Pub Date : 2020-06-01DOI: 10.1109/SAM48682.2020.9104372
Sicong Sun, Z. Ye, Xingyu Zhu
Compared with uniform linear array (ULA), the coprime array can obtain larger array aperture with the same number of physical sensors, which leads to higher spatial resolution and less effect of mutual coupling. Also, the degrees of freedom (DOFs) can be increased by reconstructing the sampling covariance matrix (SCM) in virtual array domain. In this paper, we propose a robust adaptive beamforming (RAB) algorithm based on coprime array. A novel subspace based method is performed in virtual array domain to estimate the power and direction of arrival (DOA) of interference, which also obtains the ability for DOFs enhancement. Simulation results demonstrate the robustness and effectiveness of the proposed method.
{"title":"Robust Adaptive Beamforming for Coprime Array Based on Interference Power Estimation via Subspace","authors":"Sicong Sun, Z. Ye, Xingyu Zhu","doi":"10.1109/SAM48682.2020.9104372","DOIUrl":"https://doi.org/10.1109/SAM48682.2020.9104372","url":null,"abstract":"Compared with uniform linear array (ULA), the coprime array can obtain larger array aperture with the same number of physical sensors, which leads to higher spatial resolution and less effect of mutual coupling. Also, the degrees of freedom (DOFs) can be increased by reconstructing the sampling covariance matrix (SCM) in virtual array domain. In this paper, we propose a robust adaptive beamforming (RAB) algorithm based on coprime array. A novel subspace based method is performed in virtual array domain to estimate the power and direction of arrival (DOA) of interference, which also obtains the ability for DOFs enhancement. Simulation results demonstrate the robustness and effectiveness of the proposed method.","PeriodicalId":6753,"journal":{"name":"2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"12 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75188010","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 : 2020-06-01DOI: 10.1109/SAM48682.2020.9104283
Hantian Wu, Qing Shen, Wei Liu, W. Cui
For a uniform linear array (ULA) with specially designed spacing and system settings, the received signals are first decomposed into different frequency bins via discrete Fourier transform (DFT). By grouping the frequencies of interest into several pairs, a generalized complexity reduction method is proposed to merge the redundant entries in both the auto-correlation matrices at each frequency and the cross-correlation matrices across different frequencies, followed by the group sparsity based low-complexity method to find the directions of arrival (DOAs) of the impinging signals. Simulation results demonstrate that significantly reduced complexity and improved performance can be achieved by the proposed method.
{"title":"Underdetermined Low-Complexity Wideband DOA Estimation with Uniform Linear Arrays","authors":"Hantian Wu, Qing Shen, Wei Liu, W. Cui","doi":"10.1109/SAM48682.2020.9104283","DOIUrl":"https://doi.org/10.1109/SAM48682.2020.9104283","url":null,"abstract":"For a uniform linear array (ULA) with specially designed spacing and system settings, the received signals are first decomposed into different frequency bins via discrete Fourier transform (DFT). By grouping the frequencies of interest into several pairs, a generalized complexity reduction method is proposed to merge the redundant entries in both the auto-correlation matrices at each frequency and the cross-correlation matrices across different frequencies, followed by the group sparsity based low-complexity method to find the directions of arrival (DOAs) of the impinging signals. Simulation results demonstrate that significantly reduced complexity and improved performance can be achieved by the proposed method.","PeriodicalId":6753,"journal":{"name":"2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"17 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84416130","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 : 2020-06-01DOI: 10.1109/SAM48682.2020.9104313
Ishai Eljarat, J. Tabrikian, I. Bilik
The emerging problem of automotive radars congestion is addressed in this work. Modern automotive radars handle this problem via randomization of the transmit signal parameters. Alternatively, frequency allocation methods lead to narrow-band radar operation and as a result, reduced range resolution. This work proposes to mitigate the mutual interference between radars, while optimizing the localization performance by collaborative spectrum allocation and waveform design. According to the proposed approach, the transmit energy is allocated across the entire available spectrum by minimization of the Weiss-Weinstein bound. The proposed spectrum allocation approach allows to avoid frequencies occupied by interfering radars and the use of the entire spectrum allows to achieve the maximal possible resolution.
