The paper proposes a novel distributed two-stage resource allocation technique for multiple-input multiple-output cognitive radio links operating within an environment of multiple multi-antenna primary links. Each primary link occupies exclusively part of the resources and offers the opportunity to coexistence. In the first stage, secondary links request primary resources and are either accepted or rejected based on the preferences of the primary links. In the second phase, primary links price their interference temperature and an iterative precoding optimization and price update algorithm is performed. We show the existence of equilibria by showing that the demand function fulfils the weak gross substitute property. Numerical simulations illustrate an example matching and resource allocation.
{"title":"Matching and exchange market based resource allocation in MIMO cognitive radio networks","authors":"Eduard Axel Jorswieck, Pan Cao","doi":"10.5281/ZENODO.43566","DOIUrl":"https://doi.org/10.5281/ZENODO.43566","url":null,"abstract":"The paper proposes a novel distributed two-stage resource allocation technique for multiple-input multiple-output cognitive radio links operating within an environment of multiple multi-antenna primary links. Each primary link occupies exclusively part of the resources and offers the opportunity to coexistence. In the first stage, secondary links request primary resources and are either accepted or rejected based on the preferences of the primary links. In the second phase, primary links price their interference temperature and an iterative precoding optimization and price update algorithm is performed. We show the existence of equilibria by showing that the demand function fulfils the weak gross substitute property. Numerical simulations illustrate an example matching and resource allocation.","PeriodicalId":400766,"journal":{"name":"21st European Signal Processing Conference (EUSIPCO 2013)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133035753","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}
A diffusion widely linear quaternion least mean square (D-WLIQLMS) algorithm for the collaborative processing of quaternion signals over distributed networks is proposed. We show that the underlying quaternion division algebra and the widely linear model allow for a unified processing of 3D and 4D data, which can exhibit both circular and noncircular distributions. The analysis shows that the D-WLIQLMS provides a solution that is robust to link and node failures in sensor networks. Simulations on benchmark 4D signals illustrate the advantages offered by the D-WLIQLMS.
{"title":"An adaptive diffusion quaternion LMS algorithm for distributed networks of 3D and 4D vector sensors","authors":"C. Jahanchahi, D. Mandic","doi":"10.5281/ZENODO.43726","DOIUrl":"https://doi.org/10.5281/ZENODO.43726","url":null,"abstract":"A diffusion widely linear quaternion least mean square (D-WLIQLMS) algorithm for the collaborative processing of quaternion signals over distributed networks is proposed. We show that the underlying quaternion division algebra and the widely linear model allow for a unified processing of 3D and 4D data, which can exhibit both circular and noncircular distributions. The analysis shows that the D-WLIQLMS provides a solution that is robust to link and node failures in sensor networks. Simulations on benchmark 4D signals illustrate the advantages offered by the D-WLIQLMS.","PeriodicalId":400766,"journal":{"name":"21st European Signal Processing Conference (EUSIPCO 2013)","volume":"319 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133335619","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}
In this paper, we will firstly show that the Cyclic Autocorrelation function (CAF) is a sparse function in the cyclic frequency domain. Then using this property we propose a new CAF estimator, using Compressed Sensing (CS) technique with OMP algorithm [1]. This estimator outperforms the classic estimator used in [2]. Furthermore, since our estimator does not need any information, we claim that it is a blind estimator whereas the estimator used in [2] is clearly not blind because it needs the knowledge of the cyclic frequency. Using this new CAF estimator we proposed in the second part of this paper a new blind free bands detector. It assumes that two estimated CAF of two successive packets of samples, should have close cyclic frequencies, if a telecommunication signal is present. This new detector is a soft version of the detector already presented in [3]. This methods outperforms the cyclostationnarity detector of Dantawate Giannakis of [2].
