Pub Date : 2012-08-31DOI: 10.1109/ICASSP.2012.6288601
Yichao Huang, B. Rao
Spatial and multiuser diversity are two types of diversity techniques for delivering reliable high-date-rate services. Spectral diversity comes from opportunistic scheduling in the frequency domain enabled by the OFDMA technique, and is influenced by partial feedback design. By employing the best-M partial feedback strategy, we provide a unified view of spatial, spectral, and multiuser diversity through asymptotic (in users) analysis. We examine the tail behavior of the distribution of the received channel quality information (CQI) at the scheduler to prove the type of convergence as well as to derive the asymptotic approximations for the average spectral efficiency under partial feedback. We investigate the application of our analysis to different spatial diversity schemes. Our derived results can be used to quickly determine the minimum required partial feedback in a general multiuser MIMO-OFDMA system.
{"title":"Asymptotic analysis of a partial feedback OFDMA system employing spatial, spectral, and multiuser diversity","authors":"Yichao Huang, B. Rao","doi":"10.1109/ICASSP.2012.6288601","DOIUrl":"https://doi.org/10.1109/ICASSP.2012.6288601","url":null,"abstract":"Spatial and multiuser diversity are two types of diversity techniques for delivering reliable high-date-rate services. Spectral diversity comes from opportunistic scheduling in the frequency domain enabled by the OFDMA technique, and is influenced by partial feedback design. By employing the best-M partial feedback strategy, we provide a unified view of spatial, spectral, and multiuser diversity through asymptotic (in users) analysis. We examine the tail behavior of the distribution of the received channel quality information (CQI) at the scheduler to prove the type of convergence as well as to derive the asymptotic approximations for the average spectral efficiency under partial feedback. We investigate the application of our analysis to different spatial diversity schemes. Our derived results can be used to quickly determine the minimum required partial feedback in a general multiuser MIMO-OFDMA system.","PeriodicalId":6443,"journal":{"name":"2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","volume":"131 1","pages":"3221-3224"},"PeriodicalIF":0.0,"publicationDate":"2012-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76224423","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 : 2012-08-31DOI: 10.1109/ICASSP.2012.6289150
Dongbo Min, Jiangbo Lu, V. Nguyen, M. Do
This paper presents a novel approach for improving the quality of depth video. Given a high-quality color image and its corresponding low-quality depth image, we handle various artifacts which may exist on the depth video by applying a weighted mode filtering method based on a joint histogram. When the histogram is generated, the weight based on color similarity between reference and neighboring pixels on the color image is computed and then used for counting each bin on the joint histogram of the depth map. A final solution is determined by seeking a global mode on the histogram. Experimental results show that the proposed method has outstanding performance and is very efficient in various applications such as depth video enhancement and compression.
{"title":"Weighted mode filtering and its applications to depth video enhancement and coding","authors":"Dongbo Min, Jiangbo Lu, V. Nguyen, M. Do","doi":"10.1109/ICASSP.2012.6289150","DOIUrl":"https://doi.org/10.1109/ICASSP.2012.6289150","url":null,"abstract":"This paper presents a novel approach for improving the quality of depth video. Given a high-quality color image and its corresponding low-quality depth image, we handle various artifacts which may exist on the depth video by applying a weighted mode filtering method based on a joint histogram. When the histogram is generated, the weight based on color similarity between reference and neighboring pixels on the color image is computed and then used for counting each bin on the joint histogram of the depth map. A final solution is determined by seeking a global mode on the histogram. Experimental results show that the proposed method has outstanding performance and is very efficient in various applications such as depth video enhancement and compression.","PeriodicalId":6443,"journal":{"name":"2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","volume":"60 1","pages":"5433-5436"},"PeriodicalIF":0.0,"publicationDate":"2012-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91279431","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 : 2012-08-31DOI: 10.1109/ICASSP.2012.6288948
Raul Fernandez, Steve Minnis, B. Ramabhadran
Regression of continuous-valued variables as a function of both categorical and continuous predictors arises in some areas of speech processing, such as when predicting prosodic targets in a text-to-speech system. In this work we investigate the use of Continuous Conditional Random Fields (CCRF) to conditionally predict F0 targets from a series of s symbolic and numerical predictive features derived from text. We derive the training equations for the model using a Least-Squares-Error criterion within a supervised framework, and evaluate the proposed system using this objective criterion against other baseline models that can handle mixed inputs, such as regression trees and ensemble of regression trees.