{"title":"Collaborative Spectrum Allocation and Waveform Design for Radar Coexistence","authors":"Ishai Eljarat, J. Tabrikian, I. Bilik","doi":"10.1109/SAM48682.2020.9104313","DOIUrl":"https://doi.org/10.1109/SAM48682.2020.9104313","url":null,"abstract":"The emerging problem of automotive radars congestion is addressed in this work. Modern automotive radars handle this problem via randomization of the transmit signal parameters. Alternatively, frequency allocation methods lead to narrow-band radar operation and as a result, reduced range resolution. This work proposes to mitigate the mutual interference between radars, while optimizing the localization performance by collaborative spectrum allocation and waveform design. According to the proposed approach, the transmit energy is allocated across the entire available spectrum by minimization of the Weiss-Weinstein bound. The proposed spectrum allocation approach allows to avoid frequencies occupied by interfering radars and the use of the entire spectrum allows to achieve the maximal possible resolution.","PeriodicalId":6753,"journal":{"name":"2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"58 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84832953","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 : 2020-06-01DOI: 10.1109/SAM48682.2020.9104221
Jiantao Shi
In the existing works on FDA beam-patterns produced by the traditional FDA are time variant, and this causes difficulties in target detecting and beam-pattern steering. For solving the problem, several time-dependent frequency offsets based time-invariant FDA beam-pattern design methods have been proposed, which, however, neglected the time-range relationship and led to erroneous conclusions. In this note, considering the practical constraint and the relationship between time and range, it is concluded that FDA beam-patterns are always time-variant and it is unable to form time-invariant beam-patterns.
{"title":"On time-invariant FDA beam-pattern design based on time-dependent frequency offsets","authors":"Jiantao Shi","doi":"10.1109/SAM48682.2020.9104221","DOIUrl":"https://doi.org/10.1109/SAM48682.2020.9104221","url":null,"abstract":"In the existing works on FDA beam-patterns produced by the traditional FDA are time variant, and this causes difficulties in target detecting and beam-pattern steering. For solving the problem, several time-dependent frequency offsets based time-invariant FDA beam-pattern design methods have been proposed, which, however, neglected the time-range relationship and led to erroneous conclusions. In this note, considering the practical constraint and the relationship between time and range, it is concluded that FDA beam-patterns are always time-variant and it is unable to form time-invariant beam-patterns.","PeriodicalId":6753,"journal":{"name":"2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"1 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85474578","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 : 2020-06-01DOI: 10.1109/SAM48682.2020.9104323
Yu-Hsiao Fan, Ganapati Hegde, C. Masouros, M. Pesavento
The extremely high cost associated with massive multiple-input multiple-output (MIMO) systems when it is employed with fully digital precoding can be reduced by applying hybrid precoding at an expense of increased transmit power. In such a hybrid precoding system, the transmit power required to achieve a certain quality-of-service (QoS) can be significantly reduced by employing the constructive interference (CI) precoding technique. However, as illustrated in the paper, the symbol error rate (SER) performance of CI-based precoding is very sensitive to channel errors. To address this challenge we propose a hybrid precoding approach with robustness against channel quantization error and channel estimation error. Simulation results demonstrate the superior energy efficiency of the proposed robust hybrid precoding when compared to that of a conventional non-robust precoding scheme in achieving a required QoS target.
