Deep reinforcement learning for time allocation and directional transmission in joint radar-communication

Deep reinforcement learning for time allocation and directional transmission in joint radar-communication

Current strategies for joint radar-communication (JRC) rely on prior knowledge of the communication and radar systems within the vehicle network. In this paper, we propose a framework for intelligent vehicles to conduct JRC, with minimal prior knowledge, in an environment where surrounding vehicles...

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Bibliographic Details
Main Authors: Lee, Joash, Cheng, Yanyu, Niyato, Dusit, Guan, Yong Liang, Gonzalez, David G.
Other Authors: School of Computer Science and Engineering
Format: Conference Paper
Language:English
Published: 2022
Subjects:
Engineering::Computer science and engineering
Engineering::Electrical and electronic engineering::Wireless communication systems
Vehicle-to-Everything
Deep Reinforcement Learning
Resource Allocation
Joint Radar-Communication
Online Access:https://hdl.handle.net/10356/155437

Internet

https://hdl.handle.net/10356/155437

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