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Found 12 papers, 2 papers with code
Anti-Byzantine Attacks Enabled Vehicle Selection for Asynchronous Federated Learning in Vehicular Edge Computing
In this scheme, vehicle s mobility, channel conditions with temporal variations, computational resources with temporal variations, different data amount, transmission channel status of vehicles as well as Byzantine attacks were taken into account. Simulation results show that the proposed scheme effectively improves the safety and accuracy of the global model.
Spectral Efficiency Maximization for Active RIS-aided Cell-Free Massive MIMO Systems with Imperfect CSI
A cell-free network merged with active reconfigurable reflecting surfaces (RIS) is investigated in this paper.
Cooperative Edge Caching Based on Elastic Federated and Multi-Agent Deep Reinforcement Learning in Next-Generation Network
Finally, we propose a multi-agent deep reinforcement learning (MADRL) based algorithm to decide where the predicted popular contents are collaboratively cached among SBSs.
Statistical CSI-based Beamforming for RIS-Aided Multiuser MISO Systems using Deep Reinforcement Learning
The paper presents a joint beamforming algorithm using statistical channel state information (S-CSI) for reconfigurable intelligent surfaces (RIS) for multiuser MISO wireless communications.
Smart Interference Management xApp using Deep Reinforcement Learning
Interference continues to be a key limiting factor in cellular radio access network (RAN) deployments.
Self-Sustainable Reconfigurable Intelligent Surface Aided Simultaneous Terahertz Information and Power Transfer (STIPT)
This paper proposes a new simultaneous terahertz (THz) information and power transfer (STIPT) system, which is assisted by reconfigurable intelligent surface (RIS) for both the information data and power transmission.
UAV-Assisted and Intelligent Reflecting Surfaces-Supported Terahertz Communications
In this paper, unmanned aerial vehicles (UAVs) and intelligent reflective surface (IRS) are utilized to support terahertz (THz) communications.
Dual Graph Representation Learning
Graph representation learning embeds nodes in large graphs as low-dimensional vectors and is of great benefit to many downstream applications.
Combining Deep Learning and Topic Modeling for Review Understanding in Context-Aware Recommendation
The proposed model is named LSTM-Topic matrix factorization (LTMF) which integrates both LSTM and Topic Modeling for review understanding.
A Machine Learning Framework for Resource Allocation Assisted by Cloud Computing
Moreover, optimal or near-optimal solutions of historical scenarios can be searched offline and stored in advance.
Embedding Knowledge Graphs Based on Transitivity and Antisymmetry of Rules
The key idea is to integrate knowledge triples and logic rules, and approximately order the relation types in logic rules to utilize the transitivity and antisymmetry of logic rules.
On Consideration of Content Preference and Sharing Willingness in D2D Assisted Offloading
Furthermore, an alternative group optimization (AGO) algorithm is proposed to solve the general case of the optimization problem.
Networking and Internet Architecture
