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Paper Citation Record · LEDGER

Multi-Agent DRL for QoS and Energy Optimization in RIS-Enabled Open-RAN Industrial 6G TN/NTN Networks

As of 23 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:2606.28339.

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

pith.paper-citation-record.v1
2606.28339 v1

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-30T11:22:58.667118Z

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

15 of 15 outbound references displayed

  • verified exact0
  • verified fuzzy15
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 95bde11b-64bf-4782-a801-a86830168997 · outbound

This paper cites 6g-enabled ultra-reliable low latency communication for industry 5.0: Challenges and future directions,.

Multi-Agent DRL for QoS and Energy Optimization in RIS-Enabled Open-RAN Industrial 6G TN/NTN Networks 6g-enabled ultra-reliable low latency communication for industry 5.0: Challenges and future directions,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T10:36:10.769631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-06-30T11:22:58.667118Z digest=sha256:442aacb1e8ce22e0d34107eaa91f66eeb38570c18646f72defd3a0496befc964

Observation efffd2b1-54a3-40d8-8cc1-7f2c6757bb4f · outbound

This paper cites A survey of intelligent network slicing management for industrial iot: Integrated approaches for smart transportation, smart energy, and smart factory,.

Multi-Agent DRL for QoS and Energy Optimization in RIS-Enabled Open-RAN Industrial 6G TN/NTN Networks A survey of intelligent network slicing management for industrial iot: Integrated approaches for smart transportation, smart energy, and smart factory,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T10:36:10.767727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-06-30T11:22:58.667118Z digest=sha256:5664dd2a847afa71162133e236e36b55266f70a082e55ec4ba789f0dc854d68b

Observation ba8334a4-99a6-41ec-88ea-8767a4d1d5a9 · outbound

This paper cites Empowering traffic steering in 6G Open RAN with deep reinforcement learning,.

Multi-Agent DRL for QoS and Energy Optimization in RIS-Enabled Open-RAN Industrial 6G TN/NTN Networks Empowering traffic steering in 6G Open RAN with deep reinforcement learning,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T10:36:10.775251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-06-30T11:22:58.667118Z digest=sha256:48e34f767253f3b8fc16b4777e438dbadd8075a1e33515abee5686b0e035d6a8

Observation 2eb32728-0bb2-46c3-811c-5f9dc40468d4 · outbound

This paper cites Emerging technologies for 6G non-terrestrial-networks: From academia to industrial applications,.

Multi-Agent DRL for QoS and Energy Optimization in RIS-Enabled Open-RAN Industrial 6G TN/NTN Networks Emerging technologies for 6G non-terrestrial-networks: From academia to industrial applications,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T10:36:10.777442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-06-30T11:22:58.667118Z digest=sha256:d6be428ed4b48179f95d38ca9a882be3a2945a0e9e74b1d80427d8346064652f

Observation b6da969d-02b3-4385-b0c5-38206ecf58df · outbound

This paper cites Multi-UA V Multi-RIS QoS-Aware Aerial Communication Systems Using DRL and PSO,.

Multi-Agent DRL for QoS and Energy Optimization in RIS-Enabled Open-RAN Industrial 6G TN/NTN Networks Multi-UA V Multi-RIS QoS-Aware Aerial Communication Systems Using DRL and PSO,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T10:36:10.765338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-06-30T11:22:58.667118Z digest=sha256:bb370879d1fd2eb2ca875f5b299ada47b58047ab206d0bd04ef71f08c48200e3

Observation 80b6fd89-4dd8-4ae1-805f-c833aae839df · outbound

This paper cites Guest editorial xURLLC in 6G: Next generation ultra-reliable and low-latency communications,.

Multi-Agent DRL for QoS and Energy Optimization in RIS-Enabled Open-RAN Industrial 6G TN/NTN Networks Guest editorial xURLLC in 6G: Next generation ultra-reliable and low-latency communications,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T10:36:10.787697Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-06-30T11:22:58.667118Z digest=sha256:389c604df52882bb1a20eb6a9235ae03f155f1baa1b3746c9af22f8357869dd1

Observation ddeb4cf3-e610-462e-ab66-08d6b46630eb · outbound

This paper cites RIS-Enabled UA V Swarm Optimization Framework for Energy Harvesting and Data Collection in Post-Disaster Recovery Management,.

Multi-Agent DRL for QoS and Energy Optimization in RIS-Enabled Open-RAN Industrial 6G TN/NTN Networks RIS-Enabled UA V Swarm Optimization Framework for Energy Harvesting and Data Collection in Post-Disaster Recovery Management,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T10:36:10.789880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-06-30T11:22:58.667118Z digest=sha256:46d0ca427ecff0e76be83841cb2b6e0be0f369640e6bb15658f6f6fb7112a722

Observation ae4b64be-e8aa-4278-a8db-36ba44983eb5 · outbound

This paper cites AoI-Aware Intelligent Platform for Energy and Rate Management in Multi-UA V Multi-RIS System,.

