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Found 38 papers, 2 papers with code
Learning Wireless Data Knowledge Graph for Green Intelligent Communications: Methodology and Experiments
In this paper, we propose a solution, termed the pervasive multi-level (PML) native AI architecture, which integrates the concept of knowledge graph (KG) into the intelligent operational manipulations of mobile networks, resulting in the establishment of a wireless data KG.
Exploit High-Dimensional RIS Information to Localization: What Is the Impact of Faulty Element?
Then our objective is to regain the information lost from the faulty elements and reconstruct the complete high-dimensional RIS information for localization.
Large Generative Model Assisted 3D Semantic Communication
Semantic Communication (SC) is a novel paradigm for data transmission in 6G.
Target Localization and Performance Trade-Offs in Cooperative ISAC Systems: A Scheme Based on 5G NR OFDM Signals
Specifically, we propose a two-stage scheme for target localization, where communication signals are reused as sensing reference signals based on the system information shared at the central processing unit (CPU).
Digital versus Analog Transmissions for Federated Learning over Wireless Networks
In this paper, we quantitatively compare these two effective communication schemes, i. e., digital and analog ones, for wireless federated learning (FL) over resource-constrained networks, highlighting their essential differences as well as their respective application scenarios.
Lightweight Deep Learning Based Channel Estimation for Extremely Large-Scale Massive MIMO Systems
Extremely large-scale massive multiple-input multiple-output (XL-MIMO) systems introduce the much higher channel dimensionality and incur the additional near-field propagation effect, aggravating the computation load and the difficulty to acquire the prior knowledge for channel estimation.
Wireless Network Digital Twin for 6G: Generative AI as A Key Enabler
Digital twin, which enables emulation, evaluation, and optimization of physical entities through synchronized digital replicas, has gained increasingly attention as a promising technology for intricate wireless networks.
Digital Twin-Enhanced Deep Reinforcement Learning for Resource Management in Networks Slicing
In this paper, a framework consisting of a digital twin and reinforcement learning agents is present to handle the issue.
Passive Integrated Sensing and Communication Scheme based on RF Fingerprint Information Extraction for Cell-Free RAN
This paper investigates how to achieve integrated sensing and communication (ISAC) based on a cell-free radio access network (CF-RAN) architecture with a minimum footprint of communication resources.
Digital Twin Assisted Deep Reinforcement Learning for Online Admission Control in Sliced Network
The proliferation of diverse wireless services in 5G and beyond has led to the emergence of network slicing technologies.
Large AI Model Empowered Multimodal Semantic Communications
To this end, we propose a Large AI Model-based Multimodal SC (LAM-MSC) framework, in which we first present the MLM-based Multimodal Alignment (MMA) that utilizes the MLM to enable the transformation between multimodal and unimodal data while preserving semantic consistency.
Large AI Model-Based Semantic Communications
Semantic communication (SC) is an emerging intelligent paradigm, offering solutions for various future applications like metaverse, mixed-reality, and the Internet of everything.
Joint Uplink and Downlink Resource Allocation Towards Energy-efficient Transmission for URLLC
With the proposed packet delivery mechanism, we jointly optimize bandwidth allocation and power control of uplink and downlink, antenna configuration, and subchannel assignment to minimize the average total power under the constraint of URLLC transmission requirements.
Self-information Domain-based Neural CSI Compression with Feature Coupling
The proposed SD-CsiNet projects the raw CSI onto a self-information matrix in the newly-defined self-information domain, extracts both temporal and spatial features of the self-information matrix, and then couples these two features for effective compression.
Performance Analysis and Low-Complexity Design for XL-MIMO with Near-Field Spatial Non-Stationarities
Our analytical results indicate that a limited part of the XL-array receives the majority of the signal power in the near field, which leads to a notion of visibility region (VR) of a user.
On the Road to 6G: Visions, Requirements, Key Technologies and Testbeds
A series of white papers and survey papers have been published, which aim to define 6G in terms of requirements, application scenarios, key technologies, etc.
Deep Learning-Based Modeling of 5G Core Control Plane for 5G Network Digital Twin
However, the intricate structure and diverse functionalities of the existing 5G core network, especially the control plane, present challenges in constructing core network digital twins.
Link-level simulator for 5G localization
Channel-state-information-based localization in 5G networks has been a promising way to obtain highly accurate positions compared to previous communication networks.
Two-Timescale Transmission Design for RIS-Aided Cell-Free Massive MIMO Systems
Finally, the numerical results demonstrate the correctness of our derived expressions and the benefits of deploying large-size RISs into cell-free mMIMO systems.
Low Altitude 3-D Coverage Performance Analysis in Cell-Free Distributed Collaborative Massive MIMO Systems
To improve the poor performance of distributed operation and non-scalability of centralized operation in traditional cell-free massive MIMO, we propose a cell-free distributed collaborative (CFDC) massive multiple-input multiple-output (MIMO) system based on a novel two-layer model to take advantages of the distributed cloud-edge-end collaborative architecture in beyond 5G (B5G) internet of things (IoT) environment to provide strong flexibility and scalability.
