In this work, a non-binary low density parity check (LDPC) coded high dimensional multiple input multiple output (MIMO) scheme with partial mapping for high order modulation is proposed. For the proposed scheme, when $M$ -ary quadrature amplitude modulation (QAM) is employed, then non-binary LDPC code constructed over Galois field with order $sqrt{M}$ is used for partial mapping, where $sqrt{M}$ is an integer. At the receiver side, a real-valued expectation propagation (REP) based detection algorithm is used. Furthermore, symbol-wise extrinsic information transfer (SEXIT) chart based iterative optimization algorithm is used to optimize the concatenated non-binary LDPC code. A simplified method is proposed to calculate the component EXIT chart of the massive MIMO detector, which can avoid a large amount of simulations. Numerical simulation results demonstrate the validity of the above idea.
{"title":"Optimization of non-binary LDPC coded massive MIMO systems with partial mapping and EP detection","authors":"Zhi-Yuan Feng, Qingqing Liu, Jin Xu, Weihua Liu, Zhe Zhang, Xueyan Chen, Hanqing Ding","doi":"10.1109/ICT52184.2021.9511526","DOIUrl":"https://doi.org/10.1109/ICT52184.2021.9511526","url":null,"abstract":"In this work, a non-binary low density parity check (LDPC) coded high dimensional multiple input multiple output (MIMO) scheme with partial mapping for high order modulation is proposed. For the proposed scheme, when $M$ -ary quadrature amplitude modulation (QAM) is employed, then non-binary LDPC code constructed over Galois field with order $sqrt{M}$ is used for partial mapping, where $sqrt{M}$ is an integer. At the receiver side, a real-valued expectation propagation (REP) based detection algorithm is used. Furthermore, symbol-wise extrinsic information transfer (SEXIT) chart based iterative optimization algorithm is used to optimize the concatenated non-binary LDPC code. A simplified method is proposed to calculate the component EXIT chart of the massive MIMO detector, which can avoid a large amount of simulations. Numerical simulation results demonstrate the validity of the above idea.","PeriodicalId":142681,"journal":{"name":"2021 28th International Conference on Telecommunications (ICT)","volume":"144 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":"114452185","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/ICT52184.2021.9511541
Bassant Tolba, A. El-Malek, M. Abo-Zahhad, M. Elsabrouty
In massive multiple-input multiple-output frequency division duplexing systems, the user equipment should independently estimate the massive downlink channels state information and then feed them back to the base station. This process results in a large signaling overhead. Deep learning approaches tried to overcome this challenge using neural networks as an autoencoder to learn the mapping between the input and corresponding output. However, this type of learning consumes massive training datasets to learn. Also, it can not make use of the learning through the internal information within the tasks and thus, it can not reach the convergence quickly as its parameters are randomly initialized. In this paper, we introduce a meta learner-based autoencoder for tackling the feedback overhead. The proposed approach is mainly based on finding a good initialization of the parameters of the autoencoder to adapt rapidly to new tasks with a few number of samples. The results show that the proposed autoencoder based on the meta-learner method outperforms the state of the art with a margin.