{"title":"Blind free band detector based on the sparsity of the Cyclic Autocorrelation function","authors":"Z. Khalaf, J. Palicot, A. Nafkha, Honggang Zhang","doi":"10.5281/ZENODO.43430","DOIUrl":"https://doi.org/10.5281/ZENODO.43430","url":null,"abstract":"In this paper, we will firstly show that the Cyclic Autocorrelation function (CAF) is a sparse function in the cyclic frequency domain. Then using this property we propose a new CAF estimator, using Compressed Sensing (CS) technique with OMP algorithm [1]. This estimator outperforms the classic estimator used in [2]. Furthermore, since our estimator does not need any information, we claim that it is a blind estimator whereas the estimator used in [2] is clearly not blind because it needs the knowledge of the cyclic frequency. Using this new CAF estimator we proposed in the second part of this paper a new blind free bands detector. It assumes that two estimated CAF of two successive packets of samples, should have close cyclic frequencies, if a telecommunication signal is present. This new detector is a soft version of the detector already presented in [3]. This methods outperforms the cyclostationnarity detector of Dantawate Giannakis of [2].","PeriodicalId":400766,"journal":{"name":"21st European Signal Processing Conference (EUSIPCO 2013)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123943248","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}
In GNSS (Global Navigation Satellite System) multipath (MP) results to be one of the main error sources affecting the GNSS solution. In this paper a Linear Adaptive Filter (LAF) technique [1] is applied, based on Least Squares (LS), to estimate the MP coefficients and delay by using a post-correlation approach. An assumption using LAFs [1] is the noise to be a white process, but considering post-correlation data the hypothesis of uncorrelation among the samples is not valid. The LAF is a stat-of-the-art technique, but not in the GNSS-MP-detection and mitigation field. With the objective of using this method for this purpose, the effects of the noise correlation in LS filters are studied in this paper, when the technique is applied to GNSS channel estimate in post-correlation. In this paper, a preliminary analysis is done, by means of simulations. Comparisons are shown between data affected by correlated and uncorrelated noise, using realistic GNSS data.
{"title":"Effects of noise correlation on least squares filtering in multipath detection for GNSS","authors":"S. Ugazio, L. Presti","doi":"10.5281/ZENODO.43603","DOIUrl":"https://doi.org/10.5281/ZENODO.43603","url":null,"abstract":"In GNSS (Global Navigation Satellite System) multipath (MP) results to be one of the main error sources affecting the GNSS solution. In this paper a Linear Adaptive Filter (LAF) technique [1] is applied, based on Least Squares (LS), to estimate the MP coefficients and delay by using a post-correlation approach. An assumption using LAFs [1] is the noise to be a white process, but considering post-correlation data the hypothesis of uncorrelation among the samples is not valid. The LAF is a stat-of-the-art technique, but not in the GNSS-MP-detection and mitigation field. With the objective of using this method for this purpose, the effects of the noise correlation in LS filters are studied in this paper, when the technique is applied to GNSS channel estimate in post-correlation. In this paper, a preliminary analysis is done, by means of simulations. Comparisons are shown between data affected by correlated and uncorrelated noise, using realistic GNSS data.","PeriodicalId":400766,"journal":{"name":"21st European Signal Processing Conference (EUSIPCO 2013)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123195781","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}
In this work, we have investigated the heart sound (HS) detection performance of Hidden Markov Model (HMM) in respiratory sound. Respiratory sound is composed of heart sound and lung sound, and the main frequency components of these two sounds overlap with each other. To detect the locations of heart sound segments in such adverse condition accurately, the proposed method employs following steps. First, the Shannon entropy feature is extracted for robust representation of respiratory signal for different flow rates. Second, the probabilistic models are constructed by training HMM. Finally, the location of heart sound segments are efficiently estimated by the Viterbi decoding algorithm. The experimental results showed that the proposed heart sound detection method outperforms the three well-known heart sound detection methods in the literature. The average false negative rate (FNR) values for the proposed method are 5.4 ± 2.4 and 6.3 ± 1.3 for both low and medium respiratory flow rate, respectively, which are significantly lower than that of the compared methods in the literature.
