2022 IEEE 6th International Symposium on Telecommunication Technologies (ISTT)最新文献

Intelligent Reflecting Surfaces Aided Millimetre Wave Blockage Prediction For Vehicular Communication 基于智能反射面辅助的车载通信毫米波阻塞预测

2022 IEEE 6th International Symposium on Telecommunication Technologies (ISTT) Pub Date : 2022-11-14 DOI: 10.1109/ISTT56288.2022.9966540

Fu Seong Woon, C. Leow

{"title":"Intelligent Reflecting Surfaces Aided Millimetre Wave Blockage Prediction For Vehicular Communication","authors":"Fu Seong Woon, C. Leow","doi":"10.1109/ISTT56288.2022.9966540","DOIUrl":"https://doi.org/10.1109/ISTT56288.2022.9966540","url":null,"abstract":"The ability of millimeter-wave (mmWave) to deliver gigabit throughput has led to its widespread adoption in Fifth Generation (5G) networks. However, mmWave links between Base Station (BS) and users can be easily obstructed by obstacles. In vehicular networks with dynamic environments and mobile users, the mmWave link blockage issue is even more pronounced. In order to preserve the mmWave link in the vehicular network, it is necessary to predict blockages. For blockage prediction, sensor information from Lidar, Radar, and cameras has been considered. Nonetheless, these non-radio frequency methods necessitate the use of additional equipment and signal processing, which raises the implementation cost and complexity. The existing literature also considers the use of BS and user’s Radio Frequency (RF) signatures to predict blockage. However, users’ mobility has not been taken into account. An Intelligent Reflecting Surface (IRS), on the other hand, has been viewed as a promising method for providing an alternate path by reflecting the mmWave signal between the BS and user in order to improve the reliability of vehicular networks. Therefore, this research investigates the IRS-assisted blockage prediction in order to determine the future link status in the vehicular environment with respect to user mobility. The proposed solution employs a number of active elements that are randomly distributed on the IRS to obtain the RF signatures. Furthermore, it utilises Machine Learning (ML) techniques to learn the pre-blockage wireless signatures, which can predict future blockages. The results indicate that the proposed method can predict blockages between a single IRS and a moving user with a greater than 98 percent accuracy up to one second before they occur.","PeriodicalId":389716,"journal":{"name":"2022 IEEE 6th International Symposium on Telecommunication Technologies (ISTT)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133706659","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}

引用次数: 0

DeepB2B2XSlice Engine - An O-RAN Slice Selection and Resource Optimization AI Engine DeepB2B2XSlice引擎-一个O-RAN切片选择和资源优化人工智能引擎

2022 IEEE 6th International Symposium on Telecommunication Technologies (ISTT) Pub Date : 2022-11-14 DOI: 10.1109/ISTT56288.2022.9966553

S. Singh, T. kumar, Ashish Pant, Rohit Mahalle

{"title":"DeepB2B2XSlice Engine - An O-RAN Slice Selection and Resource Optimization AI Engine","authors":"S. Singh, T. kumar, Ashish Pant, Rohit Mahalle","doi":"10.1109/ISTT56288.2022.9966553","DOIUrl":"https://doi.org/10.1109/ISTT56288.2022.9966553","url":null,"abstract":"With CSPs (communication service provider) making a lot of investment in 5G infrastructure, generating a return is bound to be a top priority. For 5G network slicing, the ability to service all types of connectivity across common network infrastructure, as well as enable operators to open their networks to B2B2X industries using analytics is key to tapping into the massive projected revenue opportunities. Optimizing Slice allocation and slice selection using machine learning, Deep Learning, and AI (Artificial Intelligence) will be key to generate revenue for CSPs for various B2B2X uses cases on basis of type of device, mobility, Latency requirement, etc. For this purpose, we are introducing O-RAN (Open-Radio Access Network) DeepB2B2XSlice Slice selection and resource optimization Engine. O-RAN DeepB2B2XSlice Engine will identify Service degradation parameter and optimize Slice resources to handle failures in future by deep learning algorithms, improve efficiency and meet SLA(Service Level Agreement) performance requirements. Engine will also perform slice selection optimization function based on SLA requirement, DeepB2B2XSlice Engine will recommend optimize Slice RAN resources parameters based on data analysis from historical data in response allocation request from operator.","PeriodicalId":389716,"journal":{"name":"2022 IEEE 6th International Symposium on Telecommunication Technologies (ISTT)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123961160","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}

