Sergiy A . Vorobyov - Academia.edu (original) (raw)
Papers by Sergiy A . Vorobyov
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IEEE Transactions on Signal Processing, 2020
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arXiv (Cornell University), Oct 21, 2019
We present a diversity multiplexing tradeoff (DMT) optimal tree pruning sphere decoding algorithm... more We present a diversity multiplexing tradeoff (DMT) optimal tree pruning sphere decoding algorithm which visits merely a single branch of the search tree of the sphere decoding (SD) algorithm, while maintaining the DMT optimality at high signal to noise ratio (SNR) regime. The search tree of the sphere decoding algorithm is pruned via intersecting one dimensional spheres with the hypersphere of the SD algorithm, and the radii are chosen to guarantee the DMT optimality. In contrast to the conventional DMT optimal SD algorithm, which is known to have a polynomial complexity at high SNR regime, we show that the proposed method achieves the DMT optimality by solely visiting a single branch of the search tree at high SNR regime. The simulation results are corroborated with the claimed characteristics of the algorithm in two different scenarios.
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An analytical lower bound on uplink channel capacity of a user in a massive multiple-input multip... more An analytical lower bound on uplink channel capacity of a user in a massive multiple-input multiple-output system where the channel vector and the covariance matrices of the users in that cell are unknown is derived in this paper. This analytical bound enables us to choose appropriate sample size for covariance matrix estimation to meet the spectral efficiency requirements. The accurate agreement between the derived bound and the simulated bound based on random samples of channel vectors and covariance matrices is shown.
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ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), May 23, 2022
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In massive multiple-input multiple-output (MIMO) systems, superimposed (SP) and time-multiplexed ... more In massive multiple-input multiple-output (MIMO) systems, superimposed (SP) and time-multiplexed (TM) pilots exhibit a complementary behavior, with the former and latter schemes offering a higher throughput in high and low inter-cell interference scenarios, respectively. Based on this observation, in this paper, we propose an algorithm for partitioning users into two disjoint sets comprising users that transmit TM and SP pilots. This selection of user sets is accomplished by minimizing the total inter-cell and intra-cell interference, and since this problem is found to be non-convex, a greedy approach is proposed to perform the partitioning. Based on simulations, it is shown that the proposed method is versatile and offers an improved performance in both high and low-interference scenarios.
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Signal Processing, Jun 1, 2020
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2022 IEEE International Symposium on Information Theory (ISIT), Jun 26, 2022
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ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Direction-of-arrival (DOA) estimation problem is a challenging one in the presence of coherent so... more Direction-of-arrival (DOA) estimation problem is a challenging one in the presence of coherent sources, when the sample size is small, and the signal-to-noise ratio is low. We address this problem by developing a new method called enhanced standard ESPRIT (ES ESPRIT), and also its unitary extension called enhanced unitary ESPRIT (EU ESPRIT). The proposed methods use statistics of the subspace perturbation. First, they generate 2K DOA candidates for K sources, and then discreetly select K of them. Numerical results show the superiority of EU ESPRIT over other existing methods especially in improving threshold performance and separating closely located sources with a small sample size.
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SSRN Electronic Journal
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Signal Processing, 2021
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2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2019
The optimal robust adaptive beamforming problem based on worst-case signal-to-noise-plus-interfer... more The optimal robust adaptive beamforming problem based on worst-case signal-to-noise-plus-interference ratio (SINR) maximization with a nonconvex uncertainty set of the desired steering vectors is considered. The uncertainty set consists of a similarity constraint and a (nonconvex) double-sided ball constraint. The worst-case SINR maximization problem is turned into a quadratic matrix inequality (QMI) problem using the strong duality of semidefinite programs. Then the linear matrix inequality (LMI) relaxation for the QMI problem is formulated, and is further restricted by adding an equivalent representation for the second largest eigenvalue of the positive semidefinite beamforming matrix to be nonnegative. It turns out that the restricted LMI problem is a bilinear matrix inequality (BLMI) relaxation problem. We propose an iterative algorithm to solve the BLMI problem that finds an optimal/suboptimal solution for the original QMI problem for the worst-case SINR maximization problem. To validate our results, simulation examples are presented and demonstrate the improved performance of the proposed robust beamformer in terms of the array output SINR.
