Pub Date : 2021-07-27DOI: 10.1109/NCC52529.2021.9530173
Ekagra Ranjan, Ameya Vikram, A. Rajesh, P. Bora
Sparse Code Multiple Access (SCMA) is an effective non-orthogonal multiple access technique that facilitates communication among users with limited orthogonal resources. Currently, its performance is limited by the quality of the handcrafted codebook. We propose Auto-SCMA, a machine learning based approach that learns the codebook using gradient descent while using a Message Passing Algorithm decoder. It is the first machine learning based approach to generalize successfully on the Rayleigh fading channel. It is able to learn an effective codebook without involving any human effort in the process. Our experimental results show that Auto-SCMA outperforms previous methods including machine learning based methods.
{"title":"Auto-SCMA: Learning Codebook for Sparse Code Multiple Access using Machine Learning","authors":"Ekagra Ranjan, Ameya Vikram, A. Rajesh, P. Bora","doi":"10.1109/NCC52529.2021.9530173","DOIUrl":"https://doi.org/10.1109/NCC52529.2021.9530173","url":null,"abstract":"Sparse Code Multiple Access (SCMA) is an effective non-orthogonal multiple access technique that facilitates communication among users with limited orthogonal resources. Currently, its performance is limited by the quality of the handcrafted codebook. We propose Auto-SCMA, a machine learning based approach that learns the codebook using gradient descent while using a Message Passing Algorithm decoder. It is the first machine learning based approach to generalize successfully on the Rayleigh fading channel. It is able to learn an effective codebook without involving any human effort in the process. Our experimental results show that Auto-SCMA outperforms previous methods including machine learning based methods.","PeriodicalId":414087,"journal":{"name":"2021 National Conference on Communications (NCC)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134461343","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 : 2021-07-27DOI: 10.1109/NCC52529.2021.9530070
Manjeer Majumder, A. Jagannatham
This paper develops a novel data dependent superimposed training technique for channel estimation in generic block transmission (BT) systems comprising of single/multi-carrier (SC/MC) and zero-padded (ZP)/ cyclic prefix (CP) systems. The training sequence comprises of the summation of a known training sequence and a data-dependent sequence that is not known to the receiver. A unique aspect of the scheme is that the channel estimation is not affected by the use of a data-dependent sequence. The pilot design framework is conceived in order to minimize the Bayesian Cramér-Rao bound (BCRB) associated with channel estimation error. Simulation results are provided to exhibit the performance of the proposed scheme for single and multi carrier zero-padded and cyclic prefixed systems.
{"title":"Optimal Pilot Design for Data Dependent Superimposed Training based Channel Estimation in Single/Multi carrier Block Transmission Systems","authors":"Manjeer Majumder, A. Jagannatham","doi":"10.1109/NCC52529.2021.9530070","DOIUrl":"https://doi.org/10.1109/NCC52529.2021.9530070","url":null,"abstract":"This paper develops a novel data dependent superimposed training technique for channel estimation in generic block transmission (BT) systems comprising of single/multi-carrier (SC/MC) and zero-padded (ZP)/ cyclic prefix (CP) systems. The training sequence comprises of the summation of a known training sequence and a data-dependent sequence that is not known to the receiver. A unique aspect of the scheme is that the channel estimation is not affected by the use of a data-dependent sequence. The pilot design framework is conceived in order to minimize the Bayesian Cramér-Rao bound (BCRB) associated with channel estimation error. Simulation results are provided to exhibit the performance of the proposed scheme for single and multi carrier zero-padded and cyclic prefixed systems.","PeriodicalId":414087,"journal":{"name":"2021 National Conference on Communications (NCC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129460264","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 : 2021-07-27DOI: 10.1109/NCC52529.2021.9530053
Payal Patel, U. Satija
Recently, convolutional neural network (CNN) has played a crucial role in classifying epileptic seizures due to its capability of automatically learning the discriminatory features from the raw electroencephalogram (EEG) data. Moreover, most of the existing methods considered artifact-free EEG data for extracting features. In this paper, we analyze the impact of ocular artifacts on the performance of CNN in extracting reliable features from the EEG data for seizure classification. Furthermore, we also analyze the robustness of CNN in determining the accurate and reliable features not only from raw EEG data but also from spectral domain EEG data. The performance of the method is evaluated on the EEG signals taken from the Bonn's dataset with different types and levels of ocular artifacts. Performance evaluation results demonstrate that the classification accuracy of the method is degraded significantly under the presence of ocular artifacts. Furthermore, it is observed that the proposed CNN architecture is able to extract the discriminatory features from spectral EEG data more accurately as compared to the raw temporal EEG data.
