Pub Date : 2021-06-01DOI: 10.1109/ICT52184.2021.9511540
Feiwen Li, Shunliang Zhang
In this paper, we propose a novel hybrid beamforming and jamming strategy to secure the transmission in wireless cooperative networks. It enhances the secrecy capacity by cooperatively using distributed multi-antenna techniques to maximize the secrecy capacity, as well as nullify the information leakage at the eavesdropper and the interference at the legitimate users. The optimum intermediate relays and jammers selection is modeled as a two-level coalitional game problem. A distributed coalition formation algorithm based on merge-and-split rules is devised to solve the problem. The approach enables the intermediate nodes self-organize into independent disjoint coalitions and requires much less computational complexity. Then the optimal relaying and jamming coalitions are selected to secure transmission in a cooperative way. Extensive simulations demonstrate that the proposed coalition formation method can improve the secrecy capacity significantly compared with the existing non-collaborate relaying and jamming nodes selection scheme and random selection approach.
{"title":"Secure transmission in cooperative wireless networks: A two-level coalitional game approach","authors":"Feiwen Li, Shunliang Zhang","doi":"10.1109/ICT52184.2021.9511540","DOIUrl":"https://doi.org/10.1109/ICT52184.2021.9511540","url":null,"abstract":"In this paper, we propose a novel hybrid beamforming and jamming strategy to secure the transmission in wireless cooperative networks. It enhances the secrecy capacity by cooperatively using distributed multi-antenna techniques to maximize the secrecy capacity, as well as nullify the information leakage at the eavesdropper and the interference at the legitimate users. The optimum intermediate relays and jammers selection is modeled as a two-level coalitional game problem. A distributed coalition formation algorithm based on merge-and-split rules is devised to solve the problem. The approach enables the intermediate nodes self-organize into independent disjoint coalitions and requires much less computational complexity. Then the optimal relaying and jamming coalitions are selected to secure transmission in a cooperative way. Extensive simulations demonstrate that the proposed coalition formation method can improve the secrecy capacity significantly compared with the existing non-collaborate relaying and jamming nodes selection scheme and random selection approach.","PeriodicalId":142681,"journal":{"name":"2021 28th International Conference on Telecommunications (ICT)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125044162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-06-01DOI: 10.1109/ICT52184.2021.9511536
Yanyun Xu, Zekun Hong
In this paper, we propose a novel detector that combines complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and cell averaging-constant false alarm rate (CA-CFAR) approach for noise-dominated ultra-wideband (UWB) pulse signal. The proposed detector is utilized to estimate noise power from the received signal's intrinsic mode functions (IMFs). Then the detection threshold is determined based on noise estimation and a given false alarm rate. The proposed method can detect UWB pulse signal submerged in noise and work blindly, requiring no prior information. The performance is validated by simulations and experiments, which show the proposed detector has high robustness to noise uncertainty and can detect weak UWB pulse signal at -15dB of signal-to-noise ratio (SNR) with a detection rate of nearly 90%. Further, experiments on the UWB positioning module prove the effectiveness of this method in practical application.