{"title":"Heart sound detection in respiratory sound using Hidden Markov Model","authors":"Hamed Shamsi, I. Y. Özbek","doi":"10.5281/ZENODO.43649","DOIUrl":"https://doi.org/10.5281/ZENODO.43649","url":null,"abstract":"In this work, we have investigated the heart sound (HS) detection performance of Hidden Markov Model (HMM) in respiratory sound. Respiratory sound is composed of heart sound and lung sound, and the main frequency components of these two sounds overlap with each other. To detect the locations of heart sound segments in such adverse condition accurately, the proposed method employs following steps. First, the Shannon entropy feature is extracted for robust representation of respiratory signal for different flow rates. Second, the probabilistic models are constructed by training HMM. Finally, the location of heart sound segments are efficiently estimated by the Viterbi decoding algorithm. The experimental results showed that the proposed heart sound detection method outperforms the three well-known heart sound detection methods in the literature. The average false negative rate (FNR) values for the proposed method are 5.4 ± 2.4 and 6.3 ± 1.3 for both low and medium respiratory flow rate, respectively, which are significantly lower than that of the compared methods in the literature.","PeriodicalId":400766,"journal":{"name":"21st European Signal Processing Conference (EUSIPCO 2013)","volume":"320 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123643052","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}
In phased array antennas, by varying the complex element weights beam patterns with desired shapes can be synthesized and/or steered to desired directions. These complex weights can be implemented by using amplitude controllers and phase shifters at the system level. Since controlling the phase of an RF signal is much easier than controlling its power, many systems do not have an individual amplitude controller for each element. Hence, beamshaping and steering are to be achieved by varying only the element phases. In this work, a new approach is proposed for phase-only beam synthesis problem. In this approach, the phase-only beam synthesis is formulated as a non-convex quadratically constrained quadratic problem (QCQP). Then, it is relaxed to a convex semidefinite problem (SDP), which generally provides an undesired high rank solution. An iterative technique is developed to obtain a rank-1 solution to the relaxed convex SDP. Conducted experiments show that, proposedmethod can successfully synthesize beam shapes with desired characteristics and steering directions by using only the element phases.
{"title":"Phase-only beam synthesis by iterative semidefinite relaxations with rank refinement","authors":"Y. K. Alp, O. Arikan, A. Bayri","doi":"10.5281/ZENODO.43340","DOIUrl":"https://doi.org/10.5281/ZENODO.43340","url":null,"abstract":"In phased array antennas, by varying the complex element weights beam patterns with desired shapes can be synthesized and/or steered to desired directions. These complex weights can be implemented by using amplitude controllers and phase shifters at the system level. Since controlling the phase of an RF signal is much easier than controlling its power, many systems do not have an individual amplitude controller for each element. Hence, beamshaping and steering are to be achieved by varying only the element phases. In this work, a new approach is proposed for phase-only beam synthesis problem. In this approach, the phase-only beam synthesis is formulated as a non-convex quadratically constrained quadratic problem (QCQP). Then, it is relaxed to a convex semidefinite problem (SDP), which generally provides an undesired high rank solution. An iterative technique is developed to obtain a rank-1 solution to the relaxed convex SDP. Conducted experiments show that, proposedmethod can successfully synthesize beam shapes with desired characteristics and steering directions by using only the element phases.","PeriodicalId":400766,"journal":{"name":"21st European Signal Processing Conference (EUSIPCO 2013)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122797753","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}
In this paper, a space-variant cubic-spline interpolation (CSI) scheme by the use of the warped distance is developed to improve the performance. Furthermore, a modified overlap-save sub-image method is introduced to solve the boundary condition problems that occur between two neighboring subimages in the actual image. Experimental results show that the proposed improved CSI scheme can actually achieve a better PSNR than the existing interpolation algorithms including the original CSI scheme.
{"title":"A space-variant cubic-spline interpolation","authors":"Jianxing Jiang, Shaohua Hong, Lin Wang","doi":"10.5281/ZENODO.43567","DOIUrl":"https://doi.org/10.5281/ZENODO.43567","url":null,"abstract":"In this paper, a space-variant cubic-spline interpolation (CSI) scheme by the use of the warped distance is developed to improve the performance. Furthermore, a modified overlap-save sub-image method is introduced to solve the boundary condition problems that occur between two neighboring subimages in the actual image. Experimental results show that the proposed improved CSI scheme can actually achieve a better PSNR than the existing interpolation algorithms including the original CSI scheme.","PeriodicalId":400766,"journal":{"name":"21st European Signal Processing Conference (EUSIPCO 2013)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121601939","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}
Ceyhun Eksin, Pooya Molavi, Alejandro Ribeiro, A. Jadbabaie
We consider a repeated network game where agents' utilities are quadratic functions of the state of the world and actions of all the agents. The state of the world is represented by a vector on which agents receive private signals with Gaussian noise. We define the solution concept as Bayesian Nash equilibrium and present a recursion to compute equilibrium strategies locally if an equilibrium exists at all stages. We further provide conditions under which a unique equilibrium exists. We conclude with an example of the proposed recursion in a repeated Cournot competition game and discuss properties of convergence such as efficient learning and convergence rate.
