Pub Date : 2021-12-15DOI: 10.1109/ACTS53447.2021.9708340
S. Deepak, Sanuj Sahoo, D. Patra
Super-resolution (SR) reconstruction of thermal images has been one of the most active research areas specifically for industrial applications. However, most of the conventional RGB SR models available in the literature are not necessarily applicable to thermal images due to their difference in characteristics when compared to normal camera images. The recent advancement in the field of deep learning-based SR has helped achieve unbelievable results. Despite the advancement in models like deep convolution neural networks (CNN) and Generative adversarial networks, there remain multiple problems unsolved that will help improve the spatial resolution of thermal images. Not only the developed model should be computationally efficient but also easily implementable in industrial applications. Motivated to overcome the said limitations, in this work a generative adversarial network (GAN) based single images super-resolution architecture is proposed for thermal camera images. The developed model not only generates at par results with the other model but also is easy to implement and computationally efficient. The modified architecture has an identical layout inspired by SRGAN. In order to make the model faster to train while having less training parameters, the number of residual blocks was reduced to 5. The batch normalization layers were excluded from the residual blocks of both the Generator and Discriminator networks to remove the redundancy. Before each convolution layer, reflective padding is utilized at the edges to preserve the size of the feature maps. The comparative results revealed that the proposed network trained on thermal images produced high-quality images with enhanced details, while still maintaining image features and perspective throughout. The experimental results show that the proposed model has achieved a reduction in computation time compared to the State-of-the-Art method. The suggested strategy has outperformed the SOTA methods with the improvement of approximately 2dB in PSNR along with 0.9825 of SSIM.
{"title":"Super-Resolution of Thermal Images Using GAN Network","authors":"S. Deepak, Sanuj Sahoo, D. Patra","doi":"10.1109/ACTS53447.2021.9708340","DOIUrl":"https://doi.org/10.1109/ACTS53447.2021.9708340","url":null,"abstract":"Super-resolution (SR) reconstruction of thermal images has been one of the most active research areas specifically for industrial applications. However, most of the conventional RGB SR models available in the literature are not necessarily applicable to thermal images due to their difference in characteristics when compared to normal camera images. The recent advancement in the field of deep learning-based SR has helped achieve unbelievable results. Despite the advancement in models like deep convolution neural networks (CNN) and Generative adversarial networks, there remain multiple problems unsolved that will help improve the spatial resolution of thermal images. Not only the developed model should be computationally efficient but also easily implementable in industrial applications. Motivated to overcome the said limitations, in this work a generative adversarial network (GAN) based single images super-resolution architecture is proposed for thermal camera images. The developed model not only generates at par results with the other model but also is easy to implement and computationally efficient. The modified architecture has an identical layout inspired by SRGAN. In order to make the model faster to train while having less training parameters, the number of residual blocks was reduced to 5. The batch normalization layers were excluded from the residual blocks of both the Generator and Discriminator networks to remove the redundancy. Before each convolution layer, reflective padding is utilized at the edges to preserve the size of the feature maps. The comparative results revealed that the proposed network trained on thermal images produced high-quality images with enhanced details, while still maintaining image features and perspective throughout. The experimental results show that the proposed model has achieved a reduction in computation time compared to the State-of-the-Art method. The suggested strategy has outperformed the SOTA methods with the improvement of approximately 2dB in PSNR along with 0.9825 of SSIM.","PeriodicalId":201741,"journal":{"name":"2021 Advanced Communication Technologies and Signal Processing (ACTS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130545436","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 : 2021-12-15DOI: 10.1109/ACTS53447.2021.9708215
Mangal Singh, Saurav Gupta, S. Yadav, Vipin Pal, S. K. Patra
With the advancement of the light-emitting diode (LED), the use of light as a communication medium has progressed in new directions. Visible light communication (VLC) makes use of white light emitting diodes (LED), which send data through glimmering light at speeds imperceptible to the naked eye. Thus, this paper formulated the VLC based system for indoor applications and evaluate its performance considering various parameters such as optical power distribution (OPD), signal to noise ratio (SNR) and channel delay spread (CDS). The observation of the OPD of a single LED transmitter and a single receiver along with 4 transmitters and receivers in a typical room has been considered. The other performance matrices such as SNR and CDS of VLC is also analyses and simulated using MATLAB software.
