Paper Citation Record · LEDGER

Sensing-Aided 6G Drone Communications: Real-World Datasets and Demonstration

As of 16 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 1 inbound Pith citation observation for arXiv:2412.04734.

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

pith.paper-citation-record.v1
2412.04734 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T21:21:52.770474Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:48:32.032286Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T14:48:32.988421Z

Reference resolution

32 of 32 outbound references displayed

verified exact2
verified fuzzy22
unresolved8
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a998874a-3217-4309-9e1c-64829935ca81 · outbound

This paper cites Towards real-world 6G drone communication: Position and camera aided beam prediction,.

Sensing-Aided 6G Drone Communications: Real-World Datasets and Demonstration Towards real-world 6G drone communication: Position and camera aided beam prediction,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:21:54.043433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 3f0f7df3-5161-4b56-874a-bc2f40fda08c · outbound

This paper cites A prospective look: Key enabling technologies, applications and open research topics in 6g networks,.

Sensing-Aided 6G Drone Communications: Real-World Datasets and Demonstration A prospective look: Key enabling technologies, applications and open research topics in 6g networks,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:21:53.996332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation e6164dbb-a3dc-483a-a0dc-c754b381fbb8 · outbound

This paper cites Toward 6G with connected sky: UA Vs and beyond,.

Sensing-Aided 6G Drone Communications: Real-World Datasets and Demonstration Toward 6G with connected sky: UA Vs and beyond,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:21:53.967909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 7b2dcd54-baf5-4c3d-a115-2dc0296e2253 · outbound

This paper cites DisastDrone: A disaster aware consumer Internet of Drone Things system in ultra-low latent 6G network,.

Sensing-Aided 6G Drone Communications: Real-World Datasets and Demonstration DisastDrone: A disaster aware consumer Internet of Drone Things system in ultra-low latent 6G network,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:21:53.940756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 1a9c70df-1604-47d9-84c4-7213aa4fc9de · outbound

This paper cites Decentralized Interference-Aware Codebook Learning in Millimeter Wave MIMO Systems.

Sensing-Aided 6G Drone Communications: Real-World Datasets and Demonstration Decentralized Interference-Aware Codebook Learning in Millimeter Wave MIMO Systems

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-08-11T21:21:53.230194Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 54b110d1-5aaf-45e0-928e-60f9a7e03e38 · outbound

This paper cites Wireless communications and applications above 100 GHz: Opportunities and challenges for 6G and beyond,.

Sensing-Aided 6G Drone Communications: Real-World Datasets and Demonstration Wireless communications and applications above 100 GHz: Opportunities and challenges for 6G and beyond,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-11T21:21:52.089152Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 48c4ab25-29f0-4a35-b9a2-9e398da1e940 · outbound

This paper cites Multilevel millimeter wave beamforming for wireless backhaul,.

Sensing-Aided 6G Drone Communications: Real-World Datasets and Demonstration Multilevel millimeter wave beamforming for wireless backhaul,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:21:53.878460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 5a77ada6-2d09-4694-ad6d-f089fa3e75c2 · outbound

This paper cites Channel estimation and hybrid precoding for millimeter wave cellular systems,.

Sensing-Aided 6G Drone Communications: Real-World Datasets and Demonstration Channel estimation and hybrid precoding for millimeter wave cellular systems,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:21:53.847331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 2ab8ee07-a5cf-4dca-8e60-4beb46576380 · outbound

This paper cites Robust beam-tracking for mmwave mobile communications,.

Sensing-Aided 6G Drone Communications: Real-World Datasets and Demonstration Robust beam-tracking for mmwave mobile communications,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:21:53.796270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 0580d14a-625f-4df5-b3df-900b43d4734b · outbound

This paper cites Machine learning for reliable mmwave systems: Blockage prediction and proactive handoff,.

