Paper Citation Record · LEDGER

Deep Reinforcement Learning for Radio Resource Allocation and Management in Next Generation Heterogeneous Wireless Networks: A Survey

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2106.00574.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2106.00574 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:13:03.931497Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-02T11:16:53.548980Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 0aa244e6-13c4-49f8-8110-34871bef243b · inbound

Frequency Resource Management in 6G User-Centric CFmMIMO: A Hybrid Reinforcement Learning and Metaheuristic Approach cites this paper.

Frequency Resource Management in 6G User-Centric CFmMIMO: A Hybrid Reinforcement Learning and Metaheuristic Approach Deep Reinforcement Learning for Radio Resource Allocation and Management in Next Generation Heterogeneous Wireless Networks: A Survey

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T13:13:03.931497Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3799fdff-26dc-4628-8568-b93d9739c25c · inbound

When AI Meets Terahertz: A Survey on the Symbiosis of Artificial Intelligence and Terahertz Networks cites this paper.

When AI Meets Terahertz: A Survey on the Symbiosis of Artificial Intelligence and Terahertz Networks Deep Reinforcement Learning for Radio Resource Allocation and Management in Next Generation Heterogeneous Wireless Networks: A Survey

Reference 60

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:06:10.476640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation aaa943c5-b3d1-47ed-9883-5d16e3e31a71 · inbound

From Denoising to Decision Making: A Survey on Diffusion Model-Enabled Deep Reinforcement Learning for Wireless Networks cites this paper.

From Denoising to Decision Making: A Survey on Diffusion Model-Enabled Deep Reinforcement Learning for Wireless Networks Deep Reinforcement Learning for Radio Resource Allocation and Management in Next Generation Heterogeneous Wireless Networks: A Survey

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-06-29T20:53:58.359108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3f43c991-ea26-4f37-9ee0-66fd88b71ded · inbound

Transformer-Enhanced Reinforcement Learning: Fundamentals and Applications in Communication Networks cites this paper.

Transformer-Enhanced Reinforcement Learning: Fundamentals and Applications in Communication Networks Deep Reinforcement Learning for Radio Resource Allocation and Management in Next Generation Heterogeneous Wireless Networks: A Survey

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-06-29T16:23:39.732835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f667958c-8659-45e1-b05c-e4541e9f7aa2 · inbound

Bounded Deep Unfolding for Joint Beamforming and Scheduling in Multi-Cell MIMO Networks cites this paper.

Bounded Deep Unfolding for Joint Beamforming and Scheduling in Multi-Cell MIMO Networks Deep Reinforcement Learning for Radio Resource Allocation and Management in Next Generation Heterogeneous Wireless Networks: A Survey

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-07-02T11:16:53.551252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 754abb2f-0e1c-4756-8294-d943a015df14 · inbound

Bounded Deep Unfolding for Joint Beamforming and Scheduling in Multi-Cell MIMO Networks cites this paper.

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-02T12:29:24.269946Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.