{"title":"Prediction of F0 contours from symbolic and numerical variables using continuous conditional random fields","authors":"Raul Fernandez, Steve Minnis, B. Ramabhadran","doi":"10.1109/ICASSP.2012.6288948","DOIUrl":"https://doi.org/10.1109/ICASSP.2012.6288948","url":null,"abstract":"Regression of continuous-valued variables as a function of both categorical and continuous predictors arises in some areas of speech processing, such as when predicting prosodic targets in a text-to-speech system. In this work we investigate the use of Continuous Conditional Random Fields (CCRF) to conditionally predict F0 targets from a series of s symbolic and numerical predictive features derived from text. We derive the training equations for the model using a Least-Squares-Error criterion within a supervised framework, and evaluate the proposed system using this objective criterion against other baseline models that can handle mixed inputs, such as regression trees and ensemble of regression trees.","PeriodicalId":6443,"journal":{"name":"2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","volume":"110 1","pages":"4621-4624"},"PeriodicalIF":0.0,"publicationDate":"2012-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87671375","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 : 2012-08-31DOI: 10.1109/ICASSP.2012.6288582
Liangping Ma, Weimin Liu, A. Zeira
The overlay approach to dynamic spectrum access recently proposed in information theory allows both primary users (PUs) and secondary users (SUs) to simultaneously access the same spectrum with comparable power levels while ensuring no degradation to the performance of PUs. However, this approach is based on a number of idealized assumptions that are difficult to satisfy in practice, and existing efforts to address this issue fall outside physical layer processing. In this paper, we propose a number of physical layer mechanisms to make the overlay approach practical. In particular, we leverage the broadcast nature of the wireless medium and the latest breakthrough in full-duplex radios to resolve the synchronization problem and to get around the non-causal assumption while naturally offering delay diversity.
{"title":"Making overlay cognitive radios practical","authors":"Liangping Ma, Weimin Liu, A. Zeira","doi":"10.1109/ICASSP.2012.6288582","DOIUrl":"https://doi.org/10.1109/ICASSP.2012.6288582","url":null,"abstract":"The overlay approach to dynamic spectrum access recently proposed in information theory allows both primary users (PUs) and secondary users (SUs) to simultaneously access the same spectrum with comparable power levels while ensuring no degradation to the performance of PUs. However, this approach is based on a number of idealized assumptions that are difficult to satisfy in practice, and existing efforts to address this issue fall outside physical layer processing. In this paper, we propose a number of physical layer mechanisms to make the overlay approach practical. In particular, we leverage the broadcast nature of the wireless medium and the latest breakthrough in full-duplex radios to resolve the synchronization problem and to get around the non-causal assumption while naturally offering delay diversity.","PeriodicalId":6443,"journal":{"name":"2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","volume":"19 1","pages":"3145-3148"},"PeriodicalIF":0.0,"publicationDate":"2012-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90761596","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 : 2012-08-31DOI: 10.1109/ICASSP.2012.6287844
C. Paleologu, J. Benesty, F. Albu
In sparse adaptive filters, the adaptation gain is “proportionately” redistributed among all the coefficients, emphasizing the large ones in order to speed up their convergence. The improved proportionate affine projection algorithm (IPAPA) is a very attractive choice for echo cancellation, since it combines the good convergence features of the affine projection algorithm (APA) and the gain factors of the improved proportionate normalized least-mean-square (IPNLMS) algorithm. Similar to the APA, a matrix inversion is required within the IPAPA. For practical reasons, the matrix needs to be regularized before inversion, i.e., a positive constant is added to the elements of its main diagonal. In this paper, we propose a formula for choosing the regularization parameter of the IPAPA, aiming at attenuating the effects of the noise in the adaptive filter estimate. Simulation results indicate the validity of this approach in both network and acoustic echo cancellation scenarios.
