Pub Date : 2024-05-01DOI: 10.23919/JCC.ea.2021-0646.202401
Changhao Li, Sun Xue, Yan Lei, Cao Suzhi
The high-speed movement of satellites makes it not feasible to directly apply the mature routing scheme on the ground to the satellite network. DT-DVTR in the snapshot-based connection-oriented routing strategy is one of the representative solutions, but it still has room for improvement in terms of routing stability. In this paper, we propose an improved scheme for connection-oriented routing strategy named the Minimal Topology Change Routing based on Collaborative Rules (MTCR-CR). The MTCR-CR uses continuous time static topology snapshots based on satellite status to search for intersatellite link(ISL) construction solutions that meet the minimum number of topology changes to avoid route oscillations. The simulation results in Beidou-3 show that compared with DT-DVTR, MTCR-CR reduces the number of routing changes by about 92%, the number of path changes caused by routing changes is about 38%, and the rerouting time is reduced by approximately 47%. At the same time, in order to show our algorithm more comprehensively, the same experimental index test was also carried out on the Globalstar satellite constellation.
{"title":"MTCR-CR routing strategy for connection-oriented routing over satellite networks","authors":"Changhao Li, Sun Xue, Yan Lei, Cao Suzhi","doi":"10.23919/JCC.ea.2021-0646.202401","DOIUrl":"https://doi.org/10.23919/JCC.ea.2021-0646.202401","url":null,"abstract":"The high-speed movement of satellites makes it not feasible to directly apply the mature routing scheme on the ground to the satellite network. DT-DVTR in the snapshot-based connection-oriented routing strategy is one of the representative solutions, but it still has room for improvement in terms of routing stability. In this paper, we propose an improved scheme for connection-oriented routing strategy named the Minimal Topology Change Routing based on Collaborative Rules (MTCR-CR). The MTCR-CR uses continuous time static topology snapshots based on satellite status to search for intersatellite link(ISL) construction solutions that meet the minimum number of topology changes to avoid route oscillations. The simulation results in Beidou-3 show that compared with DT-DVTR, MTCR-CR reduces the number of routing changes by about 92%, the number of path changes caused by routing changes is about 38%, and the rerouting time is reduced by approximately 47%. At the same time, in order to show our algorithm more comprehensively, the same experimental index test was also carried out on the Globalstar satellite constellation.","PeriodicalId":9814,"journal":{"name":"China Communications","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141132563","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}
Directional modulation (DM) is one of the most promising secure communication techniques. However, when the eavesdropper is co-located with the legitimate receiver, the conventional DM has the disadvantages of weak anti-scanning capability, anti-deciphering capability, and low secrecy rate. In response to these problems, we propose a two-dimensional multi-term weighted fractional Fourier transform aided DM scheme, in which the legitimate receiver and the transmitter use different transform terms and transform orders to encrypt and decrypt the confidential information. In order to further lower the probability of being deciphered by an eavesdropper, we use the subblock partition method to convert the one-dimensional modulated signal vector into a two-dimensional signal matrix, increasing the confusion of the useful information. Numerical results demonstrate that the proposed DM scheme not only provides stronger anti-deciphering and anti-scanning capabilities but also improves the secrecy rate performance of the system.