{"title":"Interference Exploitation-Based Hybrid Precoding With Robustness Against Channel Errors","authors":"Yu-Hsiao Fan, Ganapati Hegde, C. Masouros, M. Pesavento","doi":"10.1109/SAM48682.2020.9104323","DOIUrl":"https://doi.org/10.1109/SAM48682.2020.9104323","url":null,"abstract":"The extremely high cost associated with massive multiple-input multiple-output (MIMO) systems when it is employed with fully digital precoding can be reduced by applying hybrid precoding at an expense of increased transmit power. In such a hybrid precoding system, the transmit power required to achieve a certain quality-of-service (QoS) can be significantly reduced by employing the constructive interference (CI) precoding technique. However, as illustrated in the paper, the symbol error rate (SER) performance of CI-based precoding is very sensitive to channel errors. To address this challenge we propose a hybrid precoding approach with robustness against channel quantization error and channel estimation error. Simulation results demonstrate the superior energy efficiency of the proposed robust hybrid precoding when compared to that of a conventional non-robust precoding scheme in achieving a required QoS target.","PeriodicalId":6753,"journal":{"name":"2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"73 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86057116","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 : 2020-06-01DOI: 10.1109/SAM48682.2020.9104386
Chunmei Xu, Shengheng Liu, Cheng Zhang, Yongming Huang, Luxi Yang
In this paper, we consider a multi-cell downlink mmWave communication network and investigate an efficient transmission scheme for all base stations. Since the beams are highly directed with respected to the user equipments, user scheduling and beam selection strategy should be jointly considered. The objective is to develop the joint user scheduling and beam selection strategy that minimizes the long-term average delay cost while satisfying the instantaneous quality of service constraint of each user. To achieve the long-term performance, a distributed algorithm is proposed to develop the joint strategy based on multi-agent reinforcement learning. Simulation results validate the effectiveness of the proposed intelligent distributed method.
{"title":"Joint User Scheduling and Beam Selection in mmWave Networks Based on Multi-Agent Reinforcement Learning","authors":"Chunmei Xu, Shengheng Liu, Cheng Zhang, Yongming Huang, Luxi Yang","doi":"10.1109/SAM48682.2020.9104386","DOIUrl":"https://doi.org/10.1109/SAM48682.2020.9104386","url":null,"abstract":"In this paper, we consider a multi-cell downlink mmWave communication network and investigate an efficient transmission scheme for all base stations. Since the beams are highly directed with respected to the user equipments, user scheduling and beam selection strategy should be jointly considered. The objective is to develop the joint user scheduling and beam selection strategy that minimizes the long-term average delay cost while satisfying the instantaneous quality of service constraint of each user. To achieve the long-term performance, a distributed algorithm is proposed to develop the joint strategy based on multi-agent reinforcement learning. Simulation results validate the effectiveness of the proposed intelligent distributed method.","PeriodicalId":6753,"journal":{"name":"2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"34 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78161181","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 : 2020-06-01DOI: 10.1109/SAM48682.2020.9104392
Yacine Meslem, A. Aïssa-El-Bey, M. Djeddou
With a convenient concatenation of a convex relaxation-based detector and a simple greedy algorithm, we propose an improved Post Detection Sparse error Recovery (PDSR) approach for massive Multiple Input Multiple Output (m-MIMO) systems that, in particular, transmit QAM signals. The proposed PDSR approach can perform well in situations, where the classical one, either acts poorly or completely fails. We further propose an Alternating Direction Method of Multipliers (ADMM)-based solver for the convex detector, which is advan¬tageous in maintaining an affordable complexity to the overall proposed detection scheme. Numerical experiments show the efficiency of our approach, especially when applied to overloaded m-MIMO systems.
{"title":"Improved sparse error recovery approach for detecting QAM signals in overloaded massive MIMO systems","authors":"Yacine Meslem, A. Aïssa-El-Bey, M. Djeddou","doi":"10.1109/SAM48682.2020.9104392","DOIUrl":"https://doi.org/10.1109/SAM48682.2020.9104392","url":null,"abstract":"With a convenient concatenation of a convex relaxation-based detector and a simple greedy algorithm, we propose an improved Post Detection Sparse error Recovery (PDSR) approach for massive Multiple Input Multiple Output (m-MIMO) systems that, in particular, transmit QAM signals. The proposed PDSR approach can perform well in situations, where the classical one, either acts poorly or completely fails. We further propose an Alternating Direction Method of Multipliers (ADMM)-based solver for the convex detector, which is advan¬tageous in maintaining an affordable complexity to the overall proposed detection scheme. Numerical experiments show the efficiency of our approach, especially when applied to overloaded m-MIMO systems.","PeriodicalId":6753,"journal":{"name":"2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"23 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76651343","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 : 2020-06-01DOI: 10.1109/SAM48682.2020.9104270
Jingwei Xu, H. So
In this paper, the element-pulse coding (EPC) based multiple-input multiple-output (MIMO) radar is studied for resolving range ambiguity in clutter-free scenario. The fundamental transmit and receive procedures as well as the relationship between encoding and decoding are presented. To address the range ambiguity issue, the EPC entries in element dimension are extended to be an arbitrary permutation of the Fourier basis entries. The beampattern is designed to extract the desired target signal while suppressing targets from nuisance range regions. Both conventional and enhanced array beamforming methods are discussed. Simulation examples are provided to demonstrate the effectiveness of the proposed method.
