2019 National Conference on Communications (NCC)最新文献_第5页

Generalized Selection Combining for Dynamic SSK-BPSK Systems 动态SSK-BPSK系统的广义选择组合

2019 National Conference on Communications (NCC) Pub Date : 2019-02-01 DOI: 10.1109/NCC.2019.8732198

A. Ananth, P. Maheswaran, M. D. Selvaraj

{"title":"Generalized Selection Combining for Dynamic SSK-BPSK Systems","authors":"A. Ananth, P. Maheswaran, M. D. Selvaraj","doi":"10.1109/NCC.2019.8732198","DOIUrl":"https://doi.org/10.1109/NCC.2019.8732198","url":null,"abstract":"Space shift keying (SSK) is a multiple-input multiple-output (MIMO) technique in which the transmitter can be designed with a single radio frequency (RF) chain. By adaptively selecting the modulation in a two antenna transmitter as either SSK or binary phase shift keying (BPSK), dynamic SSK-BPSK (DSB) obtains second order transmit diversity. In this work, we conceive DSB with generalized selection combining (DSB-GSC) to reduce the receiver circuit complexity. Specifically, we propose the metrics of modulation selection and receiver antenna selection for DSB where the receiver is equipped with lesser number of RF chains than its antennas. The performance of DSB-GSC is analyzed with exact bit error rate (BER) expression which is validated using simulation results. From the results, we infer that DSB-GSC provides diversity order equal to twice the number of receiver antennas irrespective of the number of RF chains used at the receiver. We further infer that there is only small SNR gains attained for increasing receiver RF chains. Thus the receiver complexity of the system can be considerably reduced with a small performance loss compared to that of full complex receiver.","PeriodicalId":6870,"journal":{"name":"2019 National Conference on Communications (NCC)","volume":"49 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85662984","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

Emotion Recognition from Varying Length Patterns of Speech using CNN-based Segment-Level Pyramid Match Kernel based SVMs 基于cnn的分段级金字塔匹配核支持向量机对不同长度语音模式的情感识别

2019 National Conference on Communications (NCC) Pub Date : 2019-02-01 DOI: 10.1109/NCC.2019.8732191

Shikha Gupta, Kishalaya De, Dileep Aroor Dinesh, Veena Thenkanidiyoor

{"title":"Emotion Recognition from Varying Length Patterns of Speech using CNN-based Segment-Level Pyramid Match Kernel based SVMs","authors":"Shikha Gupta, Kishalaya De, Dileep Aroor Dinesh, Veena Thenkanidiyoor","doi":"10.1109/NCC.2019.8732191","DOIUrl":"https://doi.org/10.1109/NCC.2019.8732191","url":null,"abstract":"Convolutional Neural Networks (CNNs) and its variants have achieved impressive performance when used for different speech processing tasks like spoken language identification, speaker verification, speech emotion recognition, etc. Conventionally, CNNs for speech applications consider input features from fixed duration speech segments as input. In this work, we attempt to consider features from complete speech signal as input to CNN. We propose to use spatial pyramid pooling (SPP) layer in CNN architecture to remove the fixed length constraint and to consider features from varying length speech signals as input to CNN for an end to end training. Proposed architecture also results in varying size set of feature maps from convolution layer. Further, we propose novel CNN-based segment-level pyramid match kernel (CNN-SLPMK) as dynamic kernel between a pair of varying size set of feature maps for the classification framework using support vector machines (SVMs) based classifier. We demonstrate that our proposed approach achieves comparable results with state-of-the-art techniques for speech emotion recognition task.","PeriodicalId":6870,"journal":{"name":"2019 National Conference on Communications (NCC)","volume":"1 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85380726","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: 3

Improved Tail Bounds for Missing Mass and Confidence Intervals for Good-Turing Estimator 缺失质量的改进尾界和Good-Turing估计的置信区间

2019 National Conference on Communications (NCC) Pub Date : 2019-02-01 DOI: 10.1109/NCC.2019.8732184

Prafulla Chandra, Aditya Pradeep, A. Thangaraj

引用次数: 6

Codebook based Precoding for Multiuser MIMO Broadcast Systems: An MM Approach 基于码本的多用户MIMO广播系统预编码:一种MM方法

