Paper Citation Record · LEDGER

AI-assisted PHY technologies for 6G and beyond wireless networks

As of 16 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 0 inbound Pith citation observations for arXiv:1908.09523.

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

pith.paper-citation-record.v1
1908.09523 v1

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T11:12:29.458507Z

measured 12 of 12 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 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

12 of 12 outbound references displayed

verified exact0
verified fuzzy12
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 822a164e-3ffd-4a92-a072-477cb5a3e2d7 · outbound

This paper cites Proactive Resource Management in LTE-U Systems: A Deep Learning Perspective,.

AI-assisted PHY technologies for 6G and beyond wireless networks Proactive Resource Management in LTE-U Systems: A Deep Learning Perspective,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:12:29.659864Z

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 017866e6-06af-46ef-a5cb-959bde56cf34 · outbound

This paper cites Machine learning based obstacle detection for Automatic Train Pairing,.

AI-assisted PHY technologies for 6G and beyond wireless networks Machine learning based obstacle detection for Automatic Train Pairing,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:12:29.646816Z

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 e9858b86-d7eb-43ee-97af-3a259a4008a8 · outbound

This paper cites Deep Convolutional Neural Networks for Massive MIMO Fingerprint-Based Positioning,.

AI-assisted PHY technologies for 6G and beyond wireless networks Deep Convolutional Neural Networks for Massive MIMO Fingerprint-Based Positioning,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:12:29.633602Z

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 63f30a4d-de24-4999-8141-6d0d1d2f4444 · outbound

This paper cites Error correcting neural networks for channels with Gaussian noise,.

AI-assisted PHY technologies for 6G and beyond wireless networks Error correcting neural networks for channels with Gaussian noise,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:12:29.620918Z

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 53424b80-b3ba-4169-9985-a4f65afc59fb · outbound

This paper cites Performance analysis of deep learning based on recurrent neural networks for channel cod- ing,.

AI-assisted PHY technologies for 6G and beyond wireless networks Performance analysis of deep learning based on recurrent neural networks for channel cod- ing,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:12:29.607003Z

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 1a713ae4-77f2-48da-b5ec-02f73094c70c · outbound

This paper cites An Introduction to Deep Learning for the Physical Layer,.

AI-assisted PHY technologies for 6G and beyond wireless networks An Introduction to Deep Learning for the Physical Layer,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:12:29.592969Z

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 2873ba7d-5bfe-4e38-a95b-267831b68d1f · outbound

This paper cites Application of machine learning for channel based message authentication in mission critical machine type communication,.

AI-assisted PHY technologies for 6G and beyond wireless networks Application of machine learning for channel based message authentication in mission critical machine type communication,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:12:29.577750Z

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 e61fa07f-6b8a-4adc-ae51-a54cbddf7ee5 · outbound

This paper cites Channel Esti- mation for Massive MIMO Using Gaussian-Mixture Bayesian Learning,.

AI-assisted PHY technologies for 6G and beyond wireless networks Channel Esti- mation for Massive MIMO Using Gaussian-Mixture Bayesian Learning,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:12:29.563808Z

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 4ddf8426-550f-4d53-b58d-2f4b3151bffd · outbound

This paper cites Multilayer feedforward networks are universal approximators,.

AI-assisted PHY technologies for 6G and beyond wireless networks Multilayer feedforward networks are universal approximators,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:12:29.549133Z

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 3fc9c951-28e6-483a-9a5d-b9d64bb655b8 · outbound

This paper cites Physical layer authentication over mimo fading wiretap channels,.

AI-assisted PHY technologies for 6G and beyond wireless networks Physical layer authentication over mimo fading wiretap channels,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:12:29.534674Z

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 b7da8400-4000-4d4e-885d-8691ab737861 · outbound

This paper cites Channel-based physi- cal layer authentication,.

AI-assisted PHY technologies for 6G and beyond wireless networks Channel-based physi- cal layer authentication,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:12:29.521265Z

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 e9dd92fa-80dc-4c67-8e2b-fa1f57d1d7e7 · outbound

This paper cites Physical layer authentication for mission critical machine type communication using gaussian mixture model based clustering,.

AI-assisted PHY technologies for 6G and beyond wireless networks Physical layer authentication for mission critical machine type communication using gaussian mixture model based clustering,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:12:29.506810Z

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.

Pith citing papers

No inbound Pith citation observations are available.