{"title":"Study on Coding Scheme with EPC-MIMO Radar in Clutter-Free Scenario","authors":"Jingwei Xu, H. So","doi":"10.1109/SAM48682.2020.9104270","DOIUrl":"https://doi.org/10.1109/SAM48682.2020.9104270","url":null,"abstract":"In this paper, the element-pulse coding (EPC) based multiple-input multiple-output (MIMO) radar is studied for resolving range ambiguity in clutter-free scenario. The fundamental transmit and receive procedures as well as the relationship between encoding and decoding are presented. To address the range ambiguity issue, the EPC entries in element dimension are extended to be an arbitrary permutation of the Fourier basis entries. The beampattern is designed to extract the desired target signal while suppressing targets from nuisance range regions. Both conventional and enhanced array beamforming methods are discussed. Simulation examples are provided to demonstrate the effectiveness of the proposed method.","PeriodicalId":6753,"journal":{"name":"2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"41 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82385918","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 : 2020-06-01DOI: 10.1109/SAM48682.2020.9104250
A. Keziou, N. Mamouni, H. Fenniri
For separating linear instantaneous mixtures of independent/dependent source components, we extend the independent/dependent blind source separation method, proposed by [1], to cover the more general case, where the dependency structure of the source components and the related parameter are both unknown. An application is given for separating scanned recto-verso documents.
{"title":"Separation of recto-verso documents using copula based dependent source separation","authors":"A. Keziou, N. Mamouni, H. Fenniri","doi":"10.1109/SAM48682.2020.9104250","DOIUrl":"https://doi.org/10.1109/SAM48682.2020.9104250","url":null,"abstract":"For separating linear instantaneous mixtures of independent/dependent source components, we extend the independent/dependent blind source separation method, proposed by [1], to cover the more general case, where the dependency structure of the source components and the related parameter are both unknown. An application is given for separating scanned recto-verso documents.","PeriodicalId":6753,"journal":{"name":"2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"12 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87669536","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 : 2020-06-01DOI: 10.1109/SAM48682.2020.9104257
Shisheng Guo, Songlin Li, G. Cui, Shihao Fan, L. Kong, Xiaobo Yang
Localization for moving multi-target in urban environment is difficult because of the ambiguities of targets’ different multipaths. This paper considers the targets localization problem via non-line-of-sight (NLOS) signals in an L-shaped corner environment using the time-division multiple-input-multiple-output (TD-MIMO) imaging radar. We first analyse the propagation characters of the multipath signals and establish the signal model of targets hiding behind corner for TD-MIMO. Then, a novel multi-target localization algorithm by exploiting the multipath ghosts after applying back-projection (BP) imaging algorithm is proposed. Finally, we illustrate the validation the proposed algorithm via several simulation results.
{"title":"MIMO Radar Localization of Targets Behind L-shaped Corners","authors":"Shisheng Guo, Songlin Li, G. Cui, Shihao Fan, L. Kong, Xiaobo Yang","doi":"10.1109/SAM48682.2020.9104257","DOIUrl":"https://doi.org/10.1109/SAM48682.2020.9104257","url":null,"abstract":"Localization for moving multi-target in urban environment is difficult because of the ambiguities of targets’ different multipaths. This paper considers the targets localization problem via non-line-of-sight (NLOS) signals in an L-shaped corner environment using the time-division multiple-input-multiple-output (TD-MIMO) imaging radar. We first analyse the propagation characters of the multipath signals and establish the signal model of targets hiding behind corner for TD-MIMO. Then, a novel multi-target localization algorithm by exploiting the multipath ghosts after applying back-projection (BP) imaging algorithm is proposed. Finally, we illustrate the validation the proposed algorithm via several simulation results.","PeriodicalId":6753,"journal":{"name":"2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"50 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87597260","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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