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Found 18 papers, 0 papers with code
SSwsrNet: A Semi-Supervised Few-Shot Learning Framework for Wireless Signal Recognition
Moreover, a modular semi-supervised learning method that combines labeled and unlabeled data using MixMatch is exploited to further improve the classification performance under few-sample conditions.
KGAMC: A Novel Knowledge Graph Driven Automatic Modulation Classification Scheme
Automatic modulation classification (AMC) is a promising technology to realize intelligent wireless communications in the sixth generation (6G) wireless communication networks.
Knowledge Graph Driven UAV Cognitive Semantic Communication Systems for Efficient Object Detection
Unmanned aerial vehicles (UAVs) are widely used for object detection.
Adaptive Resource Allocation for Semantic Communication Networks
In order to investigate the performance of semantic communication networks, the quality of service for semantic communication (SC-QoS), including the semantic quantization efficiency (SQE) and transmission latency, is proposed for the first time.
A Partially Observable Deep Multi-Agent Active Inference Framework for Resource Allocation in 6G and Beyond Wireless Communications Networks
Simulation results demonstrate that our proposed framework can significantly improve the sum transmission rate of the secondary network compared to various benchmark schemes.
Novel Online-Offline MA2C-DDPG for Efficient Spectrum Allocation and Trajectory Optimization in Dynamic Spectrum Sharing UAV Networks
Unmanned aerial vehicle (UAV) communication is of crucial importance for diverse practical applications.
Cognitive Semantic Communication Systems Driven by Knowledge Graph: Principle, Implementation, and Performance Evaluation
Extensive simulation results conducted on a public dataset demonstrate that our proposed single-user and multi-user cognitive semantic communication systems are superior to benchmark communication systems in terms of the data compression rate and communication reliability.
Two Efficient Beamforming Methods for Hybrid IRS-aided AF Relay Wireless Networks
Moreover, it is verified that the proposed HP-SDR-FP method perform better than WF-GPI-GRR method in terms of rate performance.
One-to-Many Semantic Communication Systems: Design, Implementation, Performance Evaluation
To effectively exploit the benefits enabled by semantic communication, in this paper, we propose a one-to-many semantic communication system.
Data-and-Knowledge Dual-Driven Automatic Modulation Recognition for Wireless Communication Networks
In order to tackle these problems, a novel data-and-knowledge dual-driven automatic modulation classification scheme based on radio frequency machine learning is proposed by exploiting the attribute features of different modulations.
Cognitive Semantic Communication Systems Driven by Knowledge Graph
Semantic communication is envisioned as a promising technique to break through the Shannon limit.
Graph Neural Network-Based Scheduling for Multi-UAV-Enabled Communications in D2D Networks
In this paper, we propose a novel graph neural networks (GNN) based approach that can map the considered system into a specific graph structure and achieve the optimal solution in a low complexity manner.
Energy-Efficient Design for IRS-Assisted MEC Networks with NOMA
Energy-efficient design is of crucial importance in wireless internet of things (IoT) networks.
Automatic Modulation Classification Using Involution Enabled Residual Networks
Automatic modulation classification (AMC) is of crucial importance for realizing wireless intelligence communications.
A Unified Cognitive Learning Framework for Adapting to Dynamic Environment and Tasks
Many machine learning frameworks have been proposed and used in wireless communications for realizing diverse goals.
A Novel Automatic Modulation Classification Scheme Based on Multi-Scale Networks
Moreover, a novel loss function that combines the center loss and the cross entropy loss is exploited to learn both discriminative and separable features in order to further improve the classification performance.
A Unified Framework for IRS Enabled Wireless Powered Sensor Networks
To evaluate the performance of this IRS assisted WPSN, we are interested in maximizing its system sum throughput to jointly optimize the energy beamforming of the PS, the transmission time allocation, as well as the phase shifts of the WET and WIT phases.
Mobility-Aware Offloading and Resource Allocation in MEC-Enabled IoT Networks
In this paper, the offloading decision and resource allocation problem is studied with mobility consideration.
