"title":"5G wideband bandpass filtering power amplifiers based on a bandwidth-extended bandpass matching network","authors":"Weimin Wang, Hongmin Zhao, Yongle Wu, Xiaopan Chen","doi":"10.23919/jcc.ea.2022-0349.202302","DOIUrl":"https://doi.org/10.23919/jcc.ea.2022-0349.202302","url":null,"abstract":"In this paper, a 5G wideband power amplifier (PA) with bandpass filtering response is synthesized using a bandwidth-extended bandpass filter as the matching network (MN). In this structure, the bandwidth (θC) is defined as a variable in the closed-form equations provided by the microstrip bandpass filter. It can be extended over a wide range only by changing the characteristic impedances of the structure. Different from the other wideband MNs, the extension of bandwidth does not increase the complexity of the structure (order n is fixed). In addition, based on the bandwidth-extended structure, the wideband design of bandpass filtering PA is not limited to the fixed bandwidth of the specific filter structure. The theoretical analysis of the MN and the design flow of the PA are provided in this design. The fabricated bandpass filtering PA can support almost one-octave bandwidth (2–3.8 GHz), covering the two 5G bands (n41 and n78). The drain efficiency of 47%–60% and output power higher than 40 dBm are measured. Good frequency selectivity in S-parameter measurements can be observed.","PeriodicalId":9814,"journal":{"name":"China Communications","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68735189","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 : 2023-11-01DOI: 10.23919/jcc.ea.2022-0372.202302
Ying Chen, Wei Gu, Jiajie Xu, Yongchao Zhang, Geyong Min
Limited by battery and computing resources, the computing-intensive tasks generated by Internet of Things (IoT) devices cannot be processed all by themselves. Mobile edge computing (MEC) is a suitable solution for this problem, and the generated tasks can be offloaded from IoT devices to MEC. In this paper, we study the problem of dynamic task offloading for digital twin-empowered MEC. Digital twin techniques are applied to provide information of environment and share the training data of agent deployed on IoT devices. We formulate the task offloading problem with the goal of maximizing the energy efficiency and the workload balance among the ESs. Then, we reformulate the problem as an MDP problem and design DRL-based energy efficient task offloading (DEETO) algorithm to solve it. Comparative experiments are carried out which show the superiority of our DEETO algorithm in improving energy efficiency and balancing the workload.
{"title":"Dynamic task offloading for digital twin-empowered mobile edge computing via deep reinforcement learning","authors":"Ying Chen, Wei Gu, Jiajie Xu, Yongchao Zhang, Geyong Min","doi":"10.23919/jcc.ea.2022-0372.202302","DOIUrl":"https://doi.org/10.23919/jcc.ea.2022-0372.202302","url":null,"abstract":"Limited by battery and computing resources, the computing-intensive tasks generated by Internet of Things (IoT) devices cannot be processed all by themselves. Mobile edge computing (MEC) is a suitable solution for this problem, and the generated tasks can be offloaded from IoT devices to MEC. In this paper, we study the problem of dynamic task offloading for digital twin-empowered MEC. Digital twin techniques are applied to provide information of environment and share the training data of agent deployed on IoT devices. We formulate the task offloading problem with the goal of maximizing the energy efficiency and the workload balance among the ESs. Then, we reformulate the problem as an MDP problem and design DRL-based energy efficient task offloading (DEETO) algorithm to solve it. Comparative experiments are carried out which show the superiority of our DEETO algorithm in improving energy efficiency and balancing the workload.","PeriodicalId":9814,"journal":{"name":"China Communications","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68735263","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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