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Dynamic mode selection and resource allocation approach for 5G-vehicle-to-everything (V2X) communication using asynchronous federated deep reinforcement learning method

Iftikhar Rasheed

2022Vehicular Communications21 citationsDOI

Topics & Concepts

Reinforcement learningComputer scienceAsynchronous communicationDistributed computingMarkov decision processIntelligent transportation systemVehicular ad hoc networkCluster analysisConvergence (economics)Resource allocationLatency (audio)Reliability (semiconductor)WirelessComputer networkArtificial intelligenceMarkov processWireless ad hoc networkTelecommunicationsStatisticsMathematicsPhysicsPower (physics)EconomicsEngineeringCivil engineeringEconomic growthQuantum mechanicsVehicular Ad Hoc Networks (VANETs)IoT and Edge/Fog ComputingAdvanced MIMO Systems Optimization
Dynamic mode selection and resource allocation approach for 5G-vehicle-to-everything (V2X) communication using asynchronous federated deep reinforcement learning method | Litcius