Home ›
Entities
› academia
› Deep Reinforcement Learning-Based Joint Spectrum Allocation and Configuration Design for STAR-RIS-Assisted V2X Communications
Deep Reinforcement Learning-Based Joint Spectrum Allocation and Configuration Design for STAR-RIS-Assisted V2X Communications
Research article (IEEE Internet of Things Journal, 2023) · cited 48× · AI/ML
Deep Reinforcement Learning-Based Joint Spectrum Allocation and Configuration Design for STAR-RIS-Assisted V2X Communications
Summary
Deep Reinforcement Learning-Based Joint Spectrum Allocation and Configuration Design for STAR-RIS-Assisted V2X Communications is a scholarly article[1].
Key Facts
Deep Reinforcement Learning-Based Joint Spectrum Allocation and Configuration Design for STAR-RIS-Assisted V2X Communications's instance of is recorded as scholarly article[2].
References
Programmatic citations — every numbered marker resolves to a verifiable graph row below.
Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). Deep Reinforcement Learning-Based Joint Spectrum Allocation and Configuration Design for STAR-RIS-Assisted V2X Communications. Retrieved May 24, 2026, from https://4ort.xyz/entity/deep-reinforcement-learning-based-joint-spectrum-allocation-and-configuration-design-for-star-ris-assisted-v2x-communica