Sensing-Aided 6G Drone Communications: Real-World Datasets and Demonstration Machine learning for reliable mmwave systems: Blockage prediction and proactive handoff,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:21:53.765438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation b98649e2-557c-4183-9778-70eb3fe0be11 · outbound

This paper cites Position and machine learning-aided beam prediction and selection technique in millimeter-wave cellular system,.

Sensing-Aided 6G Drone Communications: Real-World Datasets and Demonstration Position and machine learning-aided beam prediction and selection technique in millimeter-wave cellular system,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:21:53.745920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 0c4ed358-b91a-497c-819a-9d64e75efd17 · outbound

This paper cites Millimeter wave base stations with cameras: Vision-aided beam and blockage prediction,.

Sensing-Aided 6G Drone Communications: Real-World Datasets and Demonstration Millimeter wave base stations with cameras: Vision-aided beam and blockage prediction,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:21:53.721064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation a864df29-d1d0-4bad-b2f2-1067646a57d6 · outbound

This paper cites Mmwave beam prediction with situational awareness: A machine learning approach,.

Sensing-Aided 6G Drone Communications: Real-World Datasets and Demonstration Mmwave beam prediction with situational awareness: A machine learning approach,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:21:53.689837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation c4558e26-242d-4364-a97c-f30e6189e51a · outbound

This paper cites Location- and orientation-aided millimeter wave beam selection using deep learning,.

Sensing-Aided 6G Drone Communications: Real-World Datasets and Demonstration Location- and orientation-aided millimeter wave beam selection using deep learning,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:21:53.670174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 168f8ae7-ffaa-4a9f-90ff-cf49f8f406a5 · outbound

This paper cites Vision-position multi-modal beam prediction using real millimeter wave datasets,.

Sensing-Aided 6G Drone Communications: Real-World Datasets and Demonstration Vision-position multi-modal beam prediction using real millimeter wave datasets,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:21:53.644447Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 3d9cbcf6-2cf2-4954-95a3-1d783e60e09e · outbound

This paper cites Vision-aided 6G wireless communications: Blockage prediction and proactive handoff,.

Sensing-Aided 6G Drone Communications: Real-World Datasets and Demonstration Vision-aided 6G wireless communications: Blockage prediction and proactive handoff,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:21:53.613746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 925bbdcb-4d41-4761-a41d-bf0baf0fbfe4 · outbound

This paper cites Position-aided beam prediction in the real world: How useful GPS locations actually are?.

Sensing-Aided 6G Drone Communications: Real-World Datasets and Demonstration Position-aided beam prediction in the real world: How useful GPS locations actually are?

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-11T21:21:52.339919Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3fef331b-dfec-44a6-ad96-d3b6fc6c473e · outbound

This paper cites LiDAR aided future beam prediction in real-world millimeter wave V2I communications,.

Sensing-Aided 6G Drone Communications: Real-World Datasets and Demonstration LiDAR aided future beam prediction in real-world millimeter wave V2I communications,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-11T21:21:52.350516Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d42ee2c-2607-4064-8746-1ed852234f57 · outbound

This paper cites Radar aided 6G beam prediction: Deep learning algorithms and real-world demonstration,.

Sensing-Aided 6G Drone Communications: Real-World Datasets and Demonstration Radar aided 6G beam prediction: Deep learning algorithms and real-world demonstration,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:21:53.501134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d5ef2f92-f7e5-4498-ac1b-32adaf9c7a03 · outbound

This paper cites Multi-Modal Beam Prediction Challenge 2022: Towards Generalization.

Sensing-Aided 6G Drone Communications: Real-World Datasets and Demonstration Multi-Modal Beam Prediction Challenge 2022: Towards Generalization

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-11T21:21:52.404754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6c7ee372-8207-49aa-a0a4-58877a5d71d9 · outbound

This paper cites DeepSense-V2V: A Vehicle-to-Vehicle Multi-Modal Sensing, Localization, and Communications Dataset.