{"title":"Performance Evaluation of Visible Light Communication System based on Optical Power Distribution with Channel Delay Spread and SNR","authors":"Mangal Singh, Saurav Gupta, S. Yadav, Vipin Pal, S. K. Patra","doi":"10.1109/ACTS53447.2021.9708215","DOIUrl":"https://doi.org/10.1109/ACTS53447.2021.9708215","url":null,"abstract":"With the advancement of the light-emitting diode (LED), the use of light as a communication medium has progressed in new directions. Visible light communication (VLC) makes use of white light emitting diodes (LED), which send data through glimmering light at speeds imperceptible to the naked eye. Thus, this paper formulated the VLC based system for indoor applications and evaluate its performance considering various parameters such as optical power distribution (OPD), signal to noise ratio (SNR) and channel delay spread (CDS). The observation of the OPD of a single LED transmitter and a single receiver along with 4 transmitters and receivers in a typical room has been considered. The other performance matrices such as SNR and CDS of VLC is also analyses and simulated using MATLAB software.","PeriodicalId":201741,"journal":{"name":"2021 Advanced Communication Technologies and Signal Processing (ACTS)","volume":"222 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130654909","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 : 2021-12-15DOI: 10.1109/ACTS53447.2021.9708195
Ravi Chopra, J. Dhar, Vinal Patel
Data is overflowing day by day. The use of face recognition is rapidly picking up pace due to the boom in data and available computation power. The research done in this field is at an unimaginable pace, and accuracies of more than 99% have been achieved, which are possibly less only by Baye’s error. However, there is still room for experimentation. This paper tries to build a model by mixing two novel ideas of face recognition - ArcFace and LinCos. In this paper, the target is to manipulate the Additive Angular Margin Loss used by ArcFace by incorporating the ideas of LinCos. We re-train the pre-trained ArcFace model using Mobile FaceNet with a modified loss function. The results suggest that our model optimizes at a faster rate as compared to the ArcFace and LinCos models.
{"title":"LinArc - Deep Face Recognition Using LinCos And ArcFace","authors":"Ravi Chopra, J. Dhar, Vinal Patel","doi":"10.1109/ACTS53447.2021.9708195","DOIUrl":"https://doi.org/10.1109/ACTS53447.2021.9708195","url":null,"abstract":"Data is overflowing day by day. The use of face recognition is rapidly picking up pace due to the boom in data and available computation power. The research done in this field is at an unimaginable pace, and accuracies of more than 99% have been achieved, which are possibly less only by Baye’s error. However, there is still room for experimentation. This paper tries to build a model by mixing two novel ideas of face recognition - ArcFace and LinCos. In this paper, the target is to manipulate the Additive Angular Margin Loss used by ArcFace by incorporating the ideas of LinCos. We re-train the pre-trained ArcFace model using Mobile FaceNet with a modified loss function. The results suggest that our model optimizes at a faster rate as compared to the ArcFace and LinCos models.","PeriodicalId":201741,"journal":{"name":"2021 Advanced Communication Technologies and Signal Processing (ACTS)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130738319","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 : 2021-12-15DOI: 10.1109/ACTS53447.2021.9708250
Laxmi Narayana Deekonda, S. Sahu, A. Panda
This paper presents a broadband terahertz (THz) metamaterial absorber. The unit cell structure of this absorber consists of three layers. The top layer of the structure contains a circular graphene ring. At the center frequency of 2THz, this circular graphene ring has a fractional bandwidth of 67% and absorptivity of more than 90%. The proposed absorber is polarization insensitive because of its fourfold symmetrical structure. The graphene parameter is optimized to get maximum bandwidth. This metamaterial offers TE and TM polarization insensitive up to a 60° incident angle of electro-magnetic wave.
