236 citations · 334 across the 4 of their papers we have counts for
5 papers
VRLS: A Unified Reinforcement Learning Scheduler for Vehicle-to-Vehicle Communications
Taylan Şahin, Ramin Khalili, Mate Boban +1
Vehicle-to-vehicle (V2V) communications have distinct challenges that need to be taken into account when scheduling the radio resources. Although centralized schedulers (e.g., loca…
Radio Resource Allocation for Reliable Out-of-coverage V2V Communications
Taylan Şahin, Mate Boban
We explore a new approach to radio resource allocation for vehicle-to-vehicle (V2V) communications in case of out-of-coverage areas that are delimited by network infrastructure. By…
Reinforcement Learning Scheduler for Vehicle-to-Vehicle Communications Outside Coverage
Taylan Şahin, Ramin Khalili, Mate Boban +1
Radio resources in vehicle-to-vehicle (V2V) communication can be scheduled either by a centralized scheduler residing in the network (e.g., a base station in case of cellular syste…
Use Cases, Requirements, and Design Considerations for 5G V2X
Mate Boban, Apostolos Kousaridas, Konstantinos Manolakis +2
Ultimate goal of next generation Vehicle-to-everything (V2X) communication systems is enabling accident-free cooperative automated driving that uses the available roadway efficient…
Vehicular Communications: Survey and Challenges of Channel and Propagation Models
Wantanee Viriyasitavat, Mate Boban, Hsin-Mu Tsai +1
Vehicular communication is characterized by a dynamic environment, high mobility, and comparatively low antenna heights on the communicating entities (vehicles and roadside units).…