Multi-Agent DRL for QoS and Energy Optimization in RIS-Enabled Open-RAN Industrial 6G TN/NTN Networks AoI-Aware Intelligent Platform for Energy and Rate Management in Multi-UA V Multi-RIS System,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T10:36:10.785995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-06-30T11:22:58.667118Z digest=sha256:ab7211bfed67cf389321aba8f78753af944454aed9bf8b14eb955bc8f3358749

Observation 2acc884f-3b7f-41f6-8022-94f3e47125b7 · outbound

This paper cites Reconfigurable intelligent surfaces for 6g non- terrestrial networks: Assisting connectivity from the sky,.

Multi-Agent DRL for QoS and Energy Optimization in RIS-Enabled Open-RAN Industrial 6G TN/NTN Networks Reconfigurable intelligent surfaces for 6g non- terrestrial networks: Assisting connectivity from the sky,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T10:36:10.758497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-06-30T11:22:58.667118Z digest=sha256:a3b71457cbb88ed3c86db9cfad89de279b26cff0945899f7c788304632d7daac

Observation 086d01d4-1b6a-40eb-85e0-082c8518a3b7 · outbound

This paper cites Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UA V Swarms,.

Multi-Agent DRL for QoS and Energy Optimization in RIS-Enabled Open-RAN Industrial 6G TN/NTN Networks Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UA V Swarms,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T10:36:10.760862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-06-30T11:22:58.667118Z digest=sha256:dc1baff8df3b6d4a4296c70816fa7d079b285f9a889f26053c85636e7746bebc

Observation 844c1056-822a-479f-aa6c-73099a2437cd · outbound

This paper cites Ris- assisted physical-layer key generation for d2d communications with correlated and imperfect channels,.

Multi-Agent DRL for QoS and Energy Optimization in RIS-Enabled Open-RAN Industrial 6G TN/NTN Networks Ris- assisted physical-layer key generation for d2d communications with correlated and imperfect channels,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T10:36:10.784187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-06-30T11:22:58.667118Z digest=sha256:24658392a025d375640ddbd5841d8be6e145c90a82c4c2e468e32d07202e274f

Observation ab684d95-5bf6-4570-987b-502d212e93c5 · outbound

This paper cites Distributed and secure spectrum sharing for 5g and 6g networks,.

Multi-Agent DRL for QoS and Energy Optimization in RIS-Enabled Open-RAN Industrial 6G TN/NTN Networks Distributed and secure spectrum sharing for 5g and 6g networks,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T10:36:10.773323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-06-30T11:22:58.667118Z digest=sha256:49abb4d6ca1125bc90449ac062df90a82bd912e2354eef74d4b1e62a30edd278

Observation eceed672-ba49-48f3-9f47-f62657a9510f · outbound

This paper cites DRL- Based Joint Resource Allocation and Platoon Control Optimization for UA V-Hosted Platoon Digital Twin,.

Multi-Agent DRL for QoS and Energy Optimization in RIS-Enabled Open-RAN Industrial 6G TN/NTN Networks DRL- Based Joint Resource Allocation and Platoon Control Optimization for UA V-Hosted Platoon Digital Twin,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T10:36:10.782323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-06-30T11:22:58.667118Z digest=sha256:3555f03f4e49fbcdd5592ed8d5c81d40c577733eab66d1eacad429ef6e410252

Observation 312b99f4-70a7-417e-94f2-23adcae662f0 · outbound

This paper cites Reinforcement learning in multiple-uav networks: Deployment and movement design,.

Multi-Agent DRL for QoS and Energy Optimization in RIS-Enabled Open-RAN Industrial 6G TN/NTN Networks Reinforcement learning in multiple-uav networks: Deployment and movement design,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T10:36:10.771590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-06-30T11:22:58.667118Z digest=sha256:8028323bcdba65cffe5d703553b38ae3db111fc6b905f6a241895d85a1d28473

Observation 8d6d04b3-aa00-4bb4-aaa9-f63c4f095ead · outbound

This paper cites Two- tier resource allocation for multitenant network slicing: A federated deep reinforcement learning approach,.

Multi-Agent DRL for QoS and Energy Optimization in RIS-Enabled Open-RAN Industrial 6G TN/NTN Networks Two- tier resource allocation for multitenant network slicing: A federated deep reinforcement learning approach,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T10:36:10.762704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-06-30T11:22:58.667118Z digest=sha256:865ad090506a04a54bd28a2646ad9f6761388d2f024c2e2af65132735097bdaa

Pith citing papers

No inbound Pith citation observations are available.