{"title":"A Graphene-Based Broadband Metamaterial Absorber","authors":"Laxmi Narayana Deekonda, S. Sahu, A. Panda","doi":"10.1109/ACTS53447.2021.9708250","DOIUrl":"https://doi.org/10.1109/ACTS53447.2021.9708250","url":null,"abstract":"This paper presents a broadband terahertz (THz) metamaterial absorber. The unit cell structure of this absorber consists of three layers. The top layer of the structure contains a circular graphene ring. At the center frequency of 2THz, this circular graphene ring has a fractional bandwidth of 67% and absorptivity of more than 90%. The proposed absorber is polarization insensitive because of its fourfold symmetrical structure. The graphene parameter is optimized to get maximum bandwidth. This metamaterial offers TE and TM polarization insensitive up to a 60° incident angle of electro-magnetic wave.","PeriodicalId":201741,"journal":{"name":"2021 Advanced Communication Technologies and Signal Processing (ACTS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125800927","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 : 2021-12-15DOI: 10.1109/ACTS53447.2021.9708363
B. A. Babu, Madhav Boddapati, Kantamneni Srilatha
This study gives a compact, low-profile, and flexible Artificial Magnetic Conductor (AMC) surface integrated antenna design that provides low SAR (Specific Absorption Rate) and improved radiation performance. The antenna is designed using a flexible polyimide substrate with dimensions 14×14×0.1 mm3 that makes resonance at 5.2 GHz frequency. It provides a gain of 1.05 dBi in standalone condition. The flexible substrate PDMS (Polydimethylsiloxane) is used for AMC design that provides the improved gain of 3.12 dBi. The dimension of AMC unit cell is 8×8.8×1 mm3. It provides a low SAR of 0.707 W/Kg for 10g of tissue model with a separation of 10 mm. The design and analysis are performed using CST Microwave Studio (CST MWS) tool. The designed antenna is significant at Industrial, Scientific, and Medical (ISM) band applications for wearable devices.
{"title":"AMC based Flexible Wearable Antenna with low SAR and Improved Gain for ISM band Applications","authors":"B. A. Babu, Madhav Boddapati, Kantamneni Srilatha","doi":"10.1109/ACTS53447.2021.9708363","DOIUrl":"https://doi.org/10.1109/ACTS53447.2021.9708363","url":null,"abstract":"This study gives a compact, low-profile, and flexible Artificial Magnetic Conductor (AMC) surface integrated antenna design that provides low SAR (Specific Absorption Rate) and improved radiation performance. The antenna is designed using a flexible polyimide substrate with dimensions 14×14×0.1 mm3 that makes resonance at 5.2 GHz frequency. It provides a gain of 1.05 dBi in standalone condition. The flexible substrate PDMS (Polydimethylsiloxane) is used for AMC design that provides the improved gain of 3.12 dBi. The dimension of AMC unit cell is 8×8.8×1 mm3. It provides a low SAR of 0.707 W/Kg for 10g of tissue model with a separation of 10 mm. The design and analysis are performed using CST Microwave Studio (CST MWS) tool. The designed antenna is significant at Industrial, Scientific, and Medical (ISM) band applications for wearable devices.","PeriodicalId":201741,"journal":{"name":"2021 Advanced Communication Technologies and Signal Processing (ACTS)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128701865","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 : 2021-12-15DOI: 10.1109/ACTS53447.2021.9708190
A. Bhattacharjee, R. Murugan, Tripti Goel, B. Soni
Latest advancements in deep learning have led to an enthusiasm among biomedical researchers to explore the field of semantic segmentation further. Lungs segmentation plays a crucial role in the computer-aided diagnosis of several lung diseases. However, various anatomical varieties make lungs segmentation a challenging task. The main objective of our study is to propose a modified U-Net model that automatically segments the lungs from the computed tomography images. The proposed algorithm is trained on 240 training images. The advantage of this architecture is that it consumes less data and GPU memory. Experimental results show that the proposed architecture obtained 98.3% accuracy, 96.29% dice coefficient, and 93.63% Jaccard index. The segmentation model outperformed the original U-Net and the state-of-the-art methods. Thus, the modified U-Net model is apt for accurate lung segmentation.