{"title":"Security-enhanced directional modulation based on two-dimensional M-WFRFT","authors":"Zhuang Zhou, Junshan Luo, Shilian Wang, Guojiang Xia","doi":"10.23919/JCC.ja.2022-0491","DOIUrl":"https://doi.org/10.23919/JCC.ja.2022-0491","url":null,"abstract":"Directional modulation (DM) is one of the most promising secure communication techniques. However, when the eavesdropper is co-located with the legitimate receiver, the conventional DM has the disadvantages of weak anti-scanning capability, anti-deciphering capability, and low secrecy rate. In response to these problems, we propose a two-dimensional multi-term weighted fractional Fourier transform aided DM scheme, in which the legitimate receiver and the transmitter use different transform terms and transform orders to encrypt and decrypt the confidential information. In order to further lower the probability of being deciphered by an eavesdropper, we use the subblock partition method to convert the one-dimensional modulated signal vector into a two-dimensional signal matrix, increasing the confusion of the useful information. Numerical results demonstrate that the proposed DM scheme not only provides stronger anti-deciphering and anti-scanning capabilities but also improves the secrecy rate performance of the system.","PeriodicalId":9814,"journal":{"name":"China Communications","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141144162","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 : 2024-05-01DOI: 10.23919/JCC.ea.2022-0699.202401
Xiongyue Wu, Jianhua Tang, Marie Siew
The rapid development of emerging technologies, such as edge intelligence and digital twins, have added momentum towards the development of the Industrial Internet of Things (IIoT). However, the massive amount of data generated by the IIoT, coupled with heterogeneous computation capacity across IIoT devices, and users' data privacy concerns, have posed challenges towards achieving industrial edge intelligence (IEI). To achieve IEI, in this paper, we propose a semi-federated learning framework where a portion of the data with higher privacy is kept locally and a portion of the less private data can be potentially uploaded to the edge server. In addition, we leverage digital twins to overcome the problem of computation capacity heterogeneity of IIoT devices through the mapping of physical entities. We formulate a synchronization latency minimization problem which jointly optimizes edge association and the proportion of uploaded nonprivate data. As the joint problem is NP-hard and combinatorial and taking into account the reality of large-scale device training, we develop a multi-agent hybrid action deep reinforcement learning (DRL) algorithm to find the optimal solution. Simulation results show that our proposed DRL algorithm can reduce latency and have a better convergence performance for semi-federated learning compared to benchmark algorithms.
{"title":"Digital twin-assisted semi-federated learning framework for industrial edge intelligence","authors":"Xiongyue Wu, Jianhua Tang, Marie Siew","doi":"10.23919/JCC.ea.2022-0699.202401","DOIUrl":"https://doi.org/10.23919/JCC.ea.2022-0699.202401","url":null,"abstract":"The rapid development of emerging technologies, such as edge intelligence and digital twins, have added momentum towards the development of the Industrial Internet of Things (IIoT). However, the massive amount of data generated by the IIoT, coupled with heterogeneous computation capacity across IIoT devices, and users' data privacy concerns, have posed challenges towards achieving industrial edge intelligence (IEI). To achieve IEI, in this paper, we propose a semi-federated learning framework where a portion of the data with higher privacy is kept locally and a portion of the less private data can be potentially uploaded to the edge server. In addition, we leverage digital twins to overcome the problem of computation capacity heterogeneity of IIoT devices through the mapping of physical entities. We formulate a synchronization latency minimization problem which jointly optimizes edge association and the proportion of uploaded nonprivate data. As the joint problem is NP-hard and combinatorial and taking into account the reality of large-scale device training, we develop a multi-agent hybrid action deep reinforcement learning (DRL) algorithm to find the optimal solution. Simulation results show that our proposed DRL algorithm can reduce latency and have a better convergence performance for semi-federated learning compared to benchmark algorithms.","PeriodicalId":9814,"journal":{"name":"China Communications","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141141116","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}
The flexibility of unmanned aerial vehicles (UAVs) allows them to be quickly deployed to support ground users. Intelligent reflecting surface (IRS) can reflect the incident signal and form passive beamforming to enhance the signal in the specific direction. Motivated by the promising benefits of both technologies, we consider a new scenario in this paper where a UAV uses non-orthogonal multiple access to serve multiple users with IRS. According to their distance to the UAV, the users are divided into the close users and remote users. The UAV hovers above the close users due to their higher rate requirement, while the IRS is deployed near the remote users to enhance their received power. We aim at minimizing the transmit power of UAV by jointly optimizing the beamforming of UAV and the phase shift of IRS while ensuring the decoding requirement. However, the problem is non-convex. Therefore, we decompose it into two sub-problems, including the transmit beamforming optimization and phase shift optimization, which are transformed into second-order cone programming and semidefinite programming, respectively. We propose an iterative algorithm to solve the two sub-problems alternatively. Simulation results prove the effectiveness of the proposed scheme in minimizing the transmit power of UAV.
