Performance evaluation of V2X COMMUNICATION

TITLE :- ENHANCING CELLULAR VEHICLE-TO-EVERYTHING (C-V2X) COMMUNICATION THROUGH ADAPTIVE MCS INDEX CONTROL WITH REINFORCEMENT LEARNING
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Implementation Plan:
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Tools:
Software Tools -- Omnet 4.6, SUMO-0.19.0
Operating System --Windows 10 [64-bit]
Project workflow:
Ø We Construct a network with 100- Vehicles, 2- Rsu, and 1 - Base station.
Ø The proposed work includes Four processes which are listed as follows,
sumo configuration
Communication Model
Q-learning Algorithm
Ø sumo configuration : The placement of RSU and Vehicles depends on the sumo configuration.
Ø Communication Model : Next, We Implement communication model using C-V2X standards.
Ø Q-learning Algorithm: Next, We Integrate the reinforcement learning (RL) algorithm using the Q-learning approach
Ø Finally, The performance of this research is evaluated by the following metrics,
Throughput
Latency
Packet Loss Rate
Energy Efficiency
Note:
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1. If the above plan does not satisfy your requirement, please provide the processing details, like the above step-by-step.
2. Please note that this implementation plan does not include any further steps after it is put into implementation.
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#V2XCommunication
#PerformanceEvaluation
#ConnectedVehicles
#SmartTransportation
#WirelessTechnology
#TrafficSafety
#IoT
#VehicleToEverything
#DataTransmission
#futureofmobility
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