引用次数: 0

A Novel Cost-Effective Data and Service Availability Approach in Machine-to-Machine Communication Network 机器对机器通信网络中一种经济有效的数据和服务可用性新方法

2022 IEEE 6th International Symposium on Telecommunication Technologies (ISTT) Pub Date : 2022-11-14 DOI: 10.1109/ISTT56288.2022.9966539

S. Ullah, Raja Zahilah, Marina Md Arshad

引用次数: 0

Internet of Medical Things Based Telemedicine Framework for Remote Patients Triage and Emergency Medical Services 基于医疗物联网的远程医疗框架，用于远程患者分诊和紧急医疗服务

2022 IEEE 6th International Symposium on Telecommunication Technologies (ISTT) Pub Date : 2022-11-14 DOI: 10.1109/ISTT56288.2022.9966532

Omar Sadeq Salman, N. A. A. Latiff, S. Arifin, O. Salman, Fahad Taha Al-Dhief

引用次数: 0

Evaluation and Use of Interference Matrix for FBMC-OQAM Transceiver FBMC-OQAM收发器干扰矩阵的评估与应用

2022 IEEE 6th International Symposium on Telecommunication Technologies (ISTT) Pub Date : 2022-11-14 DOI: 10.1109/ISTT56288.2022.9966537

D. Mattera, M. Tanda

引用次数: 0

Energy Coverage Analysis of Millimeter Wave Wireless Power Transfer 毫米波无线电力传输的能量覆盖分析

2022 IEEE 6th International Symposium on Telecommunication Technologies (ISTT) Pub Date : 2022-11-14 DOI: 10.1109/ISTT56288.2022.9966536

Nur Atikah Azali, N. A. Muhammad, N. Apandi, N. Sunar, N. H. Wahab

{"title":"Energy Coverage Analysis of Millimeter Wave Wireless Power Transfer","authors":"Nur Atikah Azali, N. A. Muhammad, N. Apandi, N. Sunar, N. H. Wahab","doi":"10.1109/ISTT56288.2022.9966536","DOIUrl":"https://doi.org/10.1109/ISTT56288.2022.9966536","url":null,"abstract":"The millimeter wave (MMW) region received great interest in wireless communication applications as it provides large bandwidth ranging from 30 GHz to 300 GHz. MMW communication is a new feature of fifth-generation (5G) and beyond 5G cellular networks. The large antenna arrays that will be implemented in the MMW system potentially increase user performance. Since the MMW system performance closely depends on the antenna gain, a suitable antenna pattern model is crucial to predict the MMW system performance before the real base station implementation. This paper presents a simplified antenna model known as a modified sectored (M-sectored) antenna that incorporates the number of antenna elements. Leveraging the concept of stochastic geometry, this paper analyze the energy coverage probability of MMW wireless power transfer. The locations of base station and users are modeled following Poisson point processes (PPP), and then the effect of the antenna model is investigated. This study had demonstrated that the energy coverage probability (ECP) of the proposed antenna model matches the actual antenna gain pattern. In addition, the effects of the base station density and blockage parameter are also observed.","PeriodicalId":389716,"journal":{"name":"2022 IEEE 6th International Symposium on Telecommunication Technologies (ISTT)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114855913","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}

引用次数: 0

Implications of Centralized and Distributed Multi-Agent Deep Reinforcement Learning in Dynamic Spectrum Access 集中式和分布式多智能体深度强化学习在动态频谱访问中的意义

2022 IEEE 6th International Symposium on Telecommunication Technologies (ISTT) Pub Date : 2022-11-14 DOI: 10.1109/ISTT56288.2022.9966551

Abdikarim Mohamed Ibrahim, K. Yau, Mee Hong Ling

引用次数: 1

Equalization with Time Domain Preprocessing for OFDM and FBMC in Flat Fading Fast Varying Channels 基于时域预处理的OFDM和FBMC平衰落快变信道均衡

2022 IEEE 6th International Symposium on Telecommunication Technologies (ISTT) Pub Date : 2022-11-14 DOI: 10.1109/ISTT56288.2022.9966542

