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Found 29 papers, 2 papers with code
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 THz Channel Modeling for Indoor Office and Urban Microcellular Scenarios
Generally, these results are helpful to understand and model the THz channel and apply the THz communication technique for 6G.
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 Joint Communication and Sensing Systems
Then, a stochastic JCAS channel model is proposed to capture the sharing feature, where shared and non-shared clusters by the two channels are defined 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.
