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Found 58 papers, 6 papers with code
SMPR: A structure-enhanced multimodal drug-disease prediction model for drug repositioning and cold start
Furthermore, most repositioning models are only used to complete the relationship matrix, and their practicality is poor when dealing with drug cold start problems.
A Novel Environment Object Modeling Method for Vehicular ISAC Scenarios
Existing research indicates that NLOS paths, characterized by one-bounce reflection on building walls with determined delay and angle, can support sensing and positioning.
A Brain-Inspired Perception-Decision Driving Model Based on Neural Pathway Anatomical Alignment
In the realm of autonomous driving, conventional approaches for vehicle perception and decision-making primarily rely on sensor input and rule-based algorithms.
BAN: Neuroanatomical Aligning in Auditory Recognition between Artificial Neural Network and Human Cortex
In conclusion, this study presents BAN as a recurrent, brain-inspired ANN, representing the first model that mirrors the cortical pathway of auditory recognition.
Road to 6G Digital Twin Networks: Multi-Task Adaptive Ray-Tracing as a Key Enabler
As a virtual, synchronized replica of physical network, the digital twin network (DTN) is envisioned to sense, predict, optimize and manage the intricate wireless technologies and architectures brought by 6G.
MATCNN: Infrared and Visible Image Fusion Method Based on Multi-scale CNN with Attention Transformer
While attention-based approaches have shown considerable progress in enhancing image fusion and addressing the challenges posed by long-range feature dependencies, their efficacy in capturing local features is compromised by the lack of diverse receptive field extraction techniques.
A Survey on IBR Penetrated Power System Stability Analysis Using Frequency Scanning
The rapid rise in inverter-based renewable resources has heightened concerns over subsynchronous resonance and oscillations, thereby challenging grid stability.
Preventive Energy Management for Distribution Systems Under Uncertain Events: A Deep Reinforcement Learning Approach
Consequently, to enhance system resiliency, it is essential to account for various uncertain events when implementing the optimization problem for the energy management system (EMS).
Overview of AI and Communication for 6G Network: Fundamentals, Challenges, and Future Research Opportunities
The first stage, AI for Network, focuses on employing AI to augment network performance, optimize efficiency, and enhance user service experiences.
Can Students Beyond The Teacher? Distilling Knowledge from Teacher's Bias
To address this issue, we propose a novel strategy to rectify bias and greatly improve the student model's performance.
Experimental Analysis and Modeling of Penetration Loss for Building Materials in FR1 and FR3 bands
This study focuses on analysis and modeling of the penetration loss of typical building materials in the FR1 (450 MHz-6 GHz) and FR3 (7-24 GHz) bands based on experimental measurements.
New Characteristics and Modeling of 6G Channels: A Unified Channel Model towards Standardization
As 6G research advances, the growing demand leads to the emergence of novel technologies such as Integrated Sensing and Communication (ISAC), new antenna arrays like Extremely Large MIMO (XL-MIMO) and Reconfigurable Intelligent Surfaces (RIS), along with multi-frequency bands (6-24 GHz, above 100 GHz).
Multi-Modal Environmental Sensing Based Path Loss Prediction for V2I Communications
The stability and reliability of wireless data transmission in vehicular networks face significant challenges due to the high dynamics of path loss caused by the complexity of rapidly changing environments.
Environment Reconstruction with Multi-targets Reflectors-merged Sensing Method Based on THz Single-sided Channel Characteristics
Reconstructing the propagation environment is a vital step for THz ISAC, as it enhances the predictability of the communication channel to reduce communication overhead.
Deep Reinforcement Learning for Optimizing Inverter Control: Fixed and Adaptive Gain Tuning Strategies for Power System Stability
This paper presents novel methods for tuning inverter controller gains using deep reinforcement learning (DRL).
ChannelGPT: A Large Model to Generate Digital Twin Channel for 6G Environment Intelligence
In practice, we also establish a ChannelGPT prototype to generate high-fidelity channel data for varied scenarios to validate the accuracy and generalization ability based on environment intelligence.
Corrections to "Computer Vision Aided mmWave Beam Alignment in V2X Communications"
Then, we revise the simulation results of Fig.
Wireless Environment Information Sensing, Feature, Semantic, and Knowledge: Four Steps Towards 6G AI-Enabled Air Interface
The air interface technology plays a crucial role in optimizing the communication quality for users.
BUPTCMCC-6G-CMG+: A GBSM-Based ISAC Standard Channel Model Generator
Integrated sensing and communication (ISAC) has been recognized as the key technology in the vision of the sixth generation (6G) era.
Recurrent Graph Transformer Network for Multiple Fault Localization in Naval Shipboard Systems
The integration of power electronics building blocks in modern MVDC 12kV Naval ship systems enhances energy management and functionality but also introduces complex fault detection and control challenges.
