"Doubly-Dynamic ISAC Precoding for Vehicular Networks: A Constrained Deep ..."

Zonghui Yang, Shijian Gao, Xiang Cheng (2024)

> Home

Details and statistics

DOI: 10.1109/GLOBECOM52923.2024.10901120

access: closed

type: Conference or Workshop Paper

metadata version: 2025-04-10

- view
  - electronic edition via DOI
  - unpaywalled version
  authority control:
- export record
  dblp key:
  - conf/globecom/YangG024
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/conf/globecom/YangG024
Zonghui Yang, Shijian Gao, Xiang Cheng:
Doubly-Dynamic ISAC Precoding for Vehicular Networks: A Constrained Deep Reinforcement Learning (CDRL) Approach. GLOBECOM 2024: 5417-5422

manage site settings

To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.