{"title":"A CEEMDAN-CA Detector for UWB Pulse Signal in Low SNR","authors":"Yanyun Xu, Zekun Hong","doi":"10.1109/ICT52184.2021.9511536","DOIUrl":"https://doi.org/10.1109/ICT52184.2021.9511536","url":null,"abstract":"In this paper, we propose a novel detector that combines complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and cell averaging-constant false alarm rate (CA-CFAR) approach for noise-dominated ultra-wideband (UWB) pulse signal. The proposed detector is utilized to estimate noise power from the received signal's intrinsic mode functions (IMFs). Then the detection threshold is determined based on noise estimation and a given false alarm rate. The proposed method can detect UWB pulse signal submerged in noise and work blindly, requiring no prior information. The performance is validated by simulations and experiments, which show the proposed detector has high robustness to noise uncertainty and can detect weak UWB pulse signal at -15dB of signal-to-noise ratio (SNR) with a detection rate of nearly 90%. Further, experiments on the UWB positioning module prove the effectiveness of this method in practical application.","PeriodicalId":142681,"journal":{"name":"2021 28th International Conference on Telecommunications (ICT)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126428439","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-06-01DOI: 10.1109/ict52184.2021.9511527
{"title":"Welcome General","authors":"","doi":"10.1109/ict52184.2021.9511527","DOIUrl":"https://doi.org/10.1109/ict52184.2021.9511527","url":null,"abstract":"","PeriodicalId":142681,"journal":{"name":"2021 28th International Conference on Telecommunications (ICT)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122817878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-06-01DOI: 10.1109/ICT52184.2021.9511516
Shaoying Guo, Yanyun Xu, Wei-qing Huang, Bo Liu
Specific emitter identification (SEI) is a physical-layer-based approach for enhancing wireless communication network security. A well-done SEI method can be widely applied in identifying the individual wireless communication device. In this paper, we propose a novel specific emitter identification method based on variational mode decomposition and histogram of oriented gradient (VMD-HOG). The signal is decomposed into specific temporal modes via VMD and HOG features are obtained from the time-frequency spectrum of temporal modes. The performance of the proposed method is evaluated both in single hop and relaying scenarios and under three channels with the number of emitters varying. Results depict that our proposed method provides great identification performance for both simulated signals and realistic data of Zigbee devices and outperforms the two existing methods in identification accuracy and computational complexity.
{"title":"Specific Emitter Identification via Variational Mode Decomposition and Histogram of Oriented Gradient","authors":"Shaoying Guo, Yanyun Xu, Wei-qing Huang, Bo Liu","doi":"10.1109/ICT52184.2021.9511516","DOIUrl":"https://doi.org/10.1109/ICT52184.2021.9511516","url":null,"abstract":"Specific emitter identification (SEI) is a physical-layer-based approach for enhancing wireless communication network security. A well-done SEI method can be widely applied in identifying the individual wireless communication device. In this paper, we propose a novel specific emitter identification method based on variational mode decomposition and histogram of oriented gradient (VMD-HOG). The signal is decomposed into specific temporal modes via VMD and HOG features are obtained from the time-frequency spectrum of temporal modes. The performance of the proposed method is evaluated both in single hop and relaying scenarios and under three channels with the number of emitters varying. Results depict that our proposed method provides great identification performance for both simulated signals and realistic data of Zigbee devices and outperforms the two existing methods in identification accuracy and computational complexity.","PeriodicalId":142681,"journal":{"name":"2021 28th International Conference on Telecommunications (ICT)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127745538","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-06-01DOI: 10.1109/ICT52184.2021.9511517
Ji Huan, Yongzheng Zhang, Peng Chang, Yupeng Tuo
Many botnets adopt domain generation algorithms (DGAs) to set up stealthy Command & Control (C2) communication. A DGA generates a great number of domain names and the attacker selects some of them to map to the C2 servers. In this paper, we propose Talos, a DGA detection approach to detect unknown DGAs and also known DGAs accurately. The key insight of Talos is that domain names can be represented by feature vectors satisfying the condition that distances between the feature vectors can reflect whether they are of the same class. Talos uses a neural language model to extract the feature vector of a domain name. After that, Talos determines if the feature vector belongs to a class based on whether it is within the boundary of the class and near the centroid of the class. We evaluate the detection ability of Talos on both unknown and known DGAs. Our experimental results show that Talos achieves recall over 92% on unknown classes and F1-score over 95% on known classes. We also compare Talos with state-of-the-art detection approaches and find that Talos's ability to detect unknown DGAs largely surpasses them.