Clutter Suppression, Time-Frequency Synchronization, and Sensing Parameter Association in Asynchronous Perceptive Vehicular Networks
To overcome these challenges, 1) we introduce a moving target indication based joint clutter suppression and sensing algorithm, and analyze its clutter-suppression performance and the Cramer-Rao lower bound of the paired range-velocity estimation upon using the proposed clutter suppression algorithm; 2) we design algorithms for associating individual direction-of-arrival estimates with the paired range-velocity estimates based on "domain transformation"; 3) we propose the first viable carrier frequency offset (CFO) and time offset (TO) estimation algorithm that supports passive vehicular sensing in non-line-of-sight environments.
Can Wireless Environmental Information Decrease Pilot Overhead: A CSI Prediction Example
Finally, a CNN-based channel prediction network is designed to predict the complete CSI, using the environmental feature map and partial CSI.
Large-vocabulary forensic pathological analyses via prototypical cross-modal contrastive learning
Forensic pathology is critical in determining the cause and manner of death through post-mortem examinations, both macroscopic and microscopic.
An Approximate Wave-Number Domain Expression for Near-Field XL-array Channel
Moreover, its performance surpasses that of existing DFT codebook-based beam training methods.
Learning to Adapt Foundation Model DINOv2 for Capsule Endoscopy Diagnosis
Our method, inspired by the DINOv2 foundation model, applies low-rank adaptation learning to tailor foundation models for capsule endoscopy diagnosis effectively.
Electromagnetic Wave Property Inspired Radio Environment Knowledge Construction and AI-based Verification for 6G Digital Twin Channel
Since radio propagation is affected by the environment, constructing the relationship between the environment and radio wave propagation is the key to improving the accuracy of DTC, and the construction method based on artificial intelligence (AI) is the most concentrated.
Near-Field Channel Characterization for Mid-band ELAA Systems: Sounding, Parameter Estimation, and Modeling
To this end, this work develops a channel sounder dedicated to mid-band ELAA systems based on a distributed modular vector network analyzer incorporating radio-over-fiber (RoF), phase compensation, and virtual antenna array schemes.
An Enhanced Dynamic Ray Tracing Architecture for Channel Prediction Based on Multipath Bidirectional Geometry and Field Extrapolation
Interestingly, a dynamic ray tracing (DRT) approach for channel prediction has recently been proposed, which utilizes the results of traditional RT to extrapolate the multipath geometry evolution.
AdaFSNet: Time Series Classification Based on Convolutional Network with a Adaptive and Effective Kernel Size Configuration
Our model surpassed baseline models in terms of classification accuracy, underscoring the AdaFSNet network's efficiency and effectiveness in handling time series classification tasks.
Digital Twin Channel for 6G: Concepts, Architectures and Potential Applications
Digital twin channel (DTC) is the real-time mapping of a wireless channel from the physical world to the digital world, which is expected to provide significant performance enhancements for the sixth-generation (6G) air-interface design.
Joint Sparsity Pattern Learning Based Channel Estimation for Massive MIMO-OTFS Systems
We propose a channel estimation scheme based on joint sparsity pattern learning (JSPL) for massive multi-input multi-output (MIMO) orthogonal time-frequency-space (OTFS) modulation aided systems.
360ORB-SLAM: A Visual SLAM System for Panoramic Images with Depth Completion Network
To enhance the performance and effect of AR/VR applications and visual assistance and inspection systems, visual simultaneous localization and mapping (vSLAM) is a fundamental task in computer vision and robotics.
Physics-informed Graphical Neural Network for Power System State Estimation
State estimation is highly critical for accurately observing the dynamic behavior of the power grids and minimizing risks from cyber threats.
Towards 6G Digital Twin Channel Using Radio Environment Knowledge Pool
The digital twin channel (DTC) is crucial for 6G wireless autonomous networks as it replicates the wireless channel fading states in 6G air interface transmissions.
How to Extend 3D GBSM to Integrated Sensing and Communication Channel with Sharing Feature?
The proposed approach can be summarized as follows: Firstly, an ISAC channel model is proposed, where shared and non-shared components are superimposed for both communication and sensing.
SCVCNet: Sliding cross-vector convolution network for cross-task and inter-individual-set EEG-based cognitive workload recognition
This paper presents a generic approach for applying the cognitive workload recognizer by exploiting common electroencephalogram (EEG) patterns across different human-machine tasks and individual sets.
A Hybrid Optimization and Deep Learning Algorithm for Cyber-resilient DER Control
To this end, a hybrid feedback-based optimization algorithm along with deep learning forecasting technique is proposed to specifically address the cyber-related issues.
DataAI-6G: A System Parameters Configurable Channel Dataset for AI-6G Research
A common and accurate dataset is essential for the research of AI communication.