{"title":"Performance Analysis of Convolutional Neural Network Based EEG Epileptic Seizure Classification in Presence of Ocular Artifacts","authors":"Payal Patel, U. Satija","doi":"10.1109/NCC52529.2021.9530053","DOIUrl":"https://doi.org/10.1109/NCC52529.2021.9530053","url":null,"abstract":"Recently, convolutional neural network (CNN) has played a crucial role in classifying epileptic seizures due to its capability of automatically learning the discriminatory features from the raw electroencephalogram (EEG) data. Moreover, most of the existing methods considered artifact-free EEG data for extracting features. In this paper, we analyze the impact of ocular artifacts on the performance of CNN in extracting reliable features from the EEG data for seizure classification. Furthermore, we also analyze the robustness of CNN in determining the accurate and reliable features not only from raw EEG data but also from spectral domain EEG data. The performance of the method is evaluated on the EEG signals taken from the Bonn's dataset with different types and levels of ocular artifacts. Performance evaluation results demonstrate that the classification accuracy of the method is degraded significantly under the presence of ocular artifacts. Furthermore, it is observed that the proposed CNN architecture is able to extract the discriminatory features from spectral EEG data more accurately as compared to the raw temporal EEG data.","PeriodicalId":414087,"journal":{"name":"2021 National Conference on Communications (NCC)","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125109882","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 : 2021-07-27DOI: 10.1109/NCC52529.2021.9530076
Navneet Nayan, D. Ghosh, P. M. Pradhan
In this paper, the movement epenthesis problem in continuous fingerspelling is addressed. Movement epenthesis caused due to unwanted but unavoidable hand movement in between two sign gestures in continuous signing is one of the major problems in automatic sign language recognition. A novel method based on calculating the 2-norm values of the magnitude matrices of optical flow has been proposed in this paper to detect the movement epenthesis containing video frames. We used Horn-Schunck method to compute the optical flow and estimate the speed of hands in the the continuous fingerspelling videos. The 2-norm values of the magnitude matrix of optical flow provides a discriminative feature to distinguish of movement epenthesis frames from sign frames and hence mean of the 2-norm values is used as the threshold value to detect the movement epenthesis frames in a gesture video. We tested our method on continuous fingerspelling videos of Indian sign language. Experimental results show that the performance of our proposed method is 100% accurate in detecting the movement epenthesis frames in continuous fingerspelling.
{"title":"An Optical Flow Based Approach to Detect Movement Epenthesis in Continuous Fingerspelling of Sign Language","authors":"Navneet Nayan, D. Ghosh, P. M. Pradhan","doi":"10.1109/NCC52529.2021.9530076","DOIUrl":"https://doi.org/10.1109/NCC52529.2021.9530076","url":null,"abstract":"In this paper, the movement epenthesis problem in continuous fingerspelling is addressed. Movement epenthesis caused due to unwanted but unavoidable hand movement in between two sign gestures in continuous signing is one of the major problems in automatic sign language recognition. A novel method based on calculating the 2-norm values of the magnitude matrices of optical flow has been proposed in this paper to detect the movement epenthesis containing video frames. We used Horn-Schunck method to compute the optical flow and estimate the speed of hands in the the continuous fingerspelling videos. The 2-norm values of the magnitude matrix of optical flow provides a discriminative feature to distinguish of movement epenthesis frames from sign frames and hence mean of the 2-norm values is used as the threshold value to detect the movement epenthesis frames in a gesture video. We tested our method on continuous fingerspelling videos of Indian sign language. Experimental results show that the performance of our proposed method is 100% accurate in detecting the movement epenthesis frames in continuous fingerspelling.","PeriodicalId":414087,"journal":{"name":"2021 National Conference on Communications (NCC)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115792939","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 : 2021-07-27DOI: 10.1109/NCC52529.2021.9530104
Iman Burman, Archita Hore, Ayan Chakraborty, Sharba Bandyopadhyay, S. Chakrabarti
A spiking neuronal network consumes very low power for computation contrary to conventional Von-Neumann architectures. A CMOS based circuit which includes several features of a spiking neuron closely, is presented in this paper. Features such as refractory period, spike height and width, resting potential, spiking threshold, spike frequency adaptation and inter spike interval (ISI) have been incorporated in the circuit. A small set of parameters, chosen carefully control these features in the circuit response. The spiking pattern of the proposed circuit has been matched with selected experimental data of real biological neurons from Allen Institute for Brain Science (AIBS) database.
