2020 International Conference on Signal Processing and Communications (SPCOM)最新文献_第3页

SBL-Based Hybrid Precoder/ Combiner Design for Power and Spectrally Efficient Millimeter Wave MIMO Systems 基于sbl的功率和频谱高效毫米波MIMO系统混合预编码器/组合器设计

2020 International Conference on Signal Processing and Communications (SPCOM) Pub Date : 2020-07-01 DOI: 10.1109/SPCOM50965.2020.9179621

Suraj Srivastava, Amrita Mishra, A. Jagannatham, G. Ascheid

{"title":"SBL-Based Hybrid Precoder/ Combiner Design for Power and Spectrally Efficient Millimeter Wave MIMO Systems","authors":"Suraj Srivastava, Amrita Mishra, A. Jagannatham, G. Ascheid","doi":"10.1109/SPCOM50965.2020.9179621","DOIUrl":"https://doi.org/10.1109/SPCOM50965.2020.9179621","url":null,"abstract":"This work proposes a novel sparse Bayesian learning (SBL)-based hybrid precoder/ combiner design scheme for millimeter wave (mmWave) MIMO systems. Towards this end, a multiple measurement vector (MMV) based sparse signal recovery problem is developed that maximizes the mutual information by approximating the hybrid precoder to the ideal digital precoder. A unique aspect of the proposed SBL-based scheme is that the resulting hyperparameter estimates can be used to activate the minimum number of RF chains required to approximate the ideal digital precoder/ combiner, thus enabling one to leverage the time-varying multipath profile of the underlying mmWave MIMO channel. This feature coupled with the improved ability of SBL for sparse signal recovery leads to a significantly enhanced power and spectral efficiency of the proposed scheme in comparison to the conventional schemes that activate a fixed number of RF chains and data streams, irrespective of the multipath profile of the mmWave MIMO channel. Simulation results demonstrate the improved efficiency of the proposed scheme in comparison to the existing schemes and also the resulting reduction in the average number of RF chains employed.","PeriodicalId":208527,"journal":{"name":"2020 International Conference on Signal Processing and Communications (SPCOM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125808613","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: 8

Coexistence of LTE-Unlicensed and WiFi: optimization and Game-Theoretic Frameworks lte - unlicensing与WiFi共存:优化与博弈论框架

2020 International Conference on Signal Processing and Communications (SPCOM) Pub Date : 2020-07-01 DOI: 10.1109/SPCOM50965.2020.9179532

Chaitanya Amballa, K. P. Naveen

引用次数: 2

Gaussian Broadcast Channel with State Estimation 状态估计高斯广播信道

2020 International Conference on Signal Processing and Communications (SPCOM) Pub Date : 2020-07-01 DOI: 10.1109/SPCOM50965.2020.9179635

Viswanathan Ramachandran

引用次数: 0

Equalizer-Free Clock Recovery for PAM-4 Optical Interconnects 用于PAM-4光互连的无均衡器时钟恢复

2020 International Conference on Signal Processing and Communications (SPCOM) Pub Date : 2020-07-01 DOI: 10.1109/SPCOM50965.2020.9179629

Kaushal Patel, Rakesh Ashok, Shalabh Gupta

引用次数: 0

Dendrogram based Clustering and Separation of Individual and Simultaneously Active Incipient Discharges in Transformer Insulation 基于树形图的变压器绝缘初始放电的聚类与分离

2020 International Conference on Signal Processing and Communications (SPCOM) Pub Date : 2020-07-01 DOI: 10.1109/SPCOM50965.2020.9179572