{"title":"Semantic segmentation of lungs using a modified U-Net architecture through limited Computed Tomography images","authors":"A. Bhattacharjee, R. Murugan, Tripti Goel, B. Soni","doi":"10.1109/ACTS53447.2021.9708190","DOIUrl":"https://doi.org/10.1109/ACTS53447.2021.9708190","url":null,"abstract":"Latest advancements in deep learning have led to an enthusiasm among biomedical researchers to explore the field of semantic segmentation further. Lungs segmentation plays a crucial role in the computer-aided diagnosis of several lung diseases. However, various anatomical varieties make lungs segmentation a challenging task. The main objective of our study is to propose a modified U-Net model that automatically segments the lungs from the computed tomography images. The proposed algorithm is trained on 240 training images. The advantage of this architecture is that it consumes less data and GPU memory. Experimental results show that the proposed architecture obtained 98.3% accuracy, 96.29% dice coefficient, and 93.63% Jaccard index. The segmentation model outperformed the original U-Net and the state-of-the-art methods. Thus, the modified U-Net model is apt for accurate lung segmentation.","PeriodicalId":201741,"journal":{"name":"2021 Advanced Communication Technologies and Signal Processing (ACTS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114084292","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 : 2021-12-15DOI: 10.1109/ACTS53447.2021.9708241
Prashanth Kannadaguli
Due to expanded praxis of social media, there is an elevated interest in the Natural Language Processing (NLP) of textual substance. Code swapping is a ubiquitous paradox in multilingual nation and the social communication shows mixing of a low resourced language with a highly resourced language mostly written in non-native script in the same text. It is essential to refine the code swapped text to support distinctive NLP tasks such as Machine Translation, Automated Conversational Systems and Sentiment Analysis (SA). The preeminent objective of SA is to identify and analyze the attitude, opinion, emotion or the sentiment in the dataset. Though there are multiple systems skilled on monodialectal dataset, all of them break down when it comes for code-diverse data because of the heightened intricacy of blending at various standards of text. Nonetheless, there exist a smaller number of assets for modelling such definitive code-mixed data and the Machine Learning or the Deep Learning algorithms enforcing supervised learning approach yield the better results compared to the unsupervised learning. Such datasets are available for Hindi-English, Tamil-English, Malayalam-English, Bengali-English, German-English, Spanish-English, Japanese-English, Arabic-English etc. Though our research is concentrated towards NLP for emotion and sentiment detection of Tulu, a vibrant south Indian language, to start with, we build the first ever platinum standard corpus for NLP applications of code-diverse text in Tulu-English, as there is no such resource in our native language. The performance analysis of our dataset through Krippendorff’s Alpha value of 0.9 indicates that it is a benchmark in development of Automatic Sentiment Analysis system for Tulu.
{"title":"A Code-Diverse Tulu-English Dataset For NLP Based Sentiment Analysis Applications","authors":"Prashanth Kannadaguli","doi":"10.1109/ACTS53447.2021.9708241","DOIUrl":"https://doi.org/10.1109/ACTS53447.2021.9708241","url":null,"abstract":"Due to expanded praxis of social media, there is an elevated interest in the Natural Language Processing (NLP) of textual substance. Code swapping is a ubiquitous paradox in multilingual nation and the social communication shows mixing of a low resourced language with a highly resourced language mostly written in non-native script in the same text. It is essential to refine the code swapped text to support distinctive NLP tasks such as Machine Translation, Automated Conversational Systems and Sentiment Analysis (SA). The preeminent objective of SA is to identify and analyze the attitude, opinion, emotion or the sentiment in the dataset. Though there are multiple systems skilled on monodialectal dataset, all of them break down when it comes for code-diverse data because of the heightened intricacy of blending at various standards of text. Nonetheless, there exist a smaller number of assets for modelling such definitive code-mixed data and the Machine Learning or the Deep Learning algorithms enforcing supervised learning approach yield the better results compared to the unsupervised learning. Such datasets are available for Hindi-English, Tamil-English, Malayalam-English, Bengali-English, German-English, Spanish-English, Japanese-English, Arabic-English etc. Though our research is concentrated towards NLP for emotion and sentiment detection of Tulu, a vibrant south Indian language, to start with, we build the first ever platinum standard corpus for NLP applications of code-diverse text in Tulu-English, as there is no such resource in our native language. The performance analysis of our dataset through Krippendorff’s Alpha value of 0.9 indicates that it is a benchmark in development of Automatic Sentiment Analysis system for Tulu.","PeriodicalId":201741,"journal":{"name":"2021 Advanced Communication Technologies and Signal Processing (ACTS)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115498151","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 : 2021-12-15DOI: 10.1109/ACTS53447.2021.9708301
Aman Sanwal, Shekhar Singh, P. M. Pradhan
The 5G mobile networks aim to accomplish the austere requirements on data rates, reliability, and connectivity. In order to achieve these objectives, heterogeneous radio access technologies are used. In order to use the technology efficiently, massive connectivity of devices has been proposed in 3GPP Release 15. In the stand alone architecture, small base stations are deployed without any dependency on LTE core network. Increase in the number of devices will lead to an increase in signalling overhead consisting of tracking area update and paging overhead. This paper proposes an approach to reduce the signalling cost using clustering algorithm. The base stations form clusters using the proposed algorithm, and act as static cluster heads. The clustering algorithm is used to connect different types of User Equipments (UEs), including the vehicles, machines and various stationary IoT devices. In addition, this paper also deals with a hybrid scenario which represents the unification of both the layers (LTE and NR) for the initial rollout of the 5G to fill the coverage gaps. Simulation results show that the proposed scheme provides better performance in terms of reduced energy consumption by the UEs.