{"title":"Detecting Unknown DGAs Using Distances Between Feature Vectors of Domain Names","authors":"Ji Huan, Yongzheng Zhang, Peng Chang, Yupeng Tuo","doi":"10.1109/ICT52184.2021.9511517","DOIUrl":"https://doi.org/10.1109/ICT52184.2021.9511517","url":null,"abstract":"Many botnets adopt domain generation algorithms (DGAs) to set up stealthy Command & Control (C2) communication. A DGA generates a great number of domain names and the attacker selects some of them to map to the C2 servers. In this paper, we propose Talos, a DGA detection approach to detect unknown DGAs and also known DGAs accurately. The key insight of Talos is that domain names can be represented by feature vectors satisfying the condition that distances between the feature vectors can reflect whether they are of the same class. Talos uses a neural language model to extract the feature vector of a domain name. After that, Talos determines if the feature vector belongs to a class based on whether it is within the boundary of the class and near the centroid of the class. We evaluate the detection ability of Talos on both unknown and known DGAs. Our experimental results show that Talos achieves recall over 92% on unknown classes and F1-score over 95% on known classes. We also compare Talos with state-of-the-art detection approaches and find that Talos's ability to detect unknown DGAs largely surpasses them.","PeriodicalId":142681,"journal":{"name":"2021 28th International Conference on Telecommunications (ICT)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123524604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-06-01DOI: 10.1109/ICT52184.2021.9511463
Nahid Eddermoug, A. Mansour, M. Sadik, Essaid Sabir, Mohamed Azmi
Cloud computing is a digital era technology which uses the Internet to maintain data as well as applications in cloud data centers. However, this technology still meet numerous challenges and suffers from several attacks. For this reason, we proposed recently a new scheme called “klm-based profiling and preventing security attacks (klm-PPSA)” to detect both known and unknown attacks. In this study, we exhibit a comparative study of the klm-PPSA model using separately two accurate and interpretable machine learning algorithms: regularized class association rules (RCAR) and classification based on associations (CBA). Moreover, considering an interesting data set, three case studies of the proposal with three different implementations of the $klm$ security factors are given ($k$-PPSA, km-PPSA and klm-PPSA models). The experiments for each case study with run-time measurement were done. The obtained results show that: compared to $k$-PPSA and km-PPSA models, the klm-PPSA model gives the highest performances in terms of sensitivity with both CBA and RCAR but with a processing time seven times more than CBA. However, RCAR gives an accuracy and specificity better than the CBA for all the models. Eventually, klm-PPSA system is able to detect and prevent several types of known and unknown attacks.
{"title":"Klm-based Profiling and Preventing Security Attacks for Cloud Computing: A Comparative Study","authors":"Nahid Eddermoug, A. Mansour, M. Sadik, Essaid Sabir, Mohamed Azmi","doi":"10.1109/ICT52184.2021.9511463","DOIUrl":"https://doi.org/10.1109/ICT52184.2021.9511463","url":null,"abstract":"Cloud computing is a digital era technology which uses the Internet to maintain data as well as applications in cloud data centers. However, this technology still meet numerous challenges and suffers from several attacks. For this reason, we proposed recently a new scheme called “klm-based profiling and preventing security attacks (klm-PPSA)” to detect both known and unknown attacks. In this study, we exhibit a comparative study of the klm-PPSA model using separately two accurate and interpretable machine learning algorithms: regularized class association rules (RCAR) and classification based on associations (CBA). Moreover, considering an interesting data set, three case studies of the proposal with three different implementations of the $klm$ security factors are given ($k$-PPSA, km-PPSA and klm-PPSA models). The experiments for each case study with run-time measurement were done. The obtained results show that: compared to $k$-PPSA and km-PPSA models, the klm-PPSA model gives the highest performances in terms of sensitivity with both CBA and RCAR but with a processing time seven times more than CBA. However, RCAR gives an accuracy and specificity better than the CBA for all the models. Eventually, klm-PPSA system is able to detect and prevent several types of known and unknown attacks.","PeriodicalId":142681,"journal":{"name":"2021 28th International Conference on Telecommunications (ICT)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122288939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-06-01DOI: 10.1109/ICT52184.2021.9511466
Lingyu Wang, Chen Li, Bibo Tu
Privileged credentials are one of the key targets of attackers. Password authentication is plagued by phishing scams and keyloggers for years. Using a second factor, such as user behavior, as a part of the authentication process offers higher assurance. A great deal of research has been proposed to authenticate based on the behavior of various entities. However, they often play effects after user logging on to the system. Even if the attacks are detected successfully, the malicious activities have been performed and the damage is done. In this paper, we present Evalt, an implicit approach that takes effect before user logging on to enhance authentication with an additional security layer. Evalt exploits the features extracted from authentication events to detect anomalies. Hence it could block the attackers before they cause damage to systems. We test Evalt on an open-source Windows security log dataset. The experiment shows that our method could identify threats with a good performance before the actual damage occurs based on the authentication events' features.