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ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020
With a change of signal notion to graph signal, new means of performing blind source separation (... more With a change of signal notion to graph signal, new means of performing blind source separation (BSS) appear. Particularly, existing independent component analysis (ICA) methods exploit the non-Gaussianity of the signals or other types of prior information. For graph signals, such prior information is present in a graph of dependencies in the signals. We propose BSS of graph signals which uses the prior information presented by the signal graph together with nonGaussianity. We derive the identifiability conditions for the proposed method and compare them to the conditions when only graph or non-Gaussianity approach is used. In simulation studies, we verify that the new method can separate a broader range of graph signals and show that it is also more efficient when both approaches are useful.
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IEEE Transactions on Wireless Communications, 2018
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IEEE Geoscience and Remote Sensing Letters, 2017
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2015 IEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2015
The waveform separation based on matched filtering leads to the cross correlation interference, w... more The waveform separation based on matched filtering leads to the cross correlation interference, which deteriorates the performance of multiple-input multiple-output (MIMO) radar system. This paper investigates the performance of a waveform separation approach employing a novel orthogonal frequency division multiplexing scheme for MIMO synthetic aperture radar. The approach enables to separate the waveforms perfectly even though the waveforms are on common spectral support. By means of theoretical analysis confirmed also by simulations, we show that the proposed scheme decreases sidelobe ratio. Thus, the high-quality imaging can be achieved.
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2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2016
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Bookmarks Related papers MentionsView impact
IEEE Transactions on Signal Processing, 2020
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arXiv (Cornell University), Oct 21, 2019
We present a diversity multiplexing tradeoff (DMT) optimal tree pruning sphere decoding algorithm... more We present a diversity multiplexing tradeoff (DMT) optimal tree pruning sphere decoding algorithm which visits merely a single branch of the search tree of the sphere decoding (SD) algorithm, while maintaining the DMT optimality at high signal to noise ratio (SNR) regime. The search tree of the sphere decoding algorithm is pruned via intersecting one dimensional spheres with the hypersphere of the SD algorithm, and the radii are chosen to guarantee the DMT optimality. In contrast to the conventional DMT optimal SD algorithm, which is known to have a polynomial complexity at high SNR regime, we show that the proposed method achieves the DMT optimality by solely visiting a single branch of the search tree at high SNR regime. The simulation results are corroborated with the claimed characteristics of the algorithm in two different scenarios.
Bookmarks Related papers MentionsView impact
Bookmarks Related papers MentionsView impact
An analytical lower bound on uplink channel capacity of a user in a massive multiple-input multip... more An analytical lower bound on uplink channel capacity of a user in a massive multiple-input multiple-output system where the channel vector and the covariance matrices of the users in that cell are unknown is derived in this paper. This analytical bound enables us to choose appropriate sample size for covariance matrix estimation to meet the spectral efficiency requirements. The accurate agreement between the derived bound and the simulated bound based on random samples of channel vectors and covariance matrices is shown.
Bookmarks Related papers MentionsView impact
Bookmarks Related papers MentionsView impact
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), May 23, 2022
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In massive multiple-input multiple-output (MIMO) systems, superimposed (SP) and time-multiplexed ... more In massive multiple-input multiple-output (MIMO) systems, superimposed (SP) and time-multiplexed (TM) pilots exhibit a complementary behavior, with the former and latter schemes offering a higher throughput in high and low inter-cell interference scenarios, respectively. Based on this observation, in this paper, we propose an algorithm for partitioning users into two disjoint sets comprising users that transmit TM and SP pilots. This selection of user sets is accomplished by minimizing the total inter-cell and intra-cell interference, and since this problem is found to be non-convex, a greedy approach is proposed to perform the partitioning. Based on simulations, it is shown that the proposed method is versatile and offers an improved performance in both high and low-interference scenarios.
