Incentive-driven deep reinforcement learning for content caching and D2D offloading
Offloading cellular traffic via Device-to-Device communication (or D2D offloading) has been
proved to be an effective way to ease the traffic burden of cellular networks. However …
proved to be an effective way to ease the traffic burden of cellular networks. However …
Multi-agent reinforcement learning for efficient content caching in mobile D2D networks
To address the increase of multimedia traffic dominated by streaming videos, user
equipment (UE) can collaboratively cache and share contents to alleviate the burden of …
equipment (UE) can collaboratively cache and share contents to alleviate the burden of …
Energy minimization in D2D-assisted cache-enabled Internet of Things: A deep reinforcement learning approach
Mobile edge caching (MEC) and device-todevice (D2D) communications are two potential
technologies to resolve traffic overload problems in the Internet of Things. Previous works …
technologies to resolve traffic overload problems in the Internet of Things. Previous works …
Deep reinforcement learning approaches for content caching in cache-enabled D2D networks
Internet of Things (IoT) technology suffers from the challenge that rare wireless network
resources are difficult to meet the influx of a huge number of terminal devices. Cache …
resources are difficult to meet the influx of a huge number of terminal devices. Cache …
Deep reinforcement learning (DRL)-based device-to-device (D2D) caching with blockchain and mobile edge computing
Device-to-Device (D2D) caching assists Mobile Edge Computing (MEC) based caching in
offloading inter-domain traffic by sharing cached items with nearby users, while its …
offloading inter-domain traffic by sharing cached items with nearby users, while its …
A deep reinforcement learning based approach for cost-and energy-aware multi-flow mobile data offloading
With the rapid increase in demand for mobile data, mobile network operators are trying to
expand wireless network capacity by deploying wireless local area network (LAN) hotspots …
expand wireless network capacity by deploying wireless local area network (LAN) hotspots …
Cooperative caching and fetching in d2d communications-a fully decentralized multi-agent reinforcement learning approach
To satisfy the increasing demands of cellular traffic, cooperative content caching at the
network edge (eg, User Equipment) has become a promising paradigm in the next …
network edge (eg, User Equipment) has become a promising paradigm in the next …
On social-aware content caching for D2D-enabled cellular networks with matching theory
In this paper, the problem of content caching in 5G cellular networks relying on social-aware
device-to-device communications (DTD) is investigated. Our focus is on how to efficiently …
device-to-device communications (DTD) is investigated. Our focus is on how to efficiently …
Attention-weighted federated deep reinforcement learning for device-to-device assisted heterogeneous collaborative edge caching
In order to meet the growing demands for multimedia service access and release the
pressure of the core network, edge caching and device-to-device (D2D) communication …
pressure of the core network, edge caching and device-to-device (D2D) communication …
An incentive mechanism integrating joint power, channel and link management for social-aware D2D content sharing and proactive caching
In this paper, a downlink cellular traffic offloading framework with social-aware device-to-
device (D2D) content sharing and proactive caching is studied. In the considered system …
device (D2D) content sharing and proactive caching is studied. In the considered system …