{"title":"A Meta Learner Autoencoder for Channel State Information Feedback in Massive MIMO Systems","authors":"Bassant Tolba, A. El-Malek, M. Abo-Zahhad, M. Elsabrouty","doi":"10.1109/ICT52184.2021.9511541","DOIUrl":"https://doi.org/10.1109/ICT52184.2021.9511541","url":null,"abstract":"In massive multiple-input multiple-output frequency division duplexing systems, the user equipment should independently estimate the massive downlink channels state information and then feed them back to the base station. This process results in a large signaling overhead. Deep learning approaches tried to overcome this challenge using neural networks as an autoencoder to learn the mapping between the input and corresponding output. However, this type of learning consumes massive training datasets to learn. Also, it can not make use of the learning through the internal information within the tasks and thus, it can not reach the convergence quickly as its parameters are randomly initialized. In this paper, we introduce a meta learner-based autoencoder for tackling the feedback overhead. The proposed approach is mainly based on finding a good initialization of the parameters of the autoencoder to adapt rapidly to new tasks with a few number of samples. The results show that the proposed autoencoder based on the meta-learner method outperforms the state of the art with a margin.","PeriodicalId":142681,"journal":{"name":"2021 28th International Conference on Telecommunications (ICT)","volume":"2000 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":"125729000","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/ICT52184.2021.9511465
K. Vaishnavi, Shubham Dashrath Khorvi, Rajalekshmi Kishore, Sanjeev Gurugopinath
In this paper, we present a comprehensive survey on jamming techniques for physical layer security (PLS) and anti-jamming strategies in beyond fifth generation (B5G) and towards the sixth generation (6G) communication systems. A combined study on jamming and anti-jamming methods is important for PLS, and is helpful to study and design PLS algorithms in the presence of jamming, eavesdropping and spoofing. First, we present various approaches for PLS in 6G. Next, we discuss techniques that use jammers for PLS, followed by a detailed study on recently proposed anti-jamming solutions. Further, we discuss the use of machine learning and artificial intelligence for anti-jamming. Moreover, we present a study on the challenges for PLS in 6G, and discuss some future research directions.
{"title":"A Survey on Jamming Techniques in Physical Layer Security and Anti-Jamming Strategies for 6G","authors":"K. Vaishnavi, Shubham Dashrath Khorvi, Rajalekshmi Kishore, Sanjeev Gurugopinath","doi":"10.1109/ICT52184.2021.9511465","DOIUrl":"https://doi.org/10.1109/ICT52184.2021.9511465","url":null,"abstract":"In this paper, we present a comprehensive survey on jamming techniques for physical layer security (PLS) and anti-jamming strategies in beyond fifth generation (B5G) and towards the sixth generation (6G) communication systems. A combined study on jamming and anti-jamming methods is important for PLS, and is helpful to study and design PLS algorithms in the presence of jamming, eavesdropping and spoofing. First, we present various approaches for PLS in 6G. Next, we discuss techniques that use jammers for PLS, followed by a detailed study on recently proposed anti-jamming solutions. Further, we discuss the use of machine learning and artificial intelligence for anti-jamming. Moreover, we present a study on the challenges for PLS in 6G, and discuss some future research directions.","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":"134337882","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/ICT52184.2021.9511462
Degang Sun, Sixue Lu, Wen Wang
To sense and understand how to use the wireless spectrum, people have proposed various anomaly spectrum detection methods. We judge it as anomaly behavior if the received signal is unauthorized or the radiation of an expected signal is changed. We propose CAAE, a novel wireless spectrum anomaly detection method, to detect the two kinds of anomaly behaviors. CAAE is a complex adversarial autoencoder that can realize feature extraction and image reconstruction of input data through convolution and deconvolution networks. We train CAAE in a semi-supervised learning fashion and various values in the calculation process would change if the anomaly spectrum is input after the model training is completed. Therefore, we propose the multiple scoring criterion to help improve the detection accuracy of our model. The time-frequency waterfall graphs are input and we do two sets of experiments to prove the validity of our model. The experimental results show that the comprehensive detection capability of CAAE model is superior to the comparison algorithms for our dataset.