{"title":"Development of an Algorithm for Reducing Signalling Overhead Cost in 5G Networks","authors":"Aman Sanwal, Shekhar Singh, P. M. Pradhan","doi":"10.1109/ACTS53447.2021.9708301","DOIUrl":"https://doi.org/10.1109/ACTS53447.2021.9708301","url":null,"abstract":"The 5G mobile networks aim to accomplish the austere requirements on data rates, reliability, and connectivity. In order to achieve these objectives, heterogeneous radio access technologies are used. In order to use the technology efficiently, massive connectivity of devices has been proposed in 3GPP Release 15. In the stand alone architecture, small base stations are deployed without any dependency on LTE core network. Increase in the number of devices will lead to an increase in signalling overhead consisting of tracking area update and paging overhead. This paper proposes an approach to reduce the signalling cost using clustering algorithm. The base stations form clusters using the proposed algorithm, and act as static cluster heads. The clustering algorithm is used to connect different types of User Equipments (UEs), including the vehicles, machines and various stationary IoT devices. In addition, this paper also deals with a hybrid scenario which represents the unification of both the layers (LTE and NR) for the initial rollout of the 5G to fill the coverage gaps. Simulation results show that the proposed scheme provides better performance in terms of reduced energy consumption by the UEs.","PeriodicalId":201741,"journal":{"name":"2021 Advanced Communication Technologies and Signal Processing (ACTS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124486328","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 : 2021-12-15DOI: 10.1109/ACTS53447.2021.9708264
Tarun Singhania, W. Arif, D. Sen
Bottleneck Bandwidth and Round-trip time (BBR) congestion control is the first congestion control to claim to operate at Kleinrock’s optimal operating point without filling up queues and high packet loss. Recent research on BBR revealed that inter protocol unfairness was observed in terms of bandwidth share due to the insignificant queue share occupied by loss based Congestion Control Algorithm (CCA) flows when bottleneck buffer size shared by the flows were less than two times the product of bandwidth and delay (BDP) for the bottleneck link. Also, when buffer sizes exceeded twice its BDP, the longer Round Trip Time (RTT) BBR flows dominated over shorter RTT BBR flows by grasping a greater portion of bottleneck link bandwidth (intra protocol unfairness). As inter protocol unfairness can cause other TCP variants to lose throughput and CUBIC is still one of the most widely used CCA’s, it is important to establish fairness. Inter protocol unfairness can currently allow latency cheating which allows individuals to add artificial latency to get a better share of bandwidth. In this paper, we present Bottleneck Bandwidth Buffer and Round-trip propagation time (B3R) which uses a modified BBR Congestion Control Algorithm (CCA) when operating under the above mentioned bottleneck buffer sizes to reduce inter/intra protocol unfairness. The results obtained after testing the algorithm are very encouraging; B3R improved inter protocol fairness by increasing CUBIC flows from 3% of bottleneck link bandwidth up to 31% and ensured complete intra B3R fairness for up to 4x RTT differences. B3R also helped reduce queue formation on the bottleneck by up to 50%
{"title":"Modelling and Analysis of Large Buffer Probe for B3R Congestion Control Algorithm","authors":"Tarun Singhania, W. Arif, D. Sen","doi":"10.1109/ACTS53447.2021.9708264","DOIUrl":"https://doi.org/10.1109/ACTS53447.2021.9708264","url":null,"abstract":"Bottleneck Bandwidth and Round-trip time (BBR) congestion control is the first congestion control to claim to operate at Kleinrock’s optimal operating point without filling up queues and high packet loss. Recent research on BBR revealed that inter protocol unfairness was observed in terms of bandwidth share due to the insignificant queue share occupied by loss based Congestion Control Algorithm (CCA) flows when bottleneck buffer size shared by the