{"title":"Evalt: Authenticate Implicitly Before Attacks","authors":"Lingyu Wang, Chen Li, Bibo Tu","doi":"10.1109/ICT52184.2021.9511466","DOIUrl":"https://doi.org/10.1109/ICT52184.2021.9511466","url":null,"abstract":"Privileged credentials are one of the key targets of attackers. Password authentication is plagued by phishing scams and keyloggers for years. Using a second factor, such as user behavior, as a part of the authentication process offers higher assurance. A great deal of research has been proposed to authenticate based on the behavior of various entities. However, they often play effects after user logging on to the system. Even if the attacks are detected successfully, the malicious activities have been performed and the damage is done. In this paper, we present Evalt, an implicit approach that takes effect before user logging on to enhance authentication with an additional security layer. Evalt exploits the features extracted from authentication events to detect anomalies. Hence it could block the attackers before they cause damage to systems. We test Evalt on an open-source Windows security log dataset. The experiment shows that our method could identify threats with a good performance before the actual damage occurs based on the authentication events' features.","PeriodicalId":142681,"journal":{"name":"2021 28th International Conference on Telecommunications (ICT)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128977127","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-06-01DOI: 10.1109/ICT52184.2021.9511542
Beste Atan, Nurullah Çalık, S. T. Basaran, M. Başaran, L. Durak-Ata
Learning-based computation of task execution in edge computing has a great potential to be a part of future cloud based next generation wireless networks. In this paper, we propose a novel intelligent computation task execution model to reduce decision latency by taking different system parameters into account including the execution deadline of the task, the battery level of mobile devices, and the channel between mobile device and edge server. In the edge computing, the number of task requests, resource constraints, mobility of users and energy consumption are main performance considerations. This study addresses the problem of a fast decision of the computing resources for the application offloaded to the edge servers by formulating it as a multi-class classification problem. The extensive simulation results demonstrate that the proposed algorithm is able to determine the decision of offloading computation tasks with more than 100 times faster than the conventional optimization method.
{"title":"Learning-Based Fast Decision for Task Execution in Next Generation Wireless Networks","authors":"Beste Atan, Nurullah Çalık, S. T. Basaran, M. Başaran, L. Durak-Ata","doi":"10.1109/ICT52184.2021.9511542","DOIUrl":"https://doi.org/10.1109/ICT52184.2021.9511542","url":null,"abstract":"Learning-based computation of task execution in edge computing has a great potential to be a part of future cloud based next generation wireless networks. In this paper, we propose a novel intelligent computation task execution model to reduce decision latency by taking different system parameters into account including the execution deadline of the task, the battery level of mobile devices, and the channel between mobile device and edge server. In the edge computing, the number of task requests, resource constraints, mobility of users and energy consumption are main performance considerations. This study addresses the problem of a fast decision of the computing resources for the application offloaded to the edge servers by formulating it as a multi-class classification problem. The extensive simulation results demonstrate that the proposed algorithm is able to determine the decision of offloading computation tasks with more than 100 times faster than the conventional optimization method.","PeriodicalId":142681,"journal":{"name":"2021 28th International Conference on Telecommunications (ICT)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117024151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-06-01DOI: 10.1109/ICT52184.2021.9511514
G. Varshney, Naman Shah
End users consider the data available through web as unmodified. Even when the web is secured by HTTPS, the data can be tampered in numerous tactical ways reducing trust on the integrity of data at the clients' end. One of the ways in which the web pages can be modified is via client side browser extensions. The extensions can transparently modify the web pages at client's end and can include new data to the web pages with minimal permissions. Clever modifications can be addition of a fake news or a fake advertisement or a link to a phishing website. We have identified through experimentation that such attacks are possible and have potential for serious damages. To prevent and detect such modifications we present a novel domain expressiveness based approach that uses DNS (Domain Name System) TXT records to express the Hash of important web pages that gets verified by the browsers to detect/thwart any modifications to the contents that are launched via client side malicious browser extensions or via cross site scripting. Initial experimentation suggest that the technique has potential to be used and deployed.
