Eurasip Journal on Advances in Signal Processing最新文献_第3页

Model-based clustering of multipath propagation in powerline communication channels 电力线通信信道中基于模型的多径传播聚类

4区工程技术

Eurasip Journal on Advances in Signal Processing Pub Date : 2023-10-03 DOI: 10.1186/s13634-023-01059-2

Kealeboga L. Mokise, Herman C. Myburgh

{"title":"Model-based clustering of multipath propagation in powerline communication channels","authors":"Kealeboga L. Mokise, Herman C. Myburgh","doi":"10.1186/s13634-023-01059-2","DOIUrl":"https://doi.org/10.1186/s13634-023-01059-2","url":null,"abstract":"Abstract Powerline communication (PLC) channels are known to exhibit multipath propagation behaviour. The authors present a model-based framework to address the challenge of clustering multipath propagation components (MPCs) in PLC channels for indoor low-voltage (LV) environments. The framework employs a range of finite-mixture models (FMMs), including the gamma mixture model, the inverse gamma mixture model, the Gaussian mixture model, the inverse Gaussian mixture model, the Nakagami mixture model, the inverse Nakagami mixture model (INMM) and the Rayleigh mixture model, to identify clusters of MPCs. A measurement campaign of an unknown indoor LV PLC channel is conducted to obtain a channel response. From the channel response, the delay and magnitude parameters of the MPCs are extracted using the space-alternating generalised expectation maximisation algorithm adopted only for these parameters. A maximum likelihood approach and the expectation–maximisation algorithm are employed to fit the FMMs to the MPC delay-magnitude dataset to cluster MPCs in the delay domain. The results of the model-fitting process are then evaluated using the corrected Akaike information criterion (AICc), which enables a fair comparison of the candidate models over the feasible and finite range of clusters. A novel algorithm is introduced for estimating the feasible and finite range of clusters using the extracted delay and magnitude MPC parameters. The AICc’s ranking results show that the INMM model provides the best fit. Davies–Bouldin (DB) and Calinski–Harabasz (CH) indexes are used to compare the model-based clustering approach to the conventional distance-based clustering methods. Validation results show that CH and DB indexes closely agree in the optimal number of MPC clusters for model-based clustering, which corresponds to the most within-cluster compactness of MPCs and to the most between-cluster separation in the delay domain.","PeriodicalId":49203,"journal":{"name":"Eurasip Journal on Advances in Signal Processing","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135739529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Machine learning based low-complexity channel state information estimation 基于机器学习的低复杂度信道状态信息估计

4区工程技术

Eurasip Journal on Advances in Signal Processing Pub Date : 2023-10-01 DOI: 10.1186/s13634-023-00994-4

Juan Meng, Ziping Wei, Yang Zhang, Bin Li, Chenglin Zhao

{"title":"Machine learning based low-complexity channel state information estimation","authors":"Juan Meng, Ziping Wei, Yang Zhang, Bin Li, Chenglin Zhao","doi":"10.1186/s13634-023-00994-4","DOIUrl":"https://doi.org/10.1186/s13634-023-00994-4","url":null,"abstract":"Abstract In 5G communications, the acquisition of accurate channel state information (CSI) is of great importance to the hybrid beamforming of millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) system. In classical mmWave MIMO channel estimation methods, the exploitation of inherent sparse or low-rank structures has demonstrated to improve the performance. However, most high-accurate CSI estimators incur a high computational complexity and require the prior channel information, which hence present the major challenges in the practical deployment. In this work, we leverage machine learning to design the low-complexity and high-performance channel estimator. To be specific, we first formulate the CSI estimation, in the case of sparse structure, as one classical least absolute shrinkage and selection operator problem. In order to reduce the time complexity of existing compressed sensing (CS) methods, we then approximate the original optimization problem to another one, by imposing the other low-rank constraint that was barely considered by CS. We thus solve this new approximated problem and attain the near-optimal solution of the original problem. One new method excludes any prior channel information, and greatly improves the estimation performance, which only incurs a low time complexity. Simulation results demonstrate the superiority of our proposed method both in the estimation accuracy and time complexity.","PeriodicalId":49203,"journal":{"name":"Eurasip Journal on Advances in Signal Processing","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136081122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

UAV-assisted NOMA secure communications: joint transmit power and trajectory optimization 无人机辅助NOMA安全通信:联合发射功率和轨迹优化

4区工程技术

Eurasip Journal on Advances in Signal Processing Pub Date : 2023-09-28 DOI: 10.1186/s13634-023-01056-5