2019 National Conference on Communications (NCC) Pub Date : 2019-02-01 DOI: 10.1109/NCC.2019.8732179

Sai Subramanyam Thoota, P. Babu, C. Murthy

{"title":"Codebook based Precoding for Multiuser MIMO Broadcast Systems: An MM Approach","authors":"Sai Subramanyam Thoota, P. Babu, C. Murthy","doi":"10.1109/NCC.2019.8732179","DOIUrl":"https://doi.org/10.1109/NCC.2019.8732179","url":null,"abstract":"The goal of this paper is to propose a novel, principled approach to solve non-convex optimization problems that arise in multiuser (MU) multiple input multiple output (MIMO) cellular wireless communication systems. We explore a minorization-maximization (MM) optimization approach, which is guaranteed to converge to a stationary point starting from any initialization. One of the important problems in wireless communications is sum rate maximization in MU MIMO broadcast systems, in which multiple data streams are simultaneously transmitted to all users. In this paper, we adopt a codebook based precoding method, where each data stream is beamformed using a vector selected from a predetermined codebook. Our objective is to determine the selection of beamforming vectors and power allocation to each beam to maximize the achievable sum rate. We reformulate the problem to facilitate the application of MM procedure in a nested fashion. The outcome is a novel, iterative, and computationally efficient solution, which we call the inverse-MM (IMM) algorithm. We illustrate the superior performance of our algorithm compared to existing approaches through Monte Carlo simulations. The advantages of computational efficiency, simple implementation, and structured approach makes the MM framework a good candidate for solving non convex optimization problems in wireless communications.","PeriodicalId":6870,"journal":{"name":"2019 National Conference on Communications (NCC)","volume":"46 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91056021","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

Improved Data Fusion for Multi-Sensor Tracking using a Reinforced Viterbi Algorithm 基于增强Viterbi算法的多传感器跟踪改进数据融合

2019 National Conference on Communications (NCC) Pub Date : 2019-02-01 DOI: 10.1109/NCC.2019.8732217

Rajarshi Biswas, Akash S. Doshi, Akankshya Bhatta, S. R. Pillai

引用次数: 0

On the Role of Linear, Mel and Inverse-Mel Filterbank in the Context of Automatic Speech Recognition 线性、梅尔和反梅尔滤波器组在自动语音识别中的作用

2019 National Conference on Communications (NCC) Pub Date : 2019-02-01 DOI: 10.1109/NCC.2019.8732232

H. Kathania, S. Shahnawazuddin, Waquar Ahmad, Nagaraj Adiga

{"title":"On the Role of Linear, Mel and Inverse-Mel Filterbank in the Context of Automatic Speech Recognition","authors":"H. Kathania, S. Shahnawazuddin, Waquar Ahmad, Nagaraj Adiga","doi":"10.1109/NCC.2019.8732232","DOIUrl":"https://doi.org/10.1109/NCC.2019.8732232","url":null,"abstract":"In the context of automatic speech recognition (ASR), the power spectrum is generally warped to the Mel-scale during front-end speech parameterization. This is motivated by the fact that, human perception of sound is nonlinear. The Mel-filterbank provide better resolution for low-frequency contents while a greater degree of averaging happens in the high-frequency range. The work presented in this paper aims at studying the role of linear, Mel and inverse-Mel filterbanks in the context of speech recognition. It is well known that, when speech data is from high-pitched speakers like children, there is a significant amount of relevant information in the high-frequency region. Hence, down-sampling the information in that range through Mel-filterbank reduces the recognition performance. On the other hand, employing inverse-Mel or linear-filterbanks are expected to be more effective in such cases. The same has been experimentally validated in this work. To do so, an ASR system is developed on adults' speech and tested using data from adult as well as child speakers. Significantly improved recognition rates are noted for children's as well adult females' speech when linear or inverse-Mel filterbank is used. The use of linear filters results in a relative improvement of 21% over the baseline.","PeriodicalId":6870,"journal":{"name":"2019 National Conference on Communications (NCC)","volume":"24 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86382050","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: 3

Design of Multiband Negative Permittivity Metamaterial Based on Interdigitated and Meander Line Resonator 基于交叉曲线谐振腔的多带负介电常数超材料设计

2019 National Conference on Communications (NCC) Pub Date : 2019-02-01 DOI: 10.1109/NCC.2019.8732247

Rohan G. Deshmukh, D. Marathe, K. Kulat

引用次数: 2

Sparse Bayesian Learning (SBL)-Based Frequency-Selective Channel Estimation for Millimeter Wave Hybrid MIMO Systems