{"title":"Regularization of the improved proportionate affine projection algorithm","authors":"C. Paleologu, J. Benesty, F. Albu","doi":"10.1109/ICASSP.2012.6287844","DOIUrl":"https://doi.org/10.1109/ICASSP.2012.6287844","url":null,"abstract":"In sparse adaptive filters, the adaptation gain is “proportionately” redistributed among all the coefficients, emphasizing the large ones in order to speed up their convergence. The improved proportionate affine projection algorithm (IPAPA) is a very attractive choice for echo cancellation, since it combines the good convergence features of the affine projection algorithm (APA) and the gain factors of the improved proportionate normalized least-mean-square (IPNLMS) algorithm. Similar to the APA, a matrix inversion is required within the IPAPA. For practical reasons, the matrix needs to be regularized before inversion, i.e., a positive constant is added to the elements of its main diagonal. In this paper, we propose a formula for choosing the regularization parameter of the IPAPA, aiming at attenuating the effects of the noise in the adaptive filter estimate. Simulation results indicate the validity of this approach in both network and acoustic echo cancellation scenarios.","PeriodicalId":6443,"journal":{"name":"2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","volume":"249 1","pages":"169-172"},"PeriodicalIF":0.0,"publicationDate":"2012-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72955989","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 : 2012-08-31DOI: 10.1109/ICASSP.2012.6289113
N. Verma, Kyong-Ho Lee, Kuk Jin Jang, Ali H. Shoeb
Advanced devices for embedded and ambient applications represent one of the most compelling classes of electronic systems, but they also impose more severe constraints on system resources than ever before. Although platform non-idealities have always posed a fundamental limitation, the overheads of conventional margining are now reaching intolerable levels. We describe an alternate approach to hardware resilience that applies to applications where advanced modeling and inference capabilities are required, a rapidly increasing emphasis in many applications. We show how a data-driven modeling framework for analyzing application data can also be used to effectively model and overcome a broad range of hardware non-idealities. Specific examples for biomedical sensors are shown that are able to retain performance with minimal on-line overhead despite the presence of severe digital- and analog-circuit non-idealities.
{"title":"Enabling system-level platform resilience through embedded data-driven inference capabilities in electronic devices","authors":"N. Verma, Kyong-Ho Lee, Kuk Jin Jang, Ali H. Shoeb","doi":"10.1109/ICASSP.2012.6289113","DOIUrl":"https://doi.org/10.1109/ICASSP.2012.6289113","url":null,"abstract":"Advanced devices for embedded and ambient applications represent one of the most compelling classes of electronic systems, but they also impose more severe constraints on system resources than ever before. Although platform non-idealities have always posed a fundamental limitation, the overheads of conventional margining are now reaching intolerable levels. We describe an alternate approach to hardware resilience that applies to applications where advanced modeling and inference capabilities are required, a rapidly increasing emphasis in many applications. We show how a data-driven modeling framework for analyzing application data can also be used to effectively model and overcome a broad range of hardware non-idealities. Specific examples for biomedical sensors are shown that are able to retain performance with minimal on-line overhead despite the presence of severe digital- and analog-circuit non-idealities.","PeriodicalId":6443,"journal":{"name":"2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","volume":"36 1","pages":"5285-5288"},"PeriodicalIF":0.0,"publicationDate":"2012-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78461801","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 : 2012-08-31DOI: 10.1109/ICASSP.2012.6288727
P. Borgnat, P. Abry, P. Flandrin
Surrogates are investigated as procedures of synthesis for multi-variate time series with prescribed properties. First it is shown how to prescribe a multivariate covariance function jointly with the (possibly non-Gaussian) marginal distributions. Second, using histogram matching by approximate optimal transport with the Sliced Wasserstein Distance, the surrogate synthesis is extended to prescribe covariance function and joint-distribution of the components. Algorithms are described and justified, and numerical examples are shown. MATLAB codes are publicly available online.
{"title":"Using surrogates and optimal transport for synthesis of stationary multivariate series with prescribed covariance function and non-gaussian joint-distribution","authors":"P. Borgnat, P. Abry, P. Flandrin","doi":"10.1109/ICASSP.2012.6288727","DOIUrl":"https://doi.org/10.1109/ICASSP.2012.6288727","url":null,"abstract":"Surrogates are investigated as procedures of synthesis for multi-variate time series with prescribed properties. First it is shown how to prescribe a multivariate covariance function jointly with the (possibly non-Gaussian) marginal distributions. Second, using histogram matching by approximate optimal transport with the Sliced Wasserstein Distance, the surrogate synthesis is extended to prescribe covariance function and joint-distribution of the components. Algorithms are described and justified, and numerical examples are shown. MATLAB codes are publicly available online.","PeriodicalId":6443,"journal":{"name":"2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","volume":"45 1","pages":"3729-3732"},"PeriodicalIF":0.0,"publicationDate":"2012-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77674051","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 : 2012-03-25DOI: 10.1109/ICASSP.2012.6288488
Lichuan Liu
The paper presents a female -friendly engineering education in digital signal processing (DSP) at Northern Illinois University (NIU), more generally, revising the negative value traditionally placed upon electrical engineering achievement for women. Important tasks are as follows: (1) Design the DSP curricula in female-friendly way. (2) Establish an interactive DSP learners' community by developing appropriate teaching strategies in the class. (3) Offer teaching supplements for the enrolled students.