Ruibo Han, Yongjian Wang, Yang Zhang

{"title":"UAV-assisted NOMA secure communications: joint transmit power and trajectory optimization","authors":"Ruibo Han, Yongjian Wang, Yang Zhang","doi":"10.1186/s13634-023-01056-5","DOIUrl":"https://doi.org/10.1186/s13634-023-01056-5","url":null,"abstract":"Abstract With the inherent advantages of exceptional maneuverability, flexible deployment options and cost-effectiveness, unmanned aerial vehicles (UAVs) present themselves as a viable solution for providing aerial communication services to Internet of Things devices in high-traffic or remote areas. Nevertheless, the openness of the air–ground channel poses significant security challenges to UAV-based wireless systems. In this paper, a UAV-assisted secure communication system model is established based on non-orthogonal multiple access (NOMA) from the perspective of physical layer security, aiming to conceal the transmission behavior between UAVs and legitimate users (LUs). Specifically, a mobile UAV assumes the role of an aerial base station, leveraging NOMA technique to transmit data to LUs while evading detection from mobile eavesdropper situated on the ground. To fortify the security performance of the system, a hovering UAV acts as a friendly jammer and transmits interference signals to mobile eavesdropper (referred to as Eve). The objective of this scheme is to maximize the minimum average secure rate of all LUs by meticulously optimizing the trajectory and power allocation of the mobile UAV, subject to secrecy performance constraints. The highly interdependent and non-convex nature of this optimization problem renders direct solutions infeasible. Hence, this paper designs an efficient iterative algorithm that decouples the original problem into two subproblems, enabling an alternating optimization process for the trajectory and power allocation of the mobile UAV until the convergence of the objective function is achieved. Simulation results demonstrate that the proposed algorithm effectively improves the minimum average secure rate of all LUs compared with the benchmark scheme.","PeriodicalId":49203,"journal":{"name":"Eurasip Journal on Advances in Signal Processing","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135386911","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Blind estimation of modulation parameters for PCMA signals using frame cyclic features 基于帧循环特征的PCMA信号调制参数盲估计

4区工程技术

Eurasip Journal on Advances in Signal Processing Pub Date : 2023-09-26 DOI: 10.1186/s13634-023-01055-6

Fang Li, Zhaoyang Qiu, Xiong Zha, Tianyun Li

{"title":"Blind estimation of modulation parameters for PCMA signals using frame cyclic features","authors":"Fang Li, Zhaoyang Qiu, Xiong Zha, Tianyun Li","doi":"10.1186/s13634-023-01055-6","DOIUrl":"https://doi.org/10.1186/s13634-023-01055-6","url":null,"abstract":"Abstract Blind receiver technologies for paired carrier multiple access (PCMA) signals have always been a challenging task with many technical difficulties, among which the estimation of modulation parameters is a fundamental but important element. Despite some achievements in previous studies, more systematic and sophisticated estimation methods have not been adequately investigated. In this paper, schemes for the blind estimation of the symbol timing phase, amplitude attenuation, frequency offset, and carrier phase for PCMA signals in satellite communications are proposed. The data flow transmitted in satellite communication often has a certain frame structure, the most important of which is the synchronization data, namely the so-called cycle features. The proposed schemes assume that the modulated signals have fixed frame length and frame sync code and that the symbol rate has been estimated when the signals are encoded asynchronously. Distinct from the previous methods, our schemes exploit the sync waveform and the overlapping waveform, which are estimated via singular value decomposition (SVD) (using the frame cyclic features) and interference cancelation, together with their demodulation results as aid data, for the estimation of the desired parameters. The simulation results demonstrate that the schemes are effective in the parameters estimation of PCMA signals and outperform the comparison algorithms.","PeriodicalId":49203,"journal":{"name":"Eurasip Journal on Advances in Signal Processing","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134960833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Modeling and analysis for group delay mismatch effect on wideband adaptive spatial interference cancellation 宽带自适应空间干扰消除中的群延迟失配效应建模与分析

4区工程技术

Eurasip Journal on Advances in Signal Processing Pub Date : 2023-09-26 DOI: 10.1186/s13634-023-01058-3

