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Found 11 papers, 0 papers with code
Multiagent Reinforcement Learning with an Attention Mechanism for Improving Energy Efficiency in LoRa Networks
Long Range (LoRa) wireless technology, characterized by low power consumption and a long communication range, is regarded as one of the enabling technologies for the Industrial Internet of Things (IIoT).
Federated Learning Robust to Byzantine Attacks: Achieving Zero Optimality Gap
In this paper, we propose a robust aggregation method for federated learning (FL) that can effectively tackle malicious Byzantine attacks.
Hierarchical Deep Reinforcement Learning for Age-of-Information Minimization in IRS-aided and Wireless-powered Wireless Networks
In this paper, we focus on a wireless-powered sensor network coordinated by a multi-antenna access point (AP).
Bayesian Optimization Enhanced Deep Reinforcement Learning for Trajectory Planning and Network Formation in Multi-UAV Networks
In this paper, we employ multiple UAVs coordinated by a base station (BS) to help the ground users (GUs) to offload their sensing data.
Dynamic Federated Learning-Based Economic Framework for Internet-of-Vehicles
Federated learning (FL) can empower Internet-of-Vehicles (IoV) networks by leveraging smart vehicles (SVs) to participate in the learning process with minimum data exchanges and privacy disclosure.
Optimization-driven Machine Learning for Intelligent Reflecting Surfaces Assisted Wireless Networks
Due to the large size of scattering elements, the passive beamforming is typically challenged by the high computational complexity and inexact channel information.
Optimization-driven Hierarchical Learning Framework for Wireless Powered Backscatter-aided Relay Communications
In this paper, we employ multiple wireless-powered relays to assist information transmission from a multi-antenna access point to a single-antenna receiver.
Optimization-driven Deep Reinforcement Learning for Robust Beamforming in IRS-assisted Wireless Communications
Intelligent reflecting surface (IRS) is a promising technology to assist downlink information transmissions from a multi-antenna access point (AP) to a receiver.
Robust Beamforming for IRS-assisted Wireless Communications under Channel Uncertainty
By adjusting the magnitude of reflecting coefficients, the IRS can sustain its operations by harvesting energy from the AP's signal beamforming.
Optimized Energy and Information Relaying in Self-Sustainable IRS-Empowered WPCN
We propose time-switching (TS) and power-splitting (PS) schemes for the IRS, where the IRS can harvest energy from the HAP's signals by switching between energy harvesting and signal reflection in the TS scheme or adjusting its reflection amplitude in the PS scheme.
Applications of Deep Reinforcement Learning in Communications and Networking: A Survey
Reinforcement learning has been efficiently used to enable the network entities to obtain the optimal policy including, e. g., decisions or actions, given their states when the state and action spaces are small.