{"title":"Implementation of a Spiking Neuron in CMOS","authors":"Iman Burman, Archita Hore, Ayan Chakraborty, Sharba Bandyopadhyay, S. Chakrabarti","doi":"10.1109/NCC52529.2021.9530104","DOIUrl":"https://doi.org/10.1109/NCC52529.2021.9530104","url":null,"abstract":"A spiking neuronal network consumes very low power for computation contrary to conventional Von-Neumann architectures. A CMOS based circuit which includes several features of a spiking neuron closely, is presented in this paper. Features such as refractory period, spike height and width, resting potential, spiking threshold, spike frequency adaptation and inter spike interval (ISI) have been incorporated in the circuit. A small set of parameters, chosen carefully control these features in the circuit response. The spiking pattern of the proposed circuit has been matched with selected experimental data of real biological neurons from Allen Institute for Brain Science (AIBS) database.","PeriodicalId":414087,"journal":{"name":"2021 National Conference on Communications (NCC)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121663454","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 : 2021-07-27DOI: 10.1109/NCC52529.2021.9530100
Soumen Biswas, Ranjay Hazra, S. Prasad, Arvind Sirvee
An image segmentation model using histogram-based image fitting (HF) energy is proposed to identify objects with poorly defined boundaries. The proposed energy model considers an improved fitting energy function based on normalized histogram and average intensities of objects inside as well as outside the contour curve. The fitting energy functions are computed before the curve evolution thereby reducing the complexity of intensity inhomogeneity images. Further, a new signed pressure force function is incorporated in the proposed energy model which can increase the efficiency of the curve evolution process at blur edges or at weak edge regions. The comparative analysis of the proposed energy model produces better segmentation results compared to the other state-of-the-art energy models namely the Li et. al. model, local binary fitting (LBF), and Chen-Vese (C-V) models. The proposed model is also robust to intensity inhomogeneity. In addition, the calculation of the Jaccard Index (JI) proves the robustness of the proposed energy model.
{"title":"A Level Set Model Driven by New Signed Pressure Force Function for Image Segmentation","authors":"Soumen Biswas, Ranjay Hazra, S. Prasad, Arvind Sirvee","doi":"10.1109/NCC52529.2021.9530100","DOIUrl":"https://doi.org/10.1109/NCC52529.2021.9530100","url":null,"abstract":"An image segmentation model using histogram-based image fitting (HF) energy is proposed to identify objects with poorly defined boundaries. The proposed energy model considers an improved fitting energy function based on normalized histogram and average intensities of objects inside as well as outside the contour curve. The fitting energy functions are computed before the curve evolution thereby reducing the complexity of intensity inhomogeneity images. Further, a new signed pressure force function is incorporated in the proposed energy model which can increase the efficiency of the curve evolution process at blur edges or at weak edge regions. The comparative analysis of the proposed energy model produces better segmentation results compared to the other state-of-the-art energy models namely the Li et. al. model, local binary fitting (LBF), and Chen-Vese (C-V) models. The proposed model is also robust to intensity inhomogeneity. In addition, the calculation of the Jaccard Index (JI) proves the robustness of the proposed energy model.","PeriodicalId":414087,"journal":{"name":"2021 National Conference on Communications (NCC)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133252857","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 : 2021-07-27DOI: 10.1109/NCC52529.2021.9530014
G. Kumar, Nishanth Chandra, P. Krishnamurthy
We observe optical sideband interference using an optical IQ modulator at the transmitter and a Mach-Zehnder modulator at the receiver. We measure 82% interference visibility in back-to-back configuration and 71% interference visibility over 25 km optical fiber channel. We also show the simulation of optical sideband interference using IQ modulator and Mach-Zehnder modulator. We measure 77% visibility by simulation in back-to-back connection of transmitter and receiver. We study the effect of the linewidth of the laser on the optical spectrum of the sideband. We derive expressions for sideband power as a function of the applied phase difference between transmitter and receiver in the presence of chromatic dispersion in the fiber.