{"title":"Transmit power minimization for IRS-assisted NOMA-UAV networks","authors":"Zhao Chen, Xiaowei Pang, Tang Jie, Mingqian Liu, Zhao Nan, Xiuyin Zhang, Xianbin Wang","doi":"10.23919/JCC.ea.2021-0783.202401","DOIUrl":"https://doi.org/10.23919/JCC.ea.2021-0783.202401","url":null,"abstract":"The flexibility of unmanned aerial vehicles (UAVs) allows them to be quickly deployed to support ground users. Intelligent reflecting surface (IRS) can reflect the incident signal and form passive beamforming to enhance the signal in the specific direction. Motivated by the promising benefits of both technologies, we consider a new scenario in this paper where a UAV uses non-orthogonal multiple access to serve multiple users with IRS. According to their distance to the UAV, the users are divided into the close users and remote users. The UAV hovers above the close users due to their higher rate requirement, while the IRS is deployed near the remote users to enhance their received power. We aim at minimizing the transmit power of UAV by jointly optimizing the beamforming of UAV and the phase shift of IRS while ensuring the decoding requirement. However, the problem is non-convex. Therefore, we decompose it into two sub-problems, including the transmit beamforming optimization and phase shift optimization, which are transformed into second-order cone programming and semidefinite programming, respectively. We propose an iterative algorithm to solve the two sub-problems alternatively. Simulation results prove the effectiveness of the proposed scheme in minimizing the transmit power of UAV.","PeriodicalId":9814,"journal":{"name":"China Communications","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141142555","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 : 2024-05-01DOI: 10.23919/JCC.ja.2023-0165
MohammadBagher Tavasoli, Hossein Saidi, Ali Ghiasian
One of the challenges of Information-centric Networking (ICN) is finding the optimal location for caching content and processing users' requests. In this paper, we address this challenge by leveraging Software-defined Networking (SDN) for efficient ICN management. To achieve this, we formulate the problem as a mixed-integer nonlinear programming (MINLP) model, incorporating caching, routing, and load balancing decisions. We explore two distinct scenarios to tackle the problem. Firstly, we solve the problem in an offline mode using the GAMS environment, assuming a stable network state to demonstrate the superior performance of the cache-enabled network compared to non-cache networks. Subsequently, we investigate the problem in an online mode where the network state dynamically changes over time. Given the computational complexity associated with MINLP, we propose the software-defined caching, routing, and load balancing (SDCRL) algorithm as an efficient and scalable solution. Our evaluation demonstrates that the SDCRL algorithm significantly reduces computational time while maintaining results that closely resemble those achieved by GAMS.
{"title":"An SDN-based algorithm for caching, routing, and load balancing in ICN","authors":"MohammadBagher Tavasoli, Hossein Saidi, Ali Ghiasian","doi":"10.23919/JCC.ja.2023-0165","DOIUrl":"https://doi.org/10.23919/JCC.ja.2023-0165","url":null,"abstract":"One of the challenges of Information-centric Networking (ICN) is finding the optimal location for caching content and processing users' requests. In this paper, we address this challenge by leveraging Software-defined Networking (SDN) for efficient ICN management. To achieve this, we formulate the problem as a mixed-integer nonlinear programming (MINLP) model, incorporating caching, routing, and load balancing decisions. We explore two distinct scenarios to tackle the problem. Firstly, we solve the problem in an offline mode using the GAMS environment, assuming a stable network state to demonstrate the superior performance of the cache-enabled network compared to non-cache networks. Subsequently, we investigate the problem in an online mode where the network state dynamically changes over time. Given the computational complexity associated with MINLP, we propose the software-defined caching, routing, and load balancing (SDCRL) algorithm as an efficient and scalable solution. Our evaluation demonstrates that the SDCRL algorithm significantly reduces computational time while maintaining results that closely resemble those achieved by GAMS.","PeriodicalId":9814,"journal":{"name":"China Communications","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141137138","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 : 2024-05-01DOI: 10.23919/JCC.ja.2022-0592
R. Rajakumar, S. S. Devi
Recently, anomaly detection (AD) in streaming data gained significant attention among research communities due to its applicability in finance, business, healthcare, education, etc. The recent developments of deep learning (DL) models find helpful in the detection and classification of anomalies. This article designs an oversampling with an optimal deep learning-based streaming data classification (OS-ODLSDC) model. The aim of the OS-ODLSDC model is to recognize and classify the presence of anomalies in the streaming data. The proposed OS-ODLSDC model initially undergoes preprocessing step. Since streaming data is unbalanced, support vector machine (SVM)-Synthetic Minority Over-sampling Technique (SVM-SMOTE) is applied for oversampling process. Besides, the OS-ODLSDC model employs bidirectional long short-term memory (BiLSTM) for AD and classification. Finally, the root means square propagation (RMSProp) optimizer is applied for optimal hyperparameter tuning of the BiL-STM model. For ensuring the promising performance of the OS-ODLSDC model, a wide-ranging experimental analysis is performed using three benchmark datasets such as CICIDS 2018, KDD-Cup 1999, and NSL-KDD datasets.