2019 National Conference on Communications (NCC) Pub Date : 2019-02-01 DOI: 10.1109/NCC.2019.8732197

Suraj Srivastava, Ch Suraj Kumar Patro, A. Jagannatham, G. Sharma

{"title":"Sparse Bayesian Learning (SBL)-Based Frequency-Selective Channel Estimation for Millimeter Wave Hybrid MIMO Systems","authors":"Suraj Srivastava, Ch Suraj Kumar Patro, A. Jagannatham, G. Sharma","doi":"10.1109/NCC.2019.8732197","DOIUrl":"https://doi.org/10.1109/NCC.2019.8732197","url":null,"abstract":"This work develops a novel sparse Bayesian learning (SBL)-based channel estimation technique for frequency-selective millimeter wave (mmWave) multiple-input multiple-output (MIMO) systems. Towards this end, the concatenated frequency-selective MIMO channel matrix is represented in terms of the beamspace channel vector employing suitable transmit and receive array response dictionary matrices. Subsequently, a multiple measurement vector (MMV) model is developed for estimation of the sparse beamspace channel vector considering the block transmission of zero-padded training frames. The unique aspects of the proposed scheme are that it exploits the group-sparsity inherent in the equivalent beamspace channel vector of the frequency-selective mmWave MIMO channel and also considers the effect of correlated noise in the equivalent system model due to RF-combining. This feature, coupled with the improved ability of SBL for sparse signal recovery, leads to a significantly enhanced performance of the proposed scheme in comparison to the orthogonal matching pursuit (OMP) technique proposed recently. Bayesian Cramér-Rao bounds (BCRBs) are also derived to characterize the estimation performance. Simulation results are presented to demonstrate the improved performance of the proposed SBL-based channel estimation technique in comparison to the existing scheme and also a performance close to the various benchmarks.","PeriodicalId":6870,"journal":{"name":"2019 National Conference on Communications (NCC)","volume":"44 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85401539","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: 13

Performance Analysis and Optimization of Interference limited Multi-Antenna BRN 限制干扰多天线BRN的性能分析与优化

2019 National Conference on Communications (NCC) Pub Date : 2019-02-01 DOI: 10.1109/NCC.2019.8732267

Imtiyaz Khan, Krishna Kanth Dhulipudi, Poonam Singh

引用次数: 0

Gamma Enhanced Binarization - An Adaptive Nonlinear Enhancement of Degraded Word Images for Improved Recognition of Split Characters 伽玛增强二值化-一种自适应非线性增强的退化字图像，用于改进分割字符的识别

2019 National Conference on Communications (NCC) Pub Date : 2019-02-01 DOI: 10.1109/NCC.2019.8732254

H. Kumar, A. Ramakrishnan

{"title":"Gamma Enhanced Binarization - An Adaptive Nonlinear Enhancement of Degraded Word Images for Improved Recognition of Split Characters","authors":"H. Kumar, A. Ramakrishnan","doi":"10.1109/NCC.2019.8732254","DOIUrl":"https://doi.org/10.1109/NCC.2019.8732254","url":null,"abstract":"Recognition performance of any OCR suffers because of the merged and split characters that occur in the scanned images of degraded printed documents. We propose an elegant method of non-linearly enhancing such degraded, gray-scale word images. This connects the broken strokes of the characters, so that binarization of the processed word images gives components with better connectivity for most characters or recognizable units. From an initial value of one, the value of gamma, the parameter determining the enhancement, is decreased in powers of 2 and the right value of gamma is chosen based on the recognition score of our character classifier. We have created a benchmark dataset of 1685 degraded word images obtained from scanned pages of several old Kannada books. The word images have been recognized before and after the proposed nonlinear enhancement. There is an absolute improvement of 14.8% in the Unicode level recognition accuracy of our SVM-based character classifier on the above dataset due to the proposed enhancement of the gray-scale word images. Even on the Google's Tesseract OCR for Kannada, our gamma enhanced binarization results in an improvement of 5.6% in the Unicode level accuracy.","PeriodicalId":6870,"journal":{"name":"2019 National Conference on Communications (NCC)","volume":"50 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84806843","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: 6