{"title":"CAAE: A Novel Wireless Spectrum Anomaly Detection Method with Multiple Scoring Criterion","authors":"Degang Sun, Sixue Lu, Wen Wang","doi":"10.1109/ICT52184.2021.9511462","DOIUrl":"https://doi.org/10.1109/ICT52184.2021.9511462","url":null,"abstract":"To sense and understand how to use the wireless spectrum, people have proposed various anomaly spectrum detection methods. We judge it as anomaly behavior if the received signal is unauthorized or the radiation of an expected signal is changed. We propose CAAE, a novel wireless spectrum anomaly detection method, to detect the two kinds of anomaly behaviors. CAAE is a complex adversarial autoencoder that can realize feature extraction and image reconstruction of input data through convolution and deconvolution networks. We train CAAE in a semi-supervised learning fashion and various values in the calculation process would change if the anomaly spectrum is input after the model training is completed. Therefore, we propose the multiple scoring criterion to help improve the detection accuracy of our model. The time-frequency waterfall graphs are input and we do two sets of experiments to prove the validity of our model. The experimental results show that the comprehensive detection capability of CAAE model is superior to the comparison algorithms for our dataset.","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":"131232790","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}
Aiming at the problem of identification of a large number of radio stations in the high frequency (HF) band, a fast identification method based on sparse component analysis, in which high-speed spectrum scanning data are used to separate and identify multiple stations on each channel, is proposed. Taking into account the adverse effects of the shortwave time-varying channel fading on the radio signals, utilizing the periodicity of the radio signals, a sparse component analysis algorithm based on time feature clustering (TFC-SCA) is proposed. The algorithm combines the time features with the amplitude features for clustering and realizes the accurate estimation of the mixing matrix under fading channel conditions. In addition, based on the clustering results, the algorithm projects the signals to the vectors from the origin to the clustering centers to remove the noise introduced by the time-varying channel fading. In simulation experiments with different duty cycles and different periods, the correlation coefficients of TFC-SCA are closer to 1 than clustering based sparse component analysis (C-SCA) and fast independent component analysis (FastICA), providing a good solution to the problem of separation and identification of shortwave radio stations.
{"title":"A Fast Identification Method of Shortwave Radio Stations Based on Sparse Component Analysis","authors":"Yuankun Wang, Wei-qing Huang, Qiaoyu Zhang, Dong Wei","doi":"10.1109/ICT52184.2021.9511543","DOIUrl":"https://doi.org/10.1109/ICT52184.2021.9511543","url":null,"abstract":"Aiming at the problem of identification of a large number of radio stations in the high frequency (HF) band, a fast identification method based on sparse component analysis, in which high-speed spectrum scanning data are used to separate and identify multiple stations on each channel, is proposed. Taking into account the adverse effects of the shortwave time-varying channel fading on the radio signals, utilizing the periodicity of the radio signals, a sparse component analysis algorithm based on time feature clustering (TFC-SCA) is proposed. The algorithm combines the time features with the amplitude features for clustering and realizes the accurate estimation of the mixing matrix under fading channel conditions. In addition, based on the clustering results, the algorithm projects the signals to the vectors from the origin to the clustering centers to remove the noise introduced by the time-varying channel fading. In simulation experiments with different duty cycles and different periods, the correlation coefficients of TFC-SCA are closer to 1 than clustering based sparse component analysis (C-SCA) and fast independent component analysis (FastICA), providing a good solution to the problem of separation and identification of shortwave radio stations.","PeriodicalId":142681,"journal":{"name":"2021 28th International Conference on Telecommunications (ICT)","volume":"8 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":"117011440","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/ICT52184.2021.9511515
P. Prior, Nuno Cota
This paper presents the evaluation results of the radio signal propagation prediction using Longley-Rice model in railways installed in rural areas with significant variation of propagation path and terrain profiles. The prediction results were compared with measurement acquired by installing several CW emitters along the railway and reception equipment installed on a rolling stock. In addition, the results were also compared with the prediction based on Okumura-Hata model. The obtained results prove Longley-Rice suitability for railways communication prediction on irregular terrain, achieving better results than the Okumura-Hata model.