flows were less than two times the product of bandwidth and delay (BDP) for the bottleneck link. Also, when buffer sizes exceeded twice its BDP, the longer Round Trip Time (RTT) BBR flows dominated over shorter RTT BBR flows by grasping a greater portion of bottleneck link bandwidth (intra protocol unfairness). As inter protocol unfairness can cause other TCP variants to lose throughput and CUBIC is still one of the most widely used CCA’s, it is important to establish fairness. Inter protocol unfairness can currently allow latency cheating which allows individuals to add artificial latency to get a better share of bandwidth. In this paper, we present Bottleneck Bandwidth Buffer and Round-trip propagation time (B3R) which uses a modified BBR Congestion Control Algorithm (CCA) when operating under the above mentioned bottleneck buffer sizes to reduce inter/intra protocol unfairness. The results obtained after testing the algorithm are very encouraging; B3R improved inter protocol fairness by increasing CUBIC flows from 3% of bottleneck link bandwidth up to 31% and ensured complete intra B3R fairness for up to 4x RTT differences. B3R also helped reduce queue formation on the bottleneck by up to 50%","PeriodicalId":201741,"journal":{"name":"2021 Advanced Communication Technologies and Signal Processing (ACTS)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130263339","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 : 2021-12-15DOI: 10.1109/ACTS53447.2021.9708174
K. Kola, A. Chatterjee
A printed array of microstrip radiators for DBS applications has been reported in this paper. The sole element is derived from a nature-inspired Tulip-flower-shaped geometry whose resonated at 12.50 GHz. One regular ellipse and pair of semi-ellipses are jointly formed the proposed structure, and in order to resonate at the desired frequency, an anchor-shaped slotted structure is etched from the center of the resultant geometry. The single proposed element’s time-domain parameters has been analysed for side-by-side and face-to-face arrangements. The feed network of the array is designed based on Wilkinson power divider and achieve a low-loss, high-isolation, and better impedance bandwidth responses. The antenna and the array are offered the directivity of 9.36 and 14.96 dBi, respectively. A 100% bandwidth coverage, a shallow x-pol. along the main-beam direction, immense radiation efficiency, and satisfactory electromagnetic compatibility performances have been achieved from both antennas. The antennas are convenient for DBS applications.
{"title":"An Array of Tulip-Flower Shaped Printed Radiators for Direct Broadcast Satellite (DBS) Applications","authors":"K. Kola, A. Chatterjee","doi":"10.1109/ACTS53447.2021.9708174","DOIUrl":"https://doi.org/10.1109/ACTS53447.2021.9708174","url":null,"abstract":"A printed array of microstrip radiators for DBS applications has been reported in this paper. The sole element is derived from a nature-inspired Tulip-flower-shaped geometry whose resonated at 12.50 GHz. One regular ellipse and pair of semi-ellipses are jointly formed the proposed structure, and in order to resonate at the desired frequency, an anchor-shaped slotted structure is etched from the center of the resultant geometry. The single proposed element’s time-domain parameters has been analysed for side-by-side and face-to-face arrangements. The feed network of the array is designed based on Wilkinson power divider and achieve a low-loss, high-isolation, and better impedance bandwidth responses. The antenna and the array are offered the directivity of 9.36 and 14.96 dBi, respectively. A 100% bandwidth coverage, a shallow x-pol. along the main-beam direction, immense radiation efficiency, and satisfactory electromagnetic compatibility performances have been achieved from both antennas. The antennas are convenient for DBS applications.","PeriodicalId":201741,"journal":{"name":"2021 Advanced Communication Technologies and Signal Processing (ACTS)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121110194","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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