Ahmad Hamdan, Hussein Hijazi, L. Ros, A. Ghouwayel, C. Siclet

{"title":"Equalization with Time Domain Preprocessing for OFDM and FBMC in Flat Fading Fast Varying Channels","authors":"Ahmad Hamdan, Hussein Hijazi, L. Ros, A. Ghouwayel, C. Siclet","doi":"10.1109/ISTT56288.2022.9966542","DOIUrl":"https://doi.org/10.1109/ISTT56288.2022.9966542","url":null,"abstract":"In Multi-Carrier (MC) systems, all equalization and detection procedures are classically performed at the sub-carrier level after the received signal is projected into the frequency domain. Besides, in the presence of rapid channel variation, conventional receivers suffer from critical performance degradation caused by interference. To address this specific problem, we propose to add a low-complexity time domain preprocessing prior to the frequency domain equalization process. We specifically study Orthogonal Frequency Division Multiplexing (OFDM) and Filter-Bank Multi-Carrier (FBMC) over single-path fast-varying Rayleigh channels when using the proposed scheme. Two time domain preprocessing techniques are considered. Their impact on equalization performance is evaluated in perfect and imperfect Channel State Information (CSI) scenarios, showing robustness to reasonable channel estimation errors. For both systems, a reduction in Bit Error Rate (BER) is obtained thanks to the preprocessing. Furthermore, the proposed scheme allows for capturing time diversity leading to improvement in performance for faster channel variation, rather than inducing performance degradation, showing the relevance of our approach. For OFDM, this preprocessing allows reaching the best performance compared to the existing equalizers at significant lower complexity. For FBMC, it permits to obtain a performance gain of 10 dB at $F_{d}T_{S}=0.25$, while avoiding the BER floor effect. This gain is observed at BER =$2times$ $10^{-2}$ for scenarios accepting Inter-Symbol Interference (ISI), and at BER =1$0^{-3}$ when assuming perfect ISI cancellation. For the latter scenario, we obtain performance very close to the (computationally intractable) optimum Maximum-Likelihood equalizer.","PeriodicalId":389716,"journal":{"name":"2022 IEEE 6th International Symposium on Telecommunication Technologies (ISTT)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124399725","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}

引用次数: 0

ISTT 2022 Cover Page ISTT 2022封面

2022 IEEE 6th International Symposium on Telecommunication Technologies (ISTT) Pub Date : 2022-11-14 DOI: 10.1109/istt56288.2022.9966550

引用次数: 0

Dysphonia Detection Based on Voice Signals Using Naive Bayes Classifier 基于朴素贝叶斯分类器的语音信号语音障碍检测

2022 IEEE 6th International Symposium on Telecommunication Technologies (ISTT) Pub Date : 2022-11-14 DOI: 10.1109/ISTT56288.2022.9966535

Fahad Taha Al-Dhief, N. A. A. Latiff, N. A. Malik, M. Baki, N. Sabri, Musatafa Abbas Abbood Albadr

{"title":"Dysphonia Detection Based on Voice Signals Using Naive Bayes Classifier","authors":"Fahad Taha Al-Dhief, N. A. A. Latiff, N. A. Malik, M. Baki, N. Sabri, Musatafa Abbas Abbood Albadr","doi":"10.1109/ISTT56288.2022.9966535","DOIUrl":"https://doi.org/10.1109/ISTT56288.2022.9966535","url":null,"abstract":"Voice pathology detection has gained a lot of attention in the last few decades. Furthermore, this field is considered an active topic in the healthcare area. However, most machine learning techniques are proposed to differentiate the healthy voice from the pathological voice only, where there is a lack of identification of a certain voice disease. Therefore, this work presents a method for detecting Dysphonia Disease (DD), which belongs to the pathology detection application. The proposed method uses the Naive Bayes (NB) algorithm as a classifier in order to identify the dysphonia (pathological) class from the healthy (normal) class. In addition, the Mel-Frequency Cepstral Coefficient (MFCC) is used for extracting the acoustic features. The acoustic signals used in this method were gained from the Saarbrucken Voice Database (SVD). Several evaluation measurements have been used to assess the proposed method. The experiment results indicate that the NB classifier obtained an accuracy of 81.48%, 65% sensitivity, a specificity of 91.17%, and a 76.98% G-mean. Further, the precision and F1-score are 81.25% and 72.22%, respectively.","PeriodicalId":389716,"journal":{"name":"2022 IEEE 6th International Symposium on Telecommunication Technologies (ISTT)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131643430","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}

引用次数: 1