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Intelligent resource slicing for eMBB and URLLC coexistence in 5G and beyond:a deep reinforcement learning based approach

PaperCitations, authors & open-access status

Intelligent resource slicing for eMBB and URLLC coexistence in 5G and beyond:a deep reinforcement learning based approach is a paper indexed in ScholarIQ from OpenAlex.

How many citations does Intelligent resource slicing for eMBB and URLLC coexistence in 5G and beyond:a deep reinforcement learning based approach have?

ScholarIQcitation count

Intelligent resource slicing for eMBB and URLLC coexistence in 5G and beyond:a deep reinforcement learning based approach has 325 citations in the OpenAlex counts ScholarIQ stores.

When was Intelligent resource slicing for eMBB and URLLC coexistence in 5G and beyond:a deep reinforcement learning based approach published?

ScholarIQyear

Intelligent resource slicing for eMBB and URLLC coexistence in 5G and beyond:a deep reinforcement learning based approach has 2021 year in the ScholarIQ index.

What is the open-access status of Intelligent resource slicing for eMBB and URLLC coexistence in 5G and beyond:a deep reinforcement learning based approach?

ScholarIQoa status

Intelligent resource slicing for eMBB and URLLC coexistence in 5G and beyond:a deep reinforcement learning based approach has closed oa status in the ScholarIQ index.

What is the OpenAlex record for Intelligent resource slicing for eMBB and URLLC coexistence in 5G and beyond:a deep reinforcement learning based approach?

ScholarIQopenalex

The OpenAlex for Intelligent resource slicing for eMBB and URLLC coexistence in 5G and beyond:a deep reinforcement learning based approach is on the source record.

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