Secure MIMO NOMA transmission with energy harvesting-aided full-duplex jammer under erroneous channel information
NOMA allows for the simultaneous transmission of multiple user signals and full-duplex (FD) communication enables concurrent transmit-and-receive operations, both improving spectral efficiency. Additionally, NOMA networks utilize energy ...
A Fast Total-Variation Driven Network for Sparse Aperture ISAR Imaging
Conventional Fourier transform-based Inverse Synthetic Aperture Radar (ISAR) imaging cannot deal with the cases of incomplete radar echoes, in which the data needs to be specially processed by Sparse Aperture (SA) imaging methods. Most current SA-...
Power quality disturbances classification with imbalanced/insufficient samples based on WGAN-GP-SA and DCNN
The accurate identification of power quality disturbance signals (PQDs) is of great importance to ensure the safe and stable operation of power systems. Considering that there are insufficient samples and imbalance samples of power quality ...
Semi-supervised few-shot fault diagnosis driven by multi-head dynamic graph attention network under speed fluctuations
- By constructing the k-nearest neighbor graph (KNNG) measured through dynamic time warping (DTW), we can partially address the challenge of local time offset in signals induced by fluctuations in machine speed. This approach contributes to ...
Although graph neural networks (GNNs) have achieved great success in the field of semi-supervised bearing fault diagnosis recently, most GNN-based studies still face the challenge of insufficient labeled samples. Meanwhile, the signals collected ...
Enhancing CNN efficiency through mutual information-based filter pruning
This study presents RRWFP, a novel filter pruning technique for convolutional neural networks (CNNs) designed to improve their deployment on resource-constrained devices. Relevance–Redundancy Filter-Level Weights Pruning (RRWFP) utilises mutual ...
Parallel feature enhancement and adaptive weighted feature fusion for semantic segmentation
To tackle the challenges posed by the insensitivity of current multi-scale networks to image detailed information and their limited capacity to model contextual relationships, our paper proposes a novel semantic segmentation network called ...
Deep embedding based tensor incomplete multi-view clustering
The majority of multi-view data are extracted from real life, which often lose information in some views. To solve this problem, existing incomplete multi-view clustering algorithms explore the valuable information from incomplete data while ...
Application of optimized sparse encoding algorithm in data compression
Data transmission is crucial in the process of equipment monitoring. The compression algorithms are adopted to reduce the amount of data transmission. When sparse encoding algorithms are used for this purpose, despite extensive attempts to ...
Frame-wise speech extraction with recursive expectation maximization for partially deformable microphone arrays
Large-apertured wearable and deformable microphone arrays have shown their better performance than conventional small wearable and rigid microphone arrays for speech extraction tasks, especially when the desired speech is far away from the arrays ...
Identification and distributed fusion filter for multi-sensor networked systems with stochastic deception attacks
In the multi-sensor networked systems, each sensor produces its local state estimate based on its own observations, and then sends it to a fusion center (FC) for fusion estimation. During transmitting local state estimates to the fusion center, ...
TDOA-based UWB indoor 1D localization via weighted sliding window filtering
Accurate localization of a person or object is a significant aspect in the field of industrial internet of things (IoT). Ultra-wideband (UWB) localization system, a promising technology, has been widely studied due to its high accuracy in 2D and ...
Research on moving object tracking with a large number of outliers based on TRESAC++ algorithm
In contrast to the method based on motion equations, image registration proves effective for tracking moving objects in missions where establishing a motion model is unfeasible. However, in cases where the object is captured at varying imaging ...
A Laplace operator-based active contour model with improved image edge detection performance
Active contour model (ACM) is an important branch in the field of image segmentation, since it adapts to different image types and scenes. However, traditional ACMs rely on local image information, which makes them sensitive to initial contours ...
Conditional generative model with skip-connection structure for low-light image enhancement
Vision-guided coal mine robots often encounter challenges in low-light environments, capturing images marked by poor visibility and significant loss of detail, which complicates the advancement of smart mine safety production. Despite various ...
Enhancing data rate and energy efficiency of NOMA systems using reconfigurable intelligent surfaces for millimeter-wave communications
- Xuan Nghia Pham,
- Ba Cao Nguyen,
- Tam Dinh Thi,
- Nguyen Van Vinh,
- Bui Vu Minh,
- Taejoon Kim,
- Tan N. Nguyen,
- Anh Vu Le
In this article, we employ reconfigurable intelligent surface (RIS) to aid a non-orthogonal multiple access (NOMA) system utilizing millimeter-wave (mmWave) communications. Different to recent works on the RIS-supported NOMA systems where the ...