{"title":"Optical sideband interference using optical IQ and Mach-Zehnder modulators","authors":"G. Kumar, Nishanth Chandra, P. Krishnamurthy","doi":"10.1109/NCC52529.2021.9530014","DOIUrl":"https://doi.org/10.1109/NCC52529.2021.9530014","url":null,"abstract":"We observe optical sideband interference using an optical IQ modulator at the transmitter and a Mach-Zehnder modulator at the receiver. We measure 82% interference visibility in back-to-back configuration and 71% interference visibility over 25 km optical fiber channel. We also show the simulation of optical sideband interference using IQ modulator and Mach-Zehnder modulator. We measure 77% visibility by simulation in back-to-back connection of transmitter and receiver. We study the effect of the linewidth of the laser on the optical spectrum of the sideband. We derive expressions for sideband power as a function of the applied phase difference between transmitter and receiver in the presence of chromatic dispersion in the fiber.","PeriodicalId":414087,"journal":{"name":"2021 National Conference on Communications (NCC)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125339745","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 : 2021-07-27DOI: 10.1109/NCC52529.2021.9530067
Arya Deo Mehta, H. Sharma
The recent studies suggest the feasibility of accessing crucial health parameters through contactless means with an RGB camera placed at a distance. As high-quality RGB cameras are getting more cost-effective due to the drastic evolution in imaging technology, the camera-based health monitoring is evoking a considerable interest among researchers. This development may provide a better alternative to the conventional contact-based methods, as it promises a convenient and contactless long term vital sign monitoring solution that doesn't restrict personal mobility. This paper introduces an effective approach towards monitoring heart rate (HR) from facial videos using an RGB camera in wild practical scenarios. The proposed approach introduces the face symmetry-based quality scoring, which is an essential step to ensure quality face detection and avoid false face detections in videos captured in a practical scenario. Further, steps such as feature points generation for optimum masking and variational mode decomposition (VMD) based filtering assist in obtaining a signal dominated mainly by the HR component. Two publicly available datasets comprising the video signals at different frame rates collected from the subjects with diverse ethnicities and skin tones are used to access the performance of the technique. The proposed approach achieved a mean absolute error of 6.58 beats per minute (BPM) on the COHFACE (Good illumination) dataset class, 9.11 BPM on the COHFACE (Bad illumination) dataset class and 6.37 BPM on the DEAP dataset class outperforming some of the state-of-art methods affirming its effectiveness in the estimation of HR in more realistic scenarios.
{"title":"Heart Rate Estimation from RGB Facial Videos Using Robust Face Demarcation and VMD","authors":"Arya Deo Mehta, H. Sharma","doi":"10.1109/NCC52529.2021.9530067","DOIUrl":"https://doi.org/10.1109/NCC52529.2021.9530067","url":null,"abstract":"The recent studies suggest the feasibility of accessing crucial health parameters through contactless means with an RGB camera placed at a distance. As high-quality RGB cameras are getting more cost-effective due to the drastic evolution in imaging technology, the camera-based health monitoring is evoking a considerable interest among researchers. This development may provide a better alternative to the conventional contact-based methods, as it promises a convenient and contactless long term vital sign monitoring solution that doesn't restrict personal mobility. This paper introduces an effective approach towards monitoring heart rate (HR) from facial videos using an RGB camera in wild practical scenarios. The proposed approach introduces the face symmetry-based quality scoring, which is an essential step to ensure quality face detection and avoid false face detections in videos captured in a practical scenario. Further, steps such as feature points generation for optimum masking and variational mode decomposition (VMD) based filtering assist in obtaining a signal dominated mainly by the HR component. Two publicly available datasets comprising the video signals at different frame rates collected from the subjects with diverse ethnicities and skin tones are used to access the performance of the technique. The proposed approach achieved a mean absolute error of 6.58 beats per minute (BPM) on the COHFACE (Good illumination) dataset class, 9.11 BPM on the COHFACE (Bad illumination) dataset class and 6.37 BPM on the DEAP dataset class outperforming some of the state-of-art methods affirming its effectiveness in the estimation of HR in more realistic scenarios.","PeriodicalId":414087,"journal":{"name":"2021 National Conference on Communications (NCC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125376436","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 : 2021-07-27DOI: 10.1109/NCC52529.2021.9530074
Jaya Mishra, Girish Chandra Tripathi, M. Rawat
Frequency hopping (FH) is one of the best spread spectrum techniques for interference avoidance. Nonlinearity of PA is still a hindrance in using high efficiency modulation like QAM with FH. As dwell time is short, applying digital predistortion (DPD) to mitigate nonlinearity becomes critical. Memory Polynomial Model (MPM) based indirect learning architecture offers feasible solutions with reasonable resource utilization for FPGA implementation. Hard coded DPD in FPGA is the best possibility for FH system. It takes less time in the implementation and application of DPD. If a single DPD for the whole frequency band 105MHz (2.395GHz to 2.5GHz) is used, it will consume less FPGA resource but will not provide good result. Hard coded DPD at each hopping frequency is not possible because of limited resource of FPGA. So, a solution has been worked out to use six DPD, each DPD for 3 to 4 hopping frequency. Thus, this paper provides a real-time solution of DPD implementation for the FH system in the above band. NMSE has been used to judge the efficacy of DPD. The resource utilized and time taken has been studied in this paper.