Real-time Dual-channel 2 * 2 MIMO Fiber-THz-Fiber Seamless Integration System at 385 GHz and 435 GHz
We demonstrate the first practical real-time dual-channel fiber-THz-fiber 2 * 2 MIMO seamless integration system with a record net data rate of 2 * 103. 125 Gb/s at 385 GHz and 435 GHz over two spans of 20 km SSMF and 3 m wireless link.
Content Popularity Prediction Based on Quantized Federated Bayesian Learning in Fog Radio Access Networks
To utilize the computing resources of other fog access points (F-APs) and to reduce the communications overhead, we propose a quantized federated learning (FL) framework combining with Bayesian learning.
A Federated Reinforcement Learning Method with Quantization for Cooperative Edge Caching in Fog Radio Access Networks
In this paper, cooperative edge caching problem is studied in fog radio access networks (F-RANs).
Efficient Joint DOA and TOA Estimation for Indoor Positioning with 5G Picocell Base Stations
Secondly, based on the deployment reality that 5G picocell gNBs only have a small-scale antenna array but have a large signal bandwidth, the proposed scheme decouples the estimation of time-of-arrival (TOA) and direction-of-arrival (DOA) to reduce the huge complexity induced by two-dimensional joint processing.
Computation Offloading and Resource Allocation in F-RANs: A Federated Deep Reinforcement Learning Approach
In this paper, by considering time-varying network environment, a dynamic computation offloading and resource allocation problem in F-RANs is formulated to minimize the task execution delay and energy consumption of MDs.
Content Popularity Prediction in Fog-RANs: A Clustered Federated Learning Based Approach
Based on clustered federated learning, we propose a novel mobility-aware popularity prediction policy, which integrates content popularities in terms of local users and mobile users.
Semi-supervised MIMO Detection Using Cycle-consistent Generative Adversarial Network
In this paper, a new semi-supervised deep multiple-input multiple-output (MIMO) detection approach using a cycle-consistent generative adversarial network (CycleGAN) is proposed for communication systems without any prior knowledge of underlying channel distributions.
Pervasive wireless channel modeling theory and applications to 6G GBSMs for all frequency bands and all scenarios
In this paper, a pervasive wireless channel modeling theory is first proposed, which uses a unified channel modeling method and a unified equation of channel impulse response (CIR), and can integrate important channel characteristics at different frequency bands and scenarios.
Hybrid Beamforming for Millimeter Wave MIMO Integrated Sensing and Communications
In this letter, we consider hybrid beamforming for millimeter wave (mmWave) MIMO integrated sensing and communications (ISAC).
A Novel 3D Non-Stationary GBSM for 6G THz Ultra-Massive MIMO Wireless Systems
Terahertz (THz) communication is now being considered as one of possible technologies for the sixth generation (6G) wireless communication systems.
Privacy-preserving Channel Estimation in Cell-free Hybrid Massive MIMO Systems
We consider a cell-free hybrid massive multiple-input multiple-output (MIMO) system with $K$ users and $M$ access points (APs), each with $N_a$ antennas and $N_r< N_a$ radio frequency (RF) chains.
Low-Rank Matrix Completion
Information Theory
Signal Processing
Information Theory
A General 3D Non-Stationary Wireless Channel Model for 5G and Beyond
In this paper, a novel three-dimensional (3D) non-stationary geometry-based stochastic model (GBSM) for the fifth generation (5G) and beyond 5G (B5G) systems is proposed.
True-data Testbed for 5G/B5G Intelligent Network
Future beyond fifth-generation (B5G) and sixth-generation (6G) mobile communications will shift from facilitating interpersonal communications to supporting Internet of Everything (IoE), where intelligent communications with full integration of big data and artificial intelligence (AI) will play an important role in improving network efficiency and providing high-quality service.
Reconfigurable Intelligent Surfaces for 6G Systems: Principles, Applications, and Research Directions
Reconfigurable intelligent surfaces (RISs) or intelligent reflecting surfaces (IRSs), are regarded as one of the most promising and revolutionizing techniques for enhancing the spectrum and/or energy efficiency of wireless systems.
6G Oriented Wireless Communication Channel Characteristics Analysis and Modeling
Based on the vision on the 6G wireless communication network, i. e., global coverage, all spectrums and all applications, we comprehensively survey 6G related wireless channel measurements, channel characteristics, and channel models for all frequency bands and all scenarios.
Distributed Edge Caching via Reinforcement Learning in Fog Radio Access Networks
In this paper, the distributed edge caching problem in fog radio access networks (F-RANs) is investigated.
Polar Decoding on Sparse Graphs with Deep Learning
In this paper, we present a sparse neural network decoder (SNND) of polar codes based on belief propagation (BP) and deep learning.
Improving Massive MIMO Belief Propagation Detector with Deep Neural Network
Numerical results are presented to demonstrate the performance of the DNN detectors in comparison with various BP modifications.