Niyas K. Haneefa, B. M. A. Desai, R. Sarathi, Manivasakan Rathinam

{"title":"Dendrogram based Clustering and Separation of Individual and Simultaneously Active Incipient Discharges in Transformer Insulation","authors":"Niyas K. Haneefa, B. M. A. Desai, R. Sarathi, Manivasakan Rathinam","doi":"10.1109/SPCOM50965.2020.9179572","DOIUrl":"https://doi.org/10.1109/SPCOM50965.2020.9179572","url":null,"abstract":"Partial discharges in transformer insulation are of major concern to utilities which cause the catastrophic failure of insulation. One of the major challenges is the identification of discharges from multiple sources when it occurs concurrently. Hence it is imperative to devise methods for identifying and separating those signals for corrective measures. In this study, an unsupervised learning approach is proposed for clustering of individual partial discharge signals and then using that information for separating the multi-source signals. Our clustering approach works by constructing a dendrogram by measuring the cosine similarity between the feature vectors and then computing a threshold, to group the individual source signals into different clusters. The feature vectors include the relative energies from the wavelet packet decomposed tree and the Higuchi fractal dimension of the wavelet coefficients at the terminal nodes. The generated clusters are trained using a classifier model to separate the individual and multi-source signals. The proposed approach is a simple and robust technique for individual cluster groupings and individual to multiclass separations and could be used for multiclass cluster groupings.","PeriodicalId":208527,"journal":{"name":"2020 International Conference on Signal Processing and Communications (SPCOM)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127454840","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

VLSI architectures for Delay Multiply and Sum Beamforming in Ultrasound Medical Imaging 超声医学成像中延迟相乘和和波束形成的VLSI架构

2020 International Conference on Signal Processing and Communications (SPCOM) Pub Date : 2020-07-01 DOI: 10.1109/SPCOM50965.2020.9179510

Gayathri Malamal, Mahesh Raveendranatha Panicker

{"title":"VLSI architectures for Delay Multiply and Sum Beamforming in Ultrasound Medical Imaging","authors":"Gayathri Malamal, Mahesh Raveendranatha Panicker","doi":"10.1109/SPCOM50965.2020.9179510","DOIUrl":"https://doi.org/10.1109/SPCOM50965.2020.9179510","url":null,"abstract":"Ultrasound medical imaging systems typically follow standard delay and sum (DAS) beamforming at the reception for image reconstruction. In DAS, the echo signals that are returned to the transducer are aligned in time and summed to form the beamformed signal. To improve the image quality and the signal to noise ratio of DAS, a non-linear beamforming named delay multiply and sum (DMAS) has been proposed in the literature, where, the signals arriving at the transducer are aligned in time and are pairwise multiplied in all possible combinations before summation. This provides better coherence, a correlation-based data-driven apodization, and consequently result in better contrast and resolution. However, the computational complexity of DMAS is higher than DAS thus restricting its real-time implementation. This paper presents two novel VLSI architectures for the implementation of DMAS, whose complexity is independent of the number of transducer elements. The proposed architectures are implemented on xc7z010c1g400-1 FPGA and the results clearly show the channel independency of the proposed architectures.","PeriodicalId":208527,"journal":{"name":"2020 International Conference on Signal Processing and Communications (SPCOM)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127483367","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

Sparse Plane-wave Decomposition for Upscaling Ambisonic Signals 放大双声信号的稀疏平面波分解

2020 International Conference on Signal Processing and Communications (SPCOM) Pub Date : 2020-07-01 DOI: 10.1109/SPCOM50965.2020.9179569

Gyanajyoti Routray, R. Hegde

引用次数: 1

Speech task based automatic classification of ALS and Parkinson’s Disease and their severity using log Mel spectrograms 基于语音任务的ALS和帕金森病及其严重程度的对数Mel谱图自动分类

2020 International Conference on Signal Processing and Communications (SPCOM) Pub Date : 2020-07-01 DOI: 10.1109/SPCOM50965.2020.9179503

BN Suhas, Jhansi Mallela, Aravind Illa, B. Yamini, A. Nalini, R. Yadav, D. Gope, P. Ghosh

{"title":"Speech task based automatic classification of ALS and Parkinson’s Disease and their severity using log Mel spectrograms","authors":"BN Suhas, Jhansi Mallela, Aravind Illa, B. Yamini, A. Nalini, R. Yadav, D. Gope, P. Ghosh","doi":"10.1109/SPCOM50965.2020.9179503","DOIUrl":"https://doi.org/10.1109/SPCOM50965.2020.9179503","url":null,"abstract":"We consider the task of speech based classification of patients with amyotrophic lateral sclerosis (ALS), Parkinson’s disease (PD) and healthy controls (HC). Recent work in convolutional neural networks (CNN) to solve image classification problems raises the possibility of utilizing spectral representation of speech for detection of neurological diseases. In this paper, a spectrogram based approach is used. Feeding overlapping windows to the CNN makes sure that the temporal aspects are considered by using short signal segments or wide analysis filters. A three class (ALS, PD or HC) dysarthria classification is performed. In addition, we perform two severity classification experiments for ALS (5 class) and PD (3 class) respectively. Experiments are conducted on both baseline MFCC data [1] and log Mel spectrograms. Classification results show that for several audio lengths, models trained on log Mel spectrograms consistently outperform those of MFCC’s. The ability of the network to accurately classify different classes is evaluated via the area under receiver operating characteristic curve [2],[3]. The findings from this study could aid in better detection and monitoring of ALS and PD diseases.","PeriodicalId":208527,"journal":{"name":"2020 International Conference on Signal Processing and Communications (SPCOM)","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134460857","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: 19