{"title":"An efficient modelling of oversampling with optimal deep learning enabled anomaly detection in streaming data","authors":"R. Rajakumar, S. S. Devi","doi":"10.23919/JCC.ja.2022-0592","DOIUrl":"https://doi.org/10.23919/JCC.ja.2022-0592","url":null,"abstract":"Recently, anomaly detection (AD) in streaming data gained significant attention among research communities due to its applicability in finance, business, healthcare, education, etc. The recent developments of deep learning (DL) models find helpful in the detection and classification of anomalies. This article designs an oversampling with an optimal deep learning-based streaming data classification (OS-ODLSDC) model. The aim of the OS-ODLSDC model is to recognize and classify the presence of anomalies in the streaming data. The proposed OS-ODLSDC model initially undergoes preprocessing step. Since streaming data is unbalanced, support vector machine (SVM)-Synthetic Minority Over-sampling Technique (SVM-SMOTE) is applied for oversampling process. Besides, the OS-ODLSDC model employs bidirectional long short-term memory (BiLSTM) for AD and classification. Finally, the root means square propagation (RMSProp) optimizer is applied for optimal hyperparameter tuning of the BiL-STM model. For ensuring the promising performance of the OS-ODLSDC model, a wide-ranging experimental analysis is performed using three benchmark datasets such as CICIDS 2018, KDD-Cup 1999, and NSL-KDD datasets.","PeriodicalId":9814,"journal":{"name":"China Communications","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141139230","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 : 2024-05-01DOI: 10.23919/JCC.fa.2022-0616.202405
Shiming Fu, Zhang Ping, Xuehong Shi
Traditional wireless sensor networks (WSNs) are typically deployed in remote and hostile environments for information collection. The wireless communication methods adopted by sensor nodes may make the network highly vulnerable to various attacks. Traditional encryption and authentication mechanisms cannot prevent attacks launched by internal malicious nodes. The trust-based security mechanism is usually adopted to solve this problem in WSNs. However, the behavioral evidence used for trust estimation presents some uncertainties due to the open wireless medium and the inexpensive sensor nodes. Moreover, how to efficiently collect behavioral evidences are rarely discussed. To address these issues, in this paper, we present a trust management mechanism based on fuzzy logic and a cloud model. First, a type-II fuzzy logic system is used to preprocess the behavioral evidences and alleviate uncertainty. Then, the cloud model is introduced to estimate the trust values for sensor nodes. Finally, a dynamic behavior monitoring protocol is proposed to provide a balance between energy conservation and safety assurance. Simulation results demonstrate that our trust management mechanism can effectively protect the network from internal malicious attacks while enhancing the energy efficiency of behavior monitoring.
{"title":"A fuzzy trust management mechanism with dynamic behavior monitoring for wireless sensor networks","authors":"Shiming Fu, Zhang Ping, Xuehong Shi","doi":"10.23919/JCC.fa.2022-0616.202405","DOIUrl":"https://doi.org/10.23919/JCC.fa.2022-0616.202405","url":null,"abstract":"Traditional wireless sensor networks (WSNs) are typically deployed in remote and hostile environments for information collection. The wireless communication methods adopted by sensor nodes may make the network highly vulnerable to various attacks. Traditional encryption and authentication mechanisms cannot prevent attacks launched by internal malicious nodes. The trust-based security mechanism is usually adopted to solve this problem in WSNs. However, the behavioral evidence used for trust estimation presents some uncertainties due to the open wireless medium and the inexpensive sensor nodes. Moreover, how to efficiently collect behavioral evidences are rarely discussed. To address these issues, in this paper, we present a trust management mechanism based on fuzzy logic and a cloud model. First, a type-II fuzzy logic system is used to preprocess the behavioral evidences and alleviate uncertainty. Then, the cloud model is introduced to estimate the trust values for sensor nodes. Finally, a dynamic behavior monitoring protocol is proposed to provide a balance between energy conservation and safety assurance. Simulation results demonstrate that our trust management mechanism can effectively protect the network from internal malicious attacks while enhancing the energy efficiency of behavior monitoring.","PeriodicalId":9814,"journal":{"name":"China Communications","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141136688","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 : 2024-05-01DOI: 10.23919/JCC.ja.2023-0084
Ma Shuai, Yang Lei, Wanying Ding, Li Hang, Zhongdan Zhang, Xu Jing, Zongyan Li, Xu Gang, Shiyin Li
The underwater wireless optical communication (UWOC) system has gradually become essential to underwater wireless communication technology. Unlike other existing works on UWOC systems, this paper evaluates the proposed machine learning-based signal demodulation methods through the selfbuilt experimental platform. Based on such a platform, we first construct a real signal dataset with ten modulation methods. Then, we propose a deep belief network (DBN)-based demodulator for feature extraction and multi-class feature classification. We also design an adaptive boosting (AdaBoost) demodulator as an alternative scheme without feature filtering for multiple modulated signals. Finally, it is demonstrated by extensive experimental results that the AdaBoost demodulator significantly outperforms the other algorithms. It also reveals that the demodulator accuracy decreases as the modulation order increases for a fixed received optical power. A higher-order modulation may achieve a higher effective transmission rate when the signal-to-noise ratio (SNR) is higher.