GD-YOLO: An improved convolutional neural network architecture for real-time detection of smoking and phone use behaviors
Chemical safety accidents cause significant socio-economic and environmental hazards, and safety accidents caused by unsafe worker behaviors are preventable. Detection of workers' smoking and phone use behaviors in chemical parks can avoid such ...
Unsupervised domain adaptation for the semantic segmentation of remote sensing images via a class-aware Fourier transform and a fine-grained discriminator
The semantic segmentation of remote sensing images is vital for Earth observation purposes. However, its performance can decline significantly due to differences in dataset distributions between training (source) and deployment (target) settings. ...
Mean squared error bound for learning-based multi-target localization and its application in learning network architecture design
The learning-based method has been widely applied in target localization. However, the performance of learning-based localization is mostly validated by simulation experiments and lacks theoretical analysis. In this paper, we investigate the ...
A compressed 2D-DOA and polarization estimation algorithm for mmWave polarized massive MIMO systems
Due to providing greater degrees-of-freedom (DOFs) and securer communication guarantees than traditional scalar array, polarized massive multiple-input multiple-output (MIMO) technique offers a prospective insight into millimeter-wave (mmWave) ...
Graphical abstract Highlights
- A synchronous compressive network is combined with propagator to compress high-dimensional data and avoid matrix decomposition.
- A coarse-refined strategy using rotational invariance and RDMUSIC is explored for accurate 2D-DOA and ...
Secrecy outage analysis for RIS-assisted hybrid FSO-RF systems with NOMA
In this paper, we investigate the physical-layer security performance for a reconfigurable intelligent surface (RIS) assisted free-space optical (FSO) communication-radio frequency (RF) system with non-orthogonal multiple access (NOMA). In ...
Rhythm-adaptive statistical estimation methods of probabilistic characteristics of cyclic random processes
The paper is devoted to the rhythm-adaptive statistical estimation methods of cyclic random processes probabilistic characteristics. The main goal of the article is development and research of rhythm-adaptive methods of cyclic random processes ...
Motion-guided large aperture ULA to enhance DOA estimation: An inverse synthetic aperture perspective
Direction-of-arrival (DOA) estimation is a critical issue in array signal processing, especially in radar applications. However, the array aperture of high-frequency radars is constrained by the site and platform, which in turn leads to limited ...
Graphical abstract Highlights
- Inspired by the inverse synthetic aperture, a trading time for space framework is developed to enhance DOA estimation.
- The array aperture is extended by the relative motion between radar and target. Its key condition is proper data ...
VCAFusion: An infrared and visible image fusion network with visual perception and cross-scale attention
Infrared and visible image fusion methods aim to combine salient target instances and abundant texture details into fused images. However, due to the interference of harsh conditions, such as dense smoke, fog, and intense light, it is feasible ...
Predicted position-driven deep learning channel estimation for massive MIMO systems
Multiple-input multiple-output (MIMO) can significantly improve the energy efficiency and spectral efficiency of wireless communication systems, and obtaining accurate channel state information is a key prerequisite. However, traditional channel ...
Unsupervised recognition of radar signals combining multi-block TFR with subspace clustering
In the realm of radar systems, the proliferation of new modulation techniques introduces an increased level of complexity in the identification of both existing and potentially novel modulation schemes. Conventional supervised recognition ...
Recovery of bandlimited graph signals based on the reproducing kernel Hilbert space
Signal recovery on graphs is attracting more and more attentions. Based on the smoothness assumption, the signal recovery problem can be formulated as an unconstrained optimization model. Although the model can be solved analytically, the ...
An enhanced direct position determination of non-circular sources via sparse Bayesian inference and grid refinement strategy
In this study, an off-grid sparse Bayesian inference (OGSBI) based direct position determination (DPD) algorithm is investigated. Existing SBI-based DPD algorithms are confronted with the challenge of excessive computational loads and lack of ...
Highlights
- Enhance the localization accuracy by exploiting the property of non-circular signals.
- A grid refinement strategy for direct position determination is introduced to reduce the complexity.
- Off grid sparse Bayesian inference based ...
Bandit approach for unmanned aerial vehicle-centric low earth orbit satellite selection
In this paper, the problem of optimal low earth orbit satellite (LEO-Sat) selection by unmanned aerial vehicle (UAV) in space air ground integrated networks (SAGINs) will be investigated. The primary objective is to maximize the UAV's achievable ...
Construction of type-II ZCCS for the MC-CDMA system with low PMEPR
This paper introduces a novel construction method for Type-II Z complementary code set (ZCCS) based on the Kronecker product between complete complementary code and mutually orthogonal sequences. Type-II ZCCS offer significant advantages over ...