{"title":"Distributed filters for Bayesian network games","authors":"Ceyhun Eksin, Pooya Molavi, Alejandro Ribeiro, A. Jadbabaie","doi":"10.5281/ZENODO.43737","DOIUrl":"https://doi.org/10.5281/ZENODO.43737","url":null,"abstract":"We consider a repeated network game where agents' utilities are quadratic functions of the state of the world and actions of all the agents. The state of the world is represented by a vector on which agents receive private signals with Gaussian noise. We define the solution concept as Bayesian Nash equilibrium and present a recursion to compute equilibrium strategies locally if an equilibrium exists at all stages. We further provide conditions under which a unique equilibrium exists. We conclude with an example of the proposed recursion in a repeated Cournot competition game and discuss properties of convergence such as efficient learning and convergence rate.","PeriodicalId":400766,"journal":{"name":"21st European Signal Processing Conference (EUSIPCO 2013)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131051756","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}
A novel compound Structural Health Monitoring (SHM) method as well as some signal processing and communication challenges for a robust methodology are presented in this paper. The performance of the two-step SHM method is compared to some other established damage detection techniques. The proposed method was found to identify the location of local damage more accurately than the other methods. Significant signal processing and communication aspects still need to be addressed in order to enhance the robustness of the method.
{"title":"Damage assessment of bridges using compound SHM- signal processing and communication challenges","authors":"R. Soman, T. Onoufriou, M. Kyriakides","doi":"10.5281/ZENODO.43611","DOIUrl":"https://doi.org/10.5281/ZENODO.43611","url":null,"abstract":"A novel compound Structural Health Monitoring (SHM) method as well as some signal processing and communication challenges for a robust methodology are presented in this paper. The performance of the two-step SHM method is compared to some other established damage detection techniques. The proposed method was found to identify the location of local damage more accurately than the other methods. Significant signal processing and communication aspects still need to be addressed in order to enhance the robustness of the method.","PeriodicalId":400766,"journal":{"name":"21st European Signal Processing Conference (EUSIPCO 2013)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130812862","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}
Spatial Spectrum estimation is a key technique used in a wide variety of problems arising in signal processing and communication, particularly those employing multiple antennas. In many scenarios such as direction finding using antenna arrays, it is crucial to estimate which directions in space contribute to active sources (indicated by a non zero power). It has been recently shown that if the sources from different directions are statistically uncorrelated, it is possible to identify as many as O(M2) active sources using only M physical antennas. A sparse representation for the spatial spectrum was further exploited to reconstruct the spectrum using convex optimization techniques. In this paper, we consider the situation when there is non zero cross correlation between the sources impinging from different directions. We investigate if, fundamentally, it still possible to identify more sources than the number of physical sensors and what role the cross correlation terms play. Recovery guarantees are developed to ensure uniqueness of the sparse representation for spectrum sensing. They are further extended to establish conditions under which a greedy heuristic, namely the Orthogonal Matching Pursuit algorithm will successfully recover the sparse spectrum. It is shown that in both cases, it is possible to recover support of larger size provided the correlation terms are small compared to the power of the impinging signals.
{"title":"Conditions for identifiability in sparse spatial spectrum sensing","authors":"P. Pal, P. Vaidyanathan","doi":"10.5281/ZENODO.43683","DOIUrl":"https://doi.org/10.5281/ZENODO.43683","url":null,"abstract":"Spatial Spectrum estimation is a key technique used in a wide variety of problems arising in signal processing and communication, particularly those employing multiple antennas. In many scenarios such as direction finding using antenna arrays, it is crucial to estimate which directions in space contribute to active sources (indicated by a non zero power). It has been recently shown that if the sources from different directions are statistically uncorrelated, it is possible to identify as many as O(M2) active sources using only M physical antennas. A sparse representation for the spatial spectrum was further exploited to reconstruct the spectrum using convex optimization techniques. In this paper, we consider the situation when there is non zero cross correlation between the sources impinging from different directions. We investigate if, fundamentally, it still possible to identify more sources than the number of physical sensors and what role the cross correlation terms play. Recovery guarantees are developed to ensure uniqueness of the sparse representation for spectrum sensing. They are further extended to establish conditions under which a greedy heuristic, namely the Orthogonal Matching Pursuit algorithm will successfully recover the sparse spectrum. It is shown that in both cases, it is possible to recover support of larger size provided the correlation terms are small compared to the power of the impinging signals.","PeriodicalId":400766,"journal":{"name":"21st European Signal Processing Conference (EUSIPCO 2013)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129086093","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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