{"title":"Railways Communications Propagation Prediction over Irregular Terrain using Longley-Rice Model","authors":"P. Prior, Nuno Cota","doi":"10.1109/ICT52184.2021.9511515","DOIUrl":"https://doi.org/10.1109/ICT52184.2021.9511515","url":null,"abstract":"This paper presents the evaluation results of the radio signal propagation prediction using Longley-Rice model in railways installed in rural areas with significant variation of propagation path and terrain profiles. The prediction results were compared with measurement acquired by installing several CW emitters along the railway and reception equipment installed on a rolling stock. In addition, the results were also compared with the prediction based on Okumura-Hata model. The obtained results prove Longley-Rice suitability for railways communication prediction on irregular terrain, achieving better results than the Okumura-Hata model.","PeriodicalId":142681,"journal":{"name":"2021 28th International Conference on Telecommunications (ICT)","volume":"78 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":"124885697","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/ICT52184.2021.9511544
J. Costa-Requena, C. Konstantinos, D. Kritharidis, Abraham Afriyie, N. Carapellese, Eduardo Yusta Padilla
With the explosive data growth of user traffic in wireless communications, Terahertz (THz) frequency band is envisioned as a promising candidate to support ultra-broadband communications for beyond fifth generation (5G) networks. Software-based networking is being adopted in mobile communications to improve efficiency and reduce operational costs. This paper presents the design of a comprehensive SDN management architecture for joint optimization of radio and network resources. The proposed architecture obtains the most added value out of the use of THz technology integrated with software managed networking for mobile network beyond 5G. In this paper, leveraging optical concepts and photonic integration techniques for an ultra-broadband and ultra-wideband wireless system is presented.
{"title":"SDN-enabled terahertz x-haul network","authors":"J. Costa-Requena, C. Konstantinos, D. Kritharidis, Abraham Afriyie, N. Carapellese, Eduardo Yusta Padilla","doi":"10.1109/ICT52184.2021.9511544","DOIUrl":"https://doi.org/10.1109/ICT52184.2021.9511544","url":null,"abstract":"With the explosive data growth of user traffic in wireless communications, Terahertz (THz) frequency band is envisioned as a promising candidate to support ultra-broadband communications for beyond fifth generation (5G) networks. Software-based networking is being adopted in mobile communications to improve efficiency and reduce operational costs. This paper presents the design of a comprehensive SDN management architecture for joint optimization of radio and network resources. The proposed architecture obtains the most added value out of the use of THz technology integrated with software managed networking for mobile network beyond 5G. In this paper, leveraging optical concepts and photonic integration techniques for an ultra-broadband and ultra-wideband wireless system is presented.","PeriodicalId":142681,"journal":{"name":"2021 28th International Conference on Telecommunications (ICT)","volume":"101 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":"130301296","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/ICT52184.2021.9511459
Olfa Ben Yahia, Eylem Erdogan, Günes Karabulut-Kurt, I. Altunbas, H. Yanikomeroglu
In this work, we propose a new physical layer security framework for optical space networks. More precisely, we consider two practical eavesdropping scenarios: free-space optical (FSO) eavesdropping in the space and FSO eavesdropping in the air. In the former, we assume that a high altitude platform station (HAPS) is trying to capture the confidential information from the low earth orbit (LEO) satellite, whereas in the latter, an unmanned aerial vehicle (UAV) eavesdropper is trying to intercept the confidential information from the HAPS node. To quantify the overall performance of both scenarios, we obtain closed-form secrecy outage probability (SOP) and probability of positive secrecy capacity (PPSC) expressions and validate with Monte Carlo simulations. Furthermore, we provide important design guidelines that can be helpful in the design of secure non-terrestrial networks.