Bookmarks Related papers MentionsView impact
Signal Processing, Jun 1, 2020
Bookmarks Related papers MentionsView impact
2022 IEEE International Symposium on Information Theory (ISIT), Jun 26, 2022
Bookmarks Related papers MentionsView impact
ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Direction-of-arrival (DOA) estimation problem is a challenging one in the presence of coherent so... more Direction-of-arrival (DOA) estimation problem is a challenging one in the presence of coherent sources, when the sample size is small, and the signal-to-noise ratio is low. We address this problem by developing a new method called enhanced standard ESPRIT (ES ESPRIT), and also its unitary extension called enhanced unitary ESPRIT (EU ESPRIT). The proposed methods use statistics of the subspace perturbation. First, they generate 2K DOA candidates for K sources, and then discreetly select K of them. Numerical results show the superiority of EU ESPRIT over other existing methods especially in improving threshold performance and separating closely located sources with a small sample size.
Bookmarks Related papers MentionsView impact
SSRN Electronic Journal
Bookmarks Related papers MentionsView impact
Signal Processing, 2021
Bookmarks Related papers MentionsView impact
2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2019
The optimal robust adaptive beamforming problem based on worst-case signal-to-noise-plus-interfer... more The optimal robust adaptive beamforming problem based on worst-case signal-to-noise-plus-interference ratio (SINR) maximization with a nonconvex uncertainty set of the desired steering vectors is considered. The uncertainty set consists of a similarity constraint and a (nonconvex) double-sided ball constraint. The worst-case SINR maximization problem is turned into a quadratic matrix inequality (QMI) problem using the strong duality of semidefinite programs. Then the linear matrix inequality (LMI) relaxation for the QMI problem is formulated, and is further restricted by adding an equivalent representation for the second largest eigenvalue of the positive semidefinite beamforming matrix to be nonnegative. It turns out that the restricted LMI problem is a bilinear matrix inequality (BLMI) relaxation problem. We propose an iterative algorithm to solve the BLMI problem that finds an optimal/suboptimal solution for the original QMI problem for the worst-case SINR maximization problem. To validate our results, simulation examples are presented and demonstrate the improved performance of the proposed robust beamformer in terms of the array output SINR.
Bookmarks Related papers MentionsView impact
ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020
With a change of signal notion to graph signal, new means of performing blind source separation (... more With a change of signal notion to graph signal, new means of performing blind source separation (BSS) appear. Particularly, existing independent component analysis (ICA) methods exploit the non-Gaussianity of the signals or other types of prior information. For graph signals, such prior information is present in a graph of dependencies in the signals. We propose BSS of graph signals which uses the prior information presented by the signal graph together with nonGaussianity. We derive the identifiability conditions for the proposed method and compare them to the conditions when only graph or non-Gaussianity approach is used. In simulation studies, we verify that the new method can separate a broader range of graph signals and show that it is also more efficient when both approaches are useful.
Bookmarks Related papers MentionsView impact
IEEE Transactions on Wireless Communications, 2018
Bookmarks Related papers MentionsView impact
IEEE Geoscience and Remote Sensing Letters, 2017
Bookmarks Related papers MentionsView impact
2015 IEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2015
The waveform separation based on matched filtering leads to the cross correlation interference, w... more The waveform separation based on matched filtering leads to the cross correlation interference, which deteriorates the performance of multiple-input multiple-output (MIMO) radar system. This paper investigates the performance of a waveform separation approach employing a novel orthogonal frequency division multiplexing scheme for MIMO synthetic aperture radar. The approach enables to separate the waveforms perfectly even though the waveforms are on common spectral support. By means of theoretical analysis confirmed also by simulations, we show that the proposed scheme decreases sidelobe ratio. Thus, the high-quality imaging can be achieved.
Bookmarks Related papers MentionsView impact
2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2016
Bookmarks Related papers MentionsView impact