Sensing-Aided 6G Drone Communications: Real-World Datasets and Demonstration DeepSense-V2V: A Vehicle-to-Vehicle Multi-Modal Sensing, Localization, and Communications Dataset

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-08-11T21:21:53.159394Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation faec385f-eb65-4312-9b97-02dcf34a3ef9 · outbound

This paper cites Beam alignment for high-speed uav via angle prediction and adaptive beam coverage,.

Sensing-Aided 6G Drone Communications: Real-World Datasets and Demonstration Beam alignment for high-speed uav via angle prediction and adaptive beam coverage,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:21:53.451169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 19dcfa2d-63ab-4ddd-8107-3c8a62e92222 · outbound

This paper cites Learning-based predictive beamforming for uav communications with jittering,.

Sensing-Aided 6G Drone Communications: Real-World Datasets and Demonstration Learning-based predictive beamforming for uav communications with jittering,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:21:53.431559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 4f9f44d9-a9c7-46d3-86dd-5578f96130be · outbound

This paper cites Location-aware predictive beamforming for uav communications: A deep learning approach,.

Sensing-Aided 6G Drone Communications: Real-World Datasets and Demonstration Location-aware predictive beamforming for uav communications: A deep learning approach,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:21:53.405764Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 51534e33-0589-4113-9d56-050a5152e66b · outbound

This paper cites Deepsense 6G: A large-scale real-world multi-modal sensing and communication dataset,.

Sensing-Aided 6G Drone Communications: Real-World Datasets and Demonstration Deepsense 6G: A large-scale real-world multi-modal sensing and communication dataset,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:21:53.353615Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation a63c9094-957a-42ef-a96c-5b676581b35b · outbound

This paper cites Deep residual learning for image recognition,.

Sensing-Aided 6G Drone Communications: Real-World Datasets and Demonstration Deep residual learning for image recognition,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-11T21:21:52.522558Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7e4a798b-73eb-4efd-8712-548bf1f3a89e · outbound

This paper cites Imagenet large scale visual recognition challenge,.

Sensing-Aided 6G Drone Communications: Real-World Datasets and Demonstration Imagenet large scale visual recognition challenge,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:21:53.310865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d8638f67-0171-45ad-aca3-d1bff22002e2 · outbound

This paper cites A comprehensive survey on transfer learning,.

Sensing-Aided 6G Drone Communications: Real-World Datasets and Demonstration A comprehensive survey on transfer learning,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:21:53.288959Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 9f5d5cf5-6e17-4e67-ba6f-640a1bb7c51d · outbound

This paper cites Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling.

Sensing-Aided 6G Drone Communications: Real-World Datasets and Demonstration Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-11T21:21:52.584745Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ab00e1c-915b-43aa-9342-e7109efa746b · outbound

This paper cites YOLOv3: An Incremental Improvement.

Sensing-Aided 6G Drone Communications: Real-World Datasets and Demonstration YOLOv3: An Incremental Improvement

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-11T21:21:52.625829Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 686775fd-5580-47fe-a3b6-3a7fc2d5864e · outbound

This paper cites You only look once: Unified, real-time object detection,.

Sensing-Aided 6G Drone Communications: Real-World Datasets and Demonstration You only look once: Unified, real-time object detection,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:21:53.254021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 4bffce3f-0a06-49bd-b25b-3695fafce3fd · outbound

This paper cites Learnable Wireless Digital Twins: Reconstructing Electromagnetic Field with Neural Representations.

Sensing-Aided 6G Drone Communications: Real-World Datasets and Demonstration Learnable Wireless Digital Twins: Reconstructing Electromagnetic Field with Neural Representations

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-11T21:21:52.770474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation ffb9faff-c7bc-4c89-ad78-2b44731f67f1 · inbound

GPS-Aided Deep Learning for Beam Prediction and Tracking in UAV mmWave Communication cites this paper.

GPS-Aided Deep Learning for Beam Prediction and Tracking in UAV mmWave Communication Sensing-Aided 6G Drone Communications: Real-World Datasets and Demonstration

Reference 2024

Resolution: metadata mismatch; local_arxiv, observed 2026-08-07T14:48:33.088060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.