Yunshuo Zhang, Fangmin He, Hongbo Liu, Yaxing Li, Zhong Yang, Ze Wang, Jin Meng

{"title":"Modeling and analysis for group delay mismatch effect on wideband adaptive spatial interference cancellation","authors":"Yunshuo Zhang, Fangmin He, Hongbo Liu, Yaxing Li, Zhong Yang, Ze Wang, Jin Meng","doi":"10.1186/s13634-023-01058-3","DOIUrl":"https://doi.org/10.1186/s13634-023-01058-3","url":null,"abstract":"Abstract The adaptive interference cancellation technique has been widely utilized in radar, GPS, data link, etc., systems to address challenges from external interference, such as co-site and hostile interference. Since the anti-jamming performance of the adaptive interference cancellation technique is sensitive to group delay mismatch between channels, the group delay mismatch becomes one of the main factors that limit the system’s anti-jamming capability. However, the traditional adaptive interference cancellation system’s mathematical model cannot quantitatively characterize the group delay mismatch effect on the wideband interference cancellation performance. In this paper, the mathematical model of the wideband adaptive spatial interference cancellation (ASIC) system is established, which considers the group delay mismatch, to quantitatively analyze the impact of group delay mismatch on the hostile interference cancellation. The mathematical model utilizes the weighted multi-tone signals to fit the wideband interference, and then, delay differences are attached to each tone signal to simulate the group delay mismatch. Then, the analytic expressions of weight and interference cancellation ratio are derived, which consider the interference bandwidth and group delay mismatch, to quantitatively analyze the group delay mismatch effect on the anti-jamming performance of the wideband ASIC system. Simulation results indicate that the theoretical analysis based on the mathematical model of wideband ASIC system are accurate, which can achieve the quantitative analysis of the group delay mismatch effect on the WIC performance.","PeriodicalId":49203,"journal":{"name":"Eurasip Journal on Advances in Signal Processing","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134885320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Deep adaptive temporal network (DAT-Net): an effective deep learning model for parameter estimation of radar multipath interference signals 深度自适应时间网络(DAT-Net):一种有效的雷达多径干扰信号参数估计的深度学习模型

4区工程技术

Eurasip Journal on Advances in Signal Processing Pub Date : 2023-09-25 DOI: 10.1186/s13634-023-01053-8

Kang Yan, Weidong Jin, Yingkun Huang, Pucha Song, Zhenhua Li

{"title":"Deep adaptive temporal network (DAT-Net): an effective deep learning model for parameter estimation of radar multipath interference signals","authors":"Kang Yan, Weidong Jin, Yingkun Huang, Pucha Song, Zhenhua Li","doi":"10.1186/s13634-023-01053-8","DOIUrl":"https://doi.org/10.1186/s13634-023-01053-8","url":null,"abstract":"Abstract Accurate parameter estimation in radar systems is critically hindered by multipath interference, a challenge that is amplified in complex and dynamic environments. Traditional methods for parameter estimation, which concentrate on single parameters and rely on statistical assumptions, often struggle in such scenarios. To address this, the deep adaptive temporal network (DAT-Net), an innovative deep learning model designed to handle the inherent complexities and non-stationarity of time series data, is proposed. In more detail, DAT-Net integrates both the pruned exact linear time method for effective time series segmentation and the exponential scaling-based importance evaluation algorithm for dynamic learning of importance weights. These methods enable the model to adapt to shifts in data distribution and provide a robust solution for parameter estimation. In addition, DAT-Net demonstrates the capability to comprehend inherent nonlinearities in radar multipath interference signals, thereby facilitating the modeling of intricate patterns within the data. Extensive validation experiments conducted across parameter estimation tasks and demonstrates the robust applicability and efficiency of the proposed DAT-Net model. The architecture yield root mean squared error scores as low as 0.0051 for single-parameter estimation and 0.0152 for multiple-parameter estimation.","PeriodicalId":49203,"journal":{"name":"Eurasip Journal on Advances in Signal Processing","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135768442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Estimation of LFM signal parameters using RD compressed sampling and the DFRFT dictionary 用RD压缩采样和DFRFT字典估计LFM信号参数

4区工程技术

Eurasip Journal on Advances in Signal Processing Pub Date : 2023-09-23 DOI: 10.1186/s13634-023-01057-4

Shuo Meng, Chen Meng, Cheng Wang

{"title":"Estimation of LFM signal parameters using RD compressed sampling and the DFRFT dictionary","authors":"Shuo Meng, Chen Meng, Cheng Wang","doi":"10.1186/s13634-023-01057-4","DOIUrl":"https://doi.org/10.1186/s13634-023-01057-4","url":null,"abstract":"Abstract In this paper, a method combining random demodulator (RD) and discrete fractional Fourier transform (DFRFT) dictionary is suggested to directly estimate the parameters of linear frequency modulation (LFM) signals from compressed sampling data. First, the RD system parameters are modified in accordance with the characteristics of the LFM signal to produce effective compressed sampling data. Next, a DFRFT dictionary is built using the fractional Fourier transform theory, and sparse representation coefficients are obtained by reconstructing the compressed sampling data using the recovery algorithm and DFRFT dictionary. The signal exhibits characteristics that make it pulse under the best fractional transform order, so the problem of signal parameter estimation can be reduced to searching for the location of the maximum value of sparse representation coefficients. The location is determined by a parameter optimization algorithm, and from there, the initial frequency and Chirp rate of the LFM signal can be estimated. Lastly, simulation and real data tests are performed to confirm that the suggested method can directly be utilized to estimate the parameter of LFM signals using compressed sampling data in addition to having high sparse representation ability for LFM signals.","PeriodicalId":49203,"journal":{"name":"Eurasip Journal on Advances in Signal Processing","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135961396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Correction: Quantization-aware sampling set selection for bandlimited graph signals 修正:量化感知采样集选择带宽有限的图形信号