{"title":"Digital Predistortion Resource Optimization for Frequency Hopping Transceiver System","authors":"Jaya Mishra, Girish Chandra Tripathi, M. Rawat","doi":"10.1109/NCC52529.2021.9530074","DOIUrl":"https://doi.org/10.1109/NCC52529.2021.9530074","url":null,"abstract":"Frequency hopping (FH) is one of the best spread spectrum techniques for interference avoidance. Nonlinearity of PA is still a hindrance in using high efficiency modulation like QAM with FH. As dwell time is short, applying digital predistortion (DPD) to mitigate nonlinearity becomes critical. Memory Polynomial Model (MPM) based indirect learning architecture offers feasible solutions with reasonable resource utilization for FPGA implementation. Hard coded DPD in FPGA is the best possibility for FH system. It takes less time in the implementation and application of DPD. If a single DPD for the whole frequency band 105MHz (2.395GHz to 2.5GHz) is used, it will consume less FPGA resource but will not provide good result. Hard coded DPD at each hopping frequency is not possible because of limited resource of FPGA. So, a solution has been worked out to use six DPD, each DPD for 3 to 4 hopping frequency. Thus, this paper provides a real-time solution of DPD implementation for the FH system in the above band. NMSE has been used to judge the efficacy of DPD. The resource utilized and time taken has been studied in this paper.","PeriodicalId":414087,"journal":{"name":"2021 National Conference on Communications (NCC)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123170683","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 : 2021-07-27DOI: 10.1109/NCC52529.2021.9530152
Jaswanthi Mandalapu, K. Jagannathan
We consider a photonic communication system wherein the photon detector suffers a random ‘dead time’ following each successful photon detection. If subsequent photon arrivals occur during the dead time, the information contained in the photons is assumed to be erased. We refer to such channels as photonic erasure channels and derive fundamental limits on the rate at which classical information can be transmitted on such channels. We assume photon arrivals according to a Poisson process, and consider two classes of detectors - paralyzable and nonparalyzable. We derive explicit expressions for the capacity of photonic erasure channels, for any general distribution of the dead times of the detector. For a photonic erasure channel with a nonparalyzable detector, we show that the capacity depends only on the expected dead time. On the other hand, with a paralyzable detector, the channel capacity depends on the dead time distribution through its Laplace transform.
{"title":"The Capacity of Photonic Erasure Channels with Detector Dead Times","authors":"Jaswanthi Mandalapu, K. Jagannathan","doi":"10.1109/NCC52529.2021.9530152","DOIUrl":"https://doi.org/10.1109/NCC52529.2021.9530152","url":null,"abstract":"We consider a photonic communication system wherein the photon detector suffers a random ‘dead time’ following each successful photon detection. If subsequent photon arrivals occur during the dead time, the information contained in the photons is assumed to be erased. We refer to such channels as photonic erasure channels and derive fundamental limits on the rate at which classical information can be transmitted on such channels. We assume photon arrivals according to a Poisson process, and consider two classes of detectors - paralyzable and nonparalyzable. We derive explicit expressions for the capacity of photonic erasure channels, for any general distribution of the dead times of the detector. For a photonic erasure channel with a nonparalyzable detector, we show that the capacity depends only on the expected dead time. On the other hand, with a paralyzable detector, the channel capacity depends on the dead time distribution through its Laplace transform.","PeriodicalId":414087,"journal":{"name":"2021 National Conference on Communications (NCC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114316276","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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