{"title":"Machine learning for signal demodulation in underwater wireless optical communications","authors":"Ma Shuai, Yang Lei, Wanying Ding, Li Hang, Zhongdan Zhang, Xu Jing, Zongyan Li, Xu Gang, Shiyin Li","doi":"10.23919/JCC.ja.2023-0084","DOIUrl":"https://doi.org/10.23919/JCC.ja.2023-0084","url":null,"abstract":"The underwater wireless optical communication (UWOC) system has gradually become essential to underwater wireless communication technology. Unlike other existing works on UWOC systems, this paper evaluates the proposed machine learning-based signal demodulation methods through the selfbuilt experimental platform. Based on such a platform, we first construct a real signal dataset with ten modulation methods. Then, we propose a deep belief network (DBN)-based demodulator for feature extraction and multi-class feature classification. We also design an adaptive boosting (AdaBoost) demodulator as an alternative scheme without feature filtering for multiple modulated signals. Finally, it is demonstrated by extensive experimental results that the AdaBoost demodulator significantly outperforms the other algorithms. It also reveals that the demodulator accuracy decreases as the modulation order increases for a fixed received optical power. A higher-order modulation may achieve a higher effective transmission rate when the signal-to-noise ratio (SNR) is higher.","PeriodicalId":9814,"journal":{"name":"China Communications","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141142075","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 : 2024-05-01DOI: 10.23919/JCC.fa.2022-0004.202405
Ronggui Zou, Yulong Zou, Zhu Jia, Li Bin
In this paper, we explore a cooperative decode-and-forward (DF) relay network comprised of a source, a relay, and a destination in the presence of an eavesdropper. To improve physical-layer security of the relay system, we propose a jamming aided decode-and-forward relay (JDFR) scheme combining the use of artificial noise and DF relaying which requires two stages to transmit a packet. Specifically, in stage one, the source sends confidential message to the relay while the destination acts as a friendly jammer and transmits artificial noise to confound the eavesdropper. In stage two, the relay forwards its re-encoded message to the destination while the source emits artificial noise to confuse the eavesdropper. In addition, we analyze the security-reliability tradeoff (SRT) performance of the proposed JDFR scheme, where security and reliability are evaluated by deriving intercept probability (IP) and outage probability (OP), respectively. For the purpose of comparison, SRT of the traditional decode-and-forward relay (TDFR) scheme is also analyzed. Numerical results show that the SRT performance of the proposed JDFR scheme is better than that of the TDFR scheme. Also, it is shown that for the JDFR scheme, a better SRT performance can be obtained by the optimal power allocation (OPA) between the friendly jammer and user.