4区工程技术

Eurasip Journal on Advances in Signal Processing Pub Date : 2023-01-19 DOI: 10.1186/s13634-022-00946-4

Yoon Hak Kim

引用次数: 1

A smartphone-based zero-effort method for mitigating epidemic propagation. 一种基于智能手机的零努力方法，用于缓解流行病传播。

IF 1.7 4区工程技术

Eurasip Journal on Advances in Signal Processing Pub Date : 2023-01-01 Epub Date: 2023-02-01 DOI: 10.1186/s13634-023-00984-6

Qu Wang, Meixia Fu, Jianquan Wang, Lei Sun, Rong Huang, Xianda Li, Zhuqing Jiang

{"title":"A smartphone-based zero-effort method for mitigating epidemic propagation.","authors":"Qu Wang, Meixia Fu, Jianquan Wang, Lei Sun, Rong Huang, Xianda Li, Zhuqing Jiang","doi":"10.1186/s13634-023-00984-6","DOIUrl":"10.1186/s13634-023-00984-6","url":null,"abstract":"A large number of epidemics, including COVID-19 and SARS, quickly swept the world and claimed the precious lives of large numbers of people. Due to the concealment and rapid spread of the virus, it is difficult to track down individuals with mild or asymptomatic symptoms with limited human resources. Building a low-cost and real-time epidemic early warning system to identify individuals who have been in contact with infected individuals and determine whether they need to be quarantined is an effective means to mitigate the spread of the epidemic. In this paper, we propose a smartphone-based zero-effort epidemic warning method for mitigating epidemic propagation. Firstly, we recognize epidemic-related voice activity relevant to epidemics spread by hierarchical attention mechanism and temporal convolutional network. Subsequently, we estimate the social distance between users through sensors built-in smartphone. Furthermore, we combine Wi-Fi network logs and social distance to comprehensively judge whether there is spatiotemporal contact between users and determine the duration of contact. Finally, we estimate infection risk based on epidemic-related vocal activity, social distance, and contact time. We conduct a large number of well-designed experiments in typical scenarios to fully verify the proposed method. The proposed method does not rely on any additional infrastructure and historical training data, which is conducive to integration with epidemic prevention and control systems and large-scale applications.","PeriodicalId":49203,"journal":{"name":"Eurasip Journal on Advances in Signal Processing","volume":"2023 1","pages":"18"},"PeriodicalIF":1.7,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9891762/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10668196","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A deep adversarial model for segmentation-assisted COVID-19 diagnosis using CT images. 利用 CT 图像进行分割辅助 COVID-19 诊断的深度对抗模型。

IF 1.7 4区工程技术

Eurasip Journal on Advances in Signal Processing Pub Date : 2022-01-01 Epub Date: 2022-02-10 DOI: 10.1186/s13634-022-00842-x

Hai-Yan Yao, Wang-Gen Wan, Xiang Li

{"title":"A deep adversarial model for segmentation-assisted COVID-19 diagnosis using CT images.","authors":"Hai-Yan Yao, Wang-Gen Wan, Xiang Li","doi":"10.1186/s13634-022-00842-x","DOIUrl":"10.1186/s13634-022-00842-x","url":null,"abstract":"The outbreak of coronavirus disease 2019 (COVID-19) is spreading rapidly around the world, resulting in a global pandemic. Imaging techniques such as computed tomography (CT) play an essential role in the diagnosis and treatment of the disease since lung infection or pneumonia is a common complication. However, training a deep network to learn how to diagnose COVID-19 rapidly and accurately in CT images and segment the infected regions like a radiologist is challenging. Since the infectious area is difficult to distinguish manually annotation, the segmentation results are time-consuming. To tackle these problems, we propose an efficient method based on a deep adversarial network to segment the infection regions automatically. Then, the predicted segment results can assist the diagnostic network in identifying the COVID-19 samples from the CT images. On the other hand, a radiologist-like segmentation network provides detailed information of the infectious regions by separating areas of ground-glass, consolidation, and pleural effusion, respectively. Our method can accurately predict the COVID-19 infectious probability and provide lesion regions in CT images with limited training data. Additionally, we have established a public dataset for multitask learning. Extensive experiments on diagnosis and segmentation show superior performance over state-of-the-art methods.","PeriodicalId":49203,"journal":{"name":"Eurasip Journal on Advances in Signal Processing","volume":"2022 1","pages":"10"},"PeriodicalIF":1.7,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8830991/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39807491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0