{"title":"Physical Layer Security Framework for Optical Non-Terrestrial Networks","authors":"Olfa Ben Yahia, Eylem Erdogan, Günes Karabulut-Kurt, I. Altunbas, H. Yanikomeroglu","doi":"10.1109/ICT52184.2021.9511459","DOIUrl":"https://doi.org/10.1109/ICT52184.2021.9511459","url":null,"abstract":"In this work, we propose a new physical layer security framework for optical space networks. More precisely, we consider two practical eavesdropping scenarios: free-space optical (FSO) eavesdropping in the space and FSO eavesdropping in the air. In the former, we assume that a high altitude platform station (HAPS) is trying to capture the confidential information from the low earth orbit (LEO) satellite, whereas in the latter, an unmanned aerial vehicle (UAV) eavesdropper is trying to intercept the confidential information from the HAPS node. To quantify the overall performance of both scenarios, we obtain closed-form secrecy outage probability (SOP) and probability of positive secrecy capacity (PPSC) expressions and validate with Monte Carlo simulations. Furthermore, we provide important design guidelines that can be helpful in the design of secure non-terrestrial networks.","PeriodicalId":142681,"journal":{"name":"2021 28th International Conference on Telecommunications (ICT)","volume":"27 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":"125482814","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/ICT52184.2021.9511523
Jun Wang, A. Al-Banna
Full duplex cable networks are built and analyzed in theoretical models based on the RF performance of their building blocks, including nodes, cables, taps, pluggable devices for taps and cable modems, etc. The key performance-degrading factors in FDX systems are analyzed in the models and the results are proven by experimental results.
{"title":"Modelling and Analysis of FDX cable Systems","authors":"Jun Wang, A. Al-Banna","doi":"10.1109/ICT52184.2021.9511523","DOIUrl":"https://doi.org/10.1109/ICT52184.2021.9511523","url":null,"abstract":"Full duplex cable networks are built and analyzed in theoretical models based on the RF performance of their building blocks, including nodes, cables, taps, pluggable devices for taps and cable modems, etc. The key performance-degrading factors in FDX systems are analyzed in the models and the results are proven by experimental results.","PeriodicalId":142681,"journal":{"name":"2021 28th International Conference on Telecommunications (ICT)","volume":"24 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":"124098934","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/ICT52184.2021.9511529
Dali Zhu, Hongju Sun, Di Wu
In public safety scenarios, target objects identification and tracking is an important application, and two positioning methods including wireless and computer vision are respectively used for applications. In this article, we combine the wireless signal and computer vision, and propose a novel object identification and tracking technology. The positioning method based on computer vision helps to improve the accuracy of positioning, and we can easily distinguish different users according to wireless device information. Based on our proposed trajectory association technology, the visual trajectory is accurately matched to the corresponding wireless trajectory, and the identity of the visual trajectory is confirmed. Combined with the analysis of the position change and appearance change of visual objects, wireless positioning results are fused to correct the affected visual trajectory to improve overall system performance. A tracking system was deployed in the real world. The fusion path is proved to be closer to the real path and 90% of the errors were less than 1m. We have also implemented large-scale simulation experiments to evaluate our approach. The results show that our association algorithm has a high matching success rate and is insensitive to synchronization errors.
{"title":"Fusion of Wireless Signal and Computer Vision for Identification and Tracking","authors":"Dali Zhu, Hongju Sun, Di Wu","doi":"10.1109/ICT52184.2021.9511529","DOIUrl":"https://doi.org/10.1109/ICT52184.2021.9511529","url":null,"abstract":"In public safety scenarios, target objects identification and tracking is an important application, and two positioning methods including wireless and computer vision are respectively used for applications. In this article, we combine the wireless signal and computer vision, and propose a novel object identification and tracking technology. The positioning method based on computer vision helps to improve the accuracy of positioning, and we can easily distinguish different users according to wireless device information. Based on our proposed trajectory association technology, the visual trajectory is accurately matched to the corresponding wireless trajectory, and the identity of the visual trajectory is confirmed. Combined with the analysis of the position change and appearance change of visual objects, wireless positioning results are fused to correct the affected visual trajectory to improve overall system performance. A tracking system was deployed in the real world. The fusion path is proved to be closer to the real path and 90% of the errors were less than 1m. We have also implemented large-scale simulation experiments to evaluate our approach. The results show that our association algorithm has a high matching success rate and is insensitive to synchronization errors.","PeriodicalId":142681,"journal":{"name":"2021 28th International Conference on Telecommunications (ICT)","volume":"18 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":"128075865","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}
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