{"title":"Female friendly DSP curriculum for expanding women's opportunities","authors":"Lichuan Liu","doi":"10.1109/ICASSP.2012.6288488","DOIUrl":"https://doi.org/10.1109/ICASSP.2012.6288488","url":null,"abstract":"The paper presents a female -friendly engineering education in digital signal processing (DSP) at Northern Illinois University (NIU), more generally, revising the negative value traditionally placed upon electrical engineering achievement for women. Important tasks are as follows: (1) Design the DSP curricula in female-friendly way. (2) Establish an interactive DSP learners' community by developing appropriate teaching strategies in the class. (3) Offer teaching supplements for the enrolled students.","PeriodicalId":6443,"journal":{"name":"2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","volume":"32 1","pages":"2757-2760"},"PeriodicalIF":0.0,"publicationDate":"2012-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73789373","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 : 2012-03-25DOI: 10.1109/ICASSP.2012.6288247
Jyun-Jie Wang, Houshou Chen
A novel suboptimal hiding algorithm for binary data based on weight approximation embedding, WAE, is proposed. Given a specified embedding rate, this algorithm exhibits an advantage of efficient binary embedding with reduced embedding complexity. The suboptimal WAE algorithm performs an embedding procedure through a parity check matrix. The optimal embedding based on maximal likelihood algorithm aims to locate the coset leader to minimize the embedding distortion. On the contrary, the WAE algorithm looks for a target vector close to the coset leader in an efficiently iterative manner. Given an linear embedding code C(n, k), the embedding complexity using the optimal algorithm is O(2k), while the complexity in the suboptimal WAE is reduced to O(sk) where s is the average iterations.
{"title":"A suboptimal embedding algorithm with low complexity for binary data hiding","authors":"Jyun-Jie Wang, Houshou Chen","doi":"10.1109/ICASSP.2012.6288247","DOIUrl":"https://doi.org/10.1109/ICASSP.2012.6288247","url":null,"abstract":"A novel suboptimal hiding algorithm for binary data based on weight approximation embedding, WAE, is proposed. Given a specified embedding rate, this algorithm exhibits an advantage of efficient binary embedding with reduced embedding complexity. The suboptimal WAE algorithm performs an embedding procedure through a parity check matrix. The optimal embedding based on maximal likelihood algorithm aims to locate the coset leader to minimize the embedding distortion. On the contrary, the WAE algorithm looks for a target vector close to the coset leader in an efficiently iterative manner. Given an linear embedding code C(n, k), the embedding complexity using the optimal algorithm is O(2k), while the complexity in the suboptimal WAE is reduced to O(sk) where s is the average iterations.","PeriodicalId":6443,"journal":{"name":"2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","volume":"30 1","pages":"1789-1792"},"PeriodicalIF":0.0,"publicationDate":"2012-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73885846","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 : 2012-03-25DOI: 10.1109/ICASSP.2012.6288676
A. Yeredor
Passive estimation of the Time-Difference of Arrival (TDOA) of a common signal at two (or more) sensors is a fundamental problem in signal processing, with applications mainly in emitter localization. A common approach to TDOA estimation is the maximization of the sample cross-correlation between the received signals. For various reasons, this correlation is sometimes computed via the frequency-domain, following a Discrete Fourier Transform (DFT) of the signals - in which case the linear correlation is essentially replaced with a cyclic correlation. Although the two computations differ merely by some relatively short “edge-effects”, these edge-effects can entail more impact than commonly predicted by their relative (usually negligible) effective durations. In this work we analyze the mean square TDOA estimation error resulting from the use of cyclic instead of linear correlations, showing that for some signals the loss can be more severe than what would be predicted by a simple linear dependence on the delay value.
{"title":"Analysis of the edge-effects in frequency-domain TDOA estimation","authors":"A. Yeredor","doi":"10.1109/ICASSP.2012.6288676","DOIUrl":"https://doi.org/10.1109/ICASSP.2012.6288676","url":null,"abstract":"Passive estimation of the Time-Difference of Arrival (TDOA) of a common signal at two (or more) sensors is a fundamental problem in signal processing, with applications mainly in emitter localization. A common approach to TDOA estimation is the maximization of the sample cross-correlation between the received signals. For various reasons, this correlation is sometimes computed via the frequency-domain, following a Discrete Fourier Transform (DFT) of the signals - in which case the linear correlation is essentially replaced with a cyclic correlation. Although the two computations differ merely by some relatively short “edge-effects”, these edge-effects can entail more impact than commonly predicted by their relative (usually negligible) effective durations. In this work we analyze the mean square TDOA estimation error resulting from the use of cyclic instead of linear correlations, showing that for some signals the loss can be more severe than what would be predicted by a simple linear dependence on the delay value.","PeriodicalId":6443,"journal":{"name":"2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","volume":"1 1","pages":"3521-3524"},"PeriodicalIF":0.0,"publicationDate":"2012-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73888794","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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