Improving Automatic Speech Recognition by Classifying Adult and Child Speakers into Separate Groups using Speech Rate Rhythmicity Parameter 基于语速韵律参数的成人和儿童语音自动识别方法研究

2020 International Conference on Signal Processing and Communications (SPCOM) Pub Date : 2020-07-01 DOI: 10.1109/SPCOM50965.2020.9179497

S. Shahnawazuddin, Tarun Sai Bandarupalli, R. Chakravarthy

{"title":"Improving Automatic Speech Recognition by Classifying Adult and Child Speakers into Separate Groups using Speech Rate Rhythmicity Parameter","authors":"S. Shahnawazuddin, Tarun Sai Bandarupalli, R. Chakravarthy","doi":"10.1109/SPCOM50965.2020.9179497","DOIUrl":"https://doi.org/10.1109/SPCOM50965.2020.9179497","url":null,"abstract":"When children’s speech is transcribed using acoustic models trained on adults’ data, a severely degraded recognition performance is obtained. Similar degradations are noted on recognizing adults’ speech using an automatic speech recognition (ASR) system trained on children’s speech. This problem can be overcome by using two separate ASR systems for the two groups of speakers. But this approach requires an effective technique to detect whether the given data is from adult or child speaker. In this paper, we present a very simple and novel technique to do the same. The proposed approach is based on speechrate rhythmicity parameter (SRRP). Since the speaking-rates for adults and children differ significantly, the SRRP values are also very different for the two groups of speakers. Hence, by computing the SRRP value for a given speech utterance, it can be easily determined whether it is from adult or child speaker. The corresponding ASR systems can then be used to achieve improved recognition performance. Alternatively, existing techniques for improving children’s speech recognition on adult data trained systems can be directly applied once it is known that the data is from a child speaker. Both these aspects have been experimentally validated in this work.","PeriodicalId":208527,"journal":{"name":"2020 International Conference on Signal Processing and Communications (SPCOM)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124050731","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

Performance Analysis of DF Relaying Assisted Underwater Visible Light Communication System DF中继辅助水下可见光通信系统性能分析

2020 International Conference on Signal Processing and Communications (SPCOM) Pub Date : 2020-07-01 DOI: 10.1109/SPCOM50965.2020.9179631

Monika Jain, N. Sharma, Akash Gupta, D. Rawal, P. Garg

{"title":"Performance Analysis of DF Relaying Assisted Underwater Visible Light Communication System","authors":"Monika Jain, N. Sharma, Akash Gupta, D. Rawal, P. Garg","doi":"10.1109/SPCOM50965.2020.9179631","DOIUrl":"https://doi.org/10.1109/SPCOM50965.2020.9179631","url":null,"abstract":"Underwater optical wireless communication plays an important role in the oceanography research, offshore exploration, climate monitoring, tactical surveillance and has attracted interest of military, industry, scientific and research community. In this paper, mixed satellite-underwater visible light communication (UWVLC) decode and forward (DF) cooperative system is proposed to help establish the connectivity between underwater scenario with the terrestrial regions via satellite for both oceanic monitoring as well as communication. The link between satellite and floating vessel (FV) is modeled by Shadowed-Rician fading channel and the UWVLC link is characterized by the mixture Exponential-Generalized Gamma (EGG) distribution. In particular, for the dual-hop satellite-UWVLC system, we derive the exact closed-form expressions for the average bit error rate (BER) in terms of a generalized Fox-H function. Furthermore, performance of the system is analyzed for various parameters such as air bubble levels, temperature gradient and saline level of water to validate the feasibility of the proposed system model.","PeriodicalId":208527,"journal":{"name":"2020 International Conference on Signal Processing and Communications (SPCOM)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127738865","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: 2