{"title":"Security-reliability tradeoff analysis for jamming aided decode-and-forward relay networks","authors":"Ronggui Zou, Yulong Zou, Zhu Jia, Li Bin","doi":"10.23919/JCC.fa.2022-0004.202405","DOIUrl":"https://doi.org/10.23919/JCC.fa.2022-0004.202405","url":null,"abstract":"In this paper, we explore a cooperative decode-and-forward (DF) relay network comprised of a source, a relay, and a destination in the presence of an eavesdropper. To improve physical-layer security of the relay system, we propose a jamming aided decode-and-forward relay (JDFR) scheme combining the use of artificial noise and DF relaying which requires two stages to transmit a packet. Specifically, in stage one, the source sends confidential message to the relay while the destination acts as a friendly jammer and transmits artificial noise to confound the eavesdropper. In stage two, the relay forwards its re-encoded message to the destination while the source emits artificial noise to confuse the eavesdropper. In addition, we analyze the security-reliability tradeoff (SRT) performance of the proposed JDFR scheme, where security and reliability are evaluated by deriving intercept probability (IP) and outage probability (OP), respectively. For the purpose of comparison, SRT of the traditional decode-and-forward relay (TDFR) scheme is also analyzed. Numerical results show that the SRT performance of the proposed JDFR scheme is better than that of the TDFR scheme. Also, it is shown that for the JDFR scheme, a better SRT performance can be obtained by the optimal power allocation (OPA) between the friendly jammer and user.","PeriodicalId":9814,"journal":{"name":"China Communications","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141135449","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 : 2024-05-01DOI: 10.23919/JCC.ea.2021-0665.202401
Zhao Di, Zheng Zhong, Pengfei Qin, Qin Hao, Song Bin
To meet the communication services with diverse requirements, dynamic resource allocation has shown increasing importance. In this paper, we consider the multi-slot and multi-user resource allocation (MSMU-RA) in a downlink cellular scenario with the aim of maximizing system spectral efficiency while guaranteeing user fairness. We first model the MSMU-RA problem as a dual-sequence decision-making process, and then solve it by a novel Transformer-based deep reinforcement learning (TDRL) approach. Specifically, the proposed TDRL approach can be achieved based on two aspects: 1) To adapt to the dynamic wireless environment, the proximal policy optimization (PPO) algorithm is used to optimize the multi-slot RA strategy. 2) To avoid co-channel interference, the Transformer-based PPO algorithm is presented to obtain the optimal multi-user RA scheme by exploring the mapping between user sequence and resource sequence. Experimental results show that: i) the proposed approach outperforms both the traditional and DRL methods in spectral efficiency and user fairness, ii) the proposed algorithm is superior to DRL approaches in terms of convergence speed and generalization performance.
为了满足多样化需求的通信服务，动态资源分配变得越来越重要。本文考虑了下行蜂窝场景中的多时隙和多用户资源分配（MSMU-RA）问题，目的是在保证用户公平性的同时最大化系统频谱效率。我们首先将 MSMU-RA 问题建模为一个双序列决策过程，然后通过一种新颖的基于变换器的深度强化学习（TDRL）方法来解决该问题。具体来说，所提出的 TDRL 方法可以从两个方面实现：1) 为适应动态无线环境，采用近端策略优化（PPO）算法来优化多槽 RA 策略。2) 为避免同信道干扰，提出了基于变换器的 PPO 算法，通过探索用户序列和资源序列之间的映射关系，获得最优的多用户 RA 方案。实验结果表明：i) 所提出的方法在频谱效率和用户公平性方面优于传统方法和 DRL 方法；ii) 所提出的算法在收敛速度和泛化性能方面优于 DRL 方法。
{"title":"Resource allocation in multi-user cellular networks: A transformer-based deep reinforcement learning approach","authors":"Zhao Di, Zheng Zhong, Pengfei Qin, Qin Hao, Song Bin","doi":"10.23919/JCC.ea.2021-0665.202401","DOIUrl":"https://doi.org/10.23919/JCC.ea.2021-0665.202401","url":null,"abstract":"To meet the communication services with diverse requirements, dynamic resource allocation has shown increasing importance. In this paper, we consider the multi-slot and multi-user resource allocation (MSMU-RA) in a downlink cellular scenario with the aim of maximizing system spectral efficiency while guaranteeing user fairness. We first model the MSMU-RA problem as a dual-sequence decision-making process, and then solve it by a novel Transformer-based deep reinforcement learning (TDRL) approach. Specifically, the proposed TDRL approach can be achieved based on two aspects: 1) To adapt to the dynamic wireless environment, the proximal policy optimization (PPO) algorithm is used to optimize the multi-slot RA strategy. 2) To avoid co-channel interference, the Transformer-based PPO algorithm is presented to obtain the optimal multi-user RA scheme by exploring the mapping between user sequence and resource sequence. Experimental results show that: i) the proposed approach outperforms both the traditional and DRL methods in spectral efficiency and user fairness, ii) the proposed algorithm is superior to DRL approaches in terms of convergence speed and generalization performance.","PeriodicalId":9814,"journal":{"name":"China Communications","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141133313","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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