{"title":"A DNS Security Policy for Timely Detection of Malicious Modification on Webpages","authors":"G. Varshney, Naman Shah","doi":"10.1109/ICT52184.2021.9511514","DOIUrl":"https://doi.org/10.1109/ICT52184.2021.9511514","url":null,"abstract":"End users consider the data available through web as unmodified. Even when the web is secured by HTTPS, the data can be tampered in numerous tactical ways reducing trust on the integrity of data at the clients' end. One of the ways in which the web pages can be modified is via client side browser extensions. The extensions can transparently modify the web pages at client's end and can include new data to the web pages with minimal permissions. Clever modifications can be addition of a fake news or a fake advertisement or a link to a phishing website. We have identified through experimentation that such attacks are possible and have potential for serious damages. To prevent and detect such modifications we present a novel domain expressiveness based approach that uses DNS (Domain Name System) TXT records to express the Hash of important web pages that gets verified by the browsers to detect/thwart any modifications to the contents that are launched via client side malicious browser extensions or via cross site scripting. Initial experimentation suggest that the technique has potential to be used and deployed.","PeriodicalId":142681,"journal":{"name":"2021 28th International Conference on Telecommunications (ICT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117160982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-06-01DOI: 10.1109/ICT52184.2021.9511521
Amina Girdher, Ankur Bansal, Ankit Dubey
In this paper, we consider a decode-and-forward (DF) relay-assisted mixed free space optical-radio frequency (FSO-RF) system, where the FSO system utilizes simultaneous light-wave information and power transfer (SLIPT) to extend the lifetime of the system. Considering energy harvesting at DF relay node, we derive the statistics of end-to-end signal-to-noise ratio (SNR). For the considered system, the FSO channel is modeled by the Gamma-Gamma turbulence model affected by zero boresight pointing error, and the non-coherent intensity modulation with direct detection (IM/DD) technique is employed at the FSO receiver. Further, the RF channel is assumed to undergo Nakagami-m fading. In particular, analytical closed-form expression of outage probability is derived for the considered network in terms of Meijer's G-function. To obtain further insights, we derive asymptotic outage probability expression and evaluate the diversity order analytically. The impact of DC bias along with various atmospheric turbulence and misalignment conditions on the system performance is revealed for SLIPT based mixed FSO-RF communication system. Numerical results manifest that the considered DF-based mixed FSO-RF communication system utilizing SLIPT significantly outperforms the corresponding amplify-and-forward (AF) relay-based communication system. The analytical results are corroborated through Monte-Carlo simulations.
{"title":"Analyzing SLIPT for DF Based Mixed FSO-RF Communication System","authors":"Amina Girdher, Ankur Bansal, Ankit Dubey","doi":"10.1109/ICT52184.2021.9511521","DOIUrl":"https://doi.org/10.1109/ICT52184.2021.9511521","url":null,"abstract":"In this paper, we consider a decode-and-forward (DF) relay-assisted mixed free space optical-radio frequency (FSO-RF) system, where the FSO system utilizes simultaneous light-wave information and power transfer (SLIPT) to extend the lifetime of the system. Considering energy harvesting at DF relay node, we derive the statistics of end-to-end signal-to-noise ratio (SNR). For the considered system, the FSO channel is modeled by the Gamma-Gamma turbulence model affected by zero boresight pointing error, and the non-coherent intensity modulation with direct detection (IM/DD) technique is employed at the FSO receiver. Further, the RF channel is assumed to undergo Nakagami-m fading. In particular, analytical closed-form expression of outage probability is derived for the considered network in terms of Meijer's G-function. To obtain further insights, we derive asymptotic outage probability expression and evaluate the diversity order analytically. The impact of DC bias along with various atmospheric turbulence and misalignment conditions on the system performance is revealed for SLIPT based mixed FSO-RF communication system. Numerical results manifest that the considered DF-based mixed FSO-RF communication system utilizing SLIPT significantly outperforms the corresponding amplify-and-forward (AF) relay-based communication system. The analytical results are corroborated through Monte-Carlo simulations.","PeriodicalId":142681,"journal":{"name":"2021 28th International Conference on Telecommunications (ICT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125807839","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：