Channel Measurement, Modeling, and Simulation for 6G: A Survey and Tutorial
Then, a survey of the progress of the 6G channel research regarding the above five promising technologies is presented in terms of the latest measurement campaigns, new characteristics, modeling methods, and research prospects.
3GPP-Like GBSM THz Channel Characterization, Modeling, and Simulation Based on Experimental Observations
Finally, we propose the THz channel model and its simulation framework to reconstruct CIRs based on the obtained models, which aim at characterizing the sparser THz channels.
Lightweight Machine Learning for Digital Cross-Link Interference Cancellation with RF Chain Characteristics in Flexible Duplex MIMO Systems
The flexible duplex (FD) technique, including dynamic time-division duplex (D-TDD) and dynamic frequency-division duplex (D-FDD), is regarded as a promising solution to achieving a more flexible uplink/downlink transmission in 5G-Advanced or 6G mobile communication systems.
Channel Sparsity Variation and Model-Based Analysis on 6, 26, and 132 GHz Measurements
In addition, a new intra-cluster power allocation model based on measurements is proposed to characterize the effects of sparsity in the delay domain of the 3GPP channel model.
How to Extend 3D GBSM to RIS Cascade Channel with Non-ideal Phase Modulation?
In the modeling process, we consider the non-ideal phase modulation of the RIS element, so as to accurately characterize the dependence of its phase modulation on the incoming wave angle.
Capacity Analysis of Holographic MIMO Channels with Practical Constraints
However, the channel might not satisfy isotropic scattering because of generalized angle distributions, and the antenna gain is limited by the array aperture in reality.
A Shared Cluster-based Stochastic Channel Model for Integrated Sensing and Communication Systems
Then, a stochastic ISAC channel model is proposed to capture the sharing feature, where shared and non-shared clusters by the two channels are dfined and superimposed.
How to Define the Propagation Environment Semantics and Its Application in Scatterer-Based Beam Prediction
Inspired by task-oriented semantic communication and machine learning (ML) powered environment-channel mapping methods, this work aims to provide a new view of the environment from the semantic level, which defines the propagation environment semantics (PES) as a limited set of propagation environment semantic symbols (PESS) for diverse application tasks.
Semantic Visual Simultaneous Localization and Mapping: A Survey
Numerous publications have reported that, by combining with the semantic information with vSLAM, the semantic vSLAM systems have the capability of solving the above problems in recent years.
DRL Enabled Coverage and Capacity Optimization in STAR-RIS Assisted Networks
Moreover, in order to improve the performance of the MO-PPO algorithm, two update strategies, i. e., action-value-based update strategy (AVUS) and loss function-based update strategy (LFUS), are investigated.
Computer Vision Aided mmWave Beam Alignment in V2X Communications
Visual information, captured for example by cameras, can effectively reflect the sizes and locations of the environmental scattering objects, and thereby can be used to infer communications parameters like propagation directions, receiver powers, as well as the blockage status.
Frequency-Angle Two-Dimensional Reflection Coefficient Modeling Based on Terahertz Channel Measurement
In this letter, the reflection coefficient of the THz channel is researched based on extensive measurement campaigns.
Adversarial Training-Aided Time-Varying Channel Prediction for TDD/FDD Systems
In this paper, a time-varying channel prediction method based on conditional generative adversarial network (CPcGAN) is proposed for time division duplexing/frequency division duplexing (TDD/FDD) systems.
Collaborative Visual Inertial SLAM for Multiple Smart Phones
Each agent can independently explore the environment, run a visual-inertial odometry module online, and then send all the measurement information to a central server with higher computing resources.
Identification of mental fatigue in language comprehension tasks based on EEG and deep learning
The combination of Frequency and entropy feature and CNN has the highest classification accuracy, which is 85. 34%.
Deep Learning Based Channel Covariance Matrix Estimation with User Location and Scene Images
Channel covariance matrix (CCM) is one critical parameter for designing the communications systems.
Accurate Object Association and Pose Updating for Semantic SLAM
The key to solving this problem is to correctly associate multiple object measurements of one object landmark, and refine the pose of object landmark.
Consistency-Aware Graph Network for Human Interaction Understanding
Compared with the progress made on human activity classification, much less success has been achieved on human interaction understanding (HIU).
A general representation of dynamical systems for reservoir computing
The advantages of such implementation are its usage on specialized and optimized deep learning libraries, the capabilities to generalize it to other types of networks and the possibility to evolve cellular automata and other dynamical systems in terms of connectivity, update and learning rules.
Deep Learning for Physical-Layer 5G Wireless Techniques: Opportunities, Challenges and Solutions
The new demands for high-reliability and ultra-high capacity wireless communication have led to extensive research into 5G communications.
