Paper Citation Record · LEDGER

Unified Generalization for Frequency-Domain Channel Extrapolation Across Near-Field and Far-Field Scenarios

As of 14 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2606.28885.

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

pith.paper-citation-record.v1
2606.28885 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-30T08:57:00.146581Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+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

30 of 30 outbound references displayed

verified exact3
verified fuzzy27
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 14a61147-0491-4481-bcd6-11b658f09de3 · outbound

This paper cites Multi-cell multi-user massive FD-MIMO: Downlink precoding and throughput analysis,.

Unified Generalization for Frequency-Domain Channel Extrapolation Across Near-Field and Far-Field Scenarios Multi-cell multi-user massive FD-MIMO: Downlink precoding and throughput analysis,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T10:07:01.669082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation c6cbcd6c-2f9e-4d65-957f-fd58ec642a9f · outbound

This paper cites Toward environment-aware 6G communications via channel knowledge map,.

Unified Generalization for Frequency-Domain Channel Extrapolation Across Near-Field and Far-Field Scenarios Toward environment-aware 6G communications via channel knowledge map,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T10:07:01.679702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 03f90fd1-884e-42a2-b486-a2a0c6333869 · outbound

This paper cites New paradigm for unified near- field and far-field wireless communications,.

Unified Generalization for Frequency-Domain Channel Extrapolation Across Near-Field and Far-Field Scenarios New paradigm for unified near- field and far-field wireless communications,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T10:07:01.653139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation e9dbeb5e-f69f-415c-90a9-c4adf25dc5c7 · outbound

This paper cites Beamspace channel estimation for wideband millimeter-wave MIMO: A model- driven unsupervised learning approach,.

Unified Generalization for Frequency-Domain Channel Extrapolation Across Near-Field and Far-Field Scenarios Beamspace channel estimation for wideband millimeter-wave MIMO: A model- driven unsupervised learning approach,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T10:07:01.672456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d78cc14e-c132-4854-98d2-3d0ba5e3e1d0 · outbound

This paper cites Deep learning assisted mmWave beam prediction for heterogeneous networks: A dual- band fusion approach,.

Unified Generalization for Frequency-Domain Channel Extrapolation Across Near-Field and Far-Field Scenarios Deep learning assisted mmWave beam prediction for heterogeneous networks: A dual- band fusion approach,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T10:07:01.688322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 716c20e5-80c2-476e-bc08-00f0bd45a119 · outbound

This paper cites Deep learning assisted calibrated beam training for millimeter-wave communication systems.

Unified Generalization for Frequency-Domain Channel Extrapolation Across Near-Field and Far-Field Scenarios Deep learning assisted calibrated beam training for millimeter-wave communication systems

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T10:07:01.665130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 2c58e48e-71d1-4744-ba87-2725396e05a8 · outbound

This paper cites Compressive sensing with prior support quality information and application to massive MIMO channel estima- tion with temporal correlation,.

Unified Generalization for Frequency-Domain Channel Extrapolation Across Near-Field and Far-Field Scenarios Compressive sensing with prior support quality information and application to massive MIMO channel estima- tion with temporal correlation,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T10:07:01.676133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 38f15e4f-e832-4f11-b8a7-06f28a7c3297 · outbound

This paper cites Far- field to near-field: Experimental studies of MIMO channel characteri- zation and modeling in the 6 GHz band,.

Unified Generalization for Frequency-Domain Channel Extrapolation Across Near-Field and Far-Field Scenarios Far- field to near-field: Experimental studies of MIMO channel characteri- zation and modeling in the 6 GHz band,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T10:07:01.674292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 3b7745ed-f642-4c55-85ef-52d5e88d9b0e · outbound

This paper cites Near-field wideband beamforming for extremely large antenna arrays,.

Unified Generalization for Frequency-Domain Channel Extrapolation Across Near-Field and Far-Field Scenarios Near-field wideband beamforming for extremely large antenna arrays,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T10:07:01.630969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 7d73f65e-1136-4029-962e-cb15cfbddf0f · outbound

This paper cites Fraunhofer and Fresnel distances: Unified derivation for aperture antennas,.

Unified Generalization for Frequency-Domain Channel Extrapolation Across Near-Field and Far-Field Scenarios Fraunhofer and Fresnel distances: Unified derivation for aperture antennas,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T10:07:01.661516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a660ad5e-b9c2-4990-bc47-81e732206bbf · outbound

This paper cites Channel estimation for extremely large-scale MIMO: Far-field or near-field?.

Unified Generalization for Frequency-Domain Channel Extrapolation Across Near-Field and Far-Field Scenarios Channel estimation for extremely large-scale MIMO: Far-field or near-field?

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T10:07:01.677949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 2b19df3a-19b3-4cd9-998c-f2b4f19d8b03 · outbound

This paper cites Unifying far-field and near- field wireless communications in 6G MIMO,.

Unified Generalization for Frequency-Domain Channel Extrapolation Across Near-Field and Far-Field Scenarios Unifying far-field and near- field wireless communications in 6G MIMO,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T10:07:01.655162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 297b8807-0cd7-4a12-a664-e0639e50cd61 · outbound

This paper cites Tracking FDD massive MIMO downlink channels by exploiting delay and angular reciprocity,.

Unified Generalization for Frequency-Domain Channel Extrapolation Across Near-Field and Far-Field Scenarios Tracking FDD massive MIMO downlink channels by exploiting delay and angular reciprocity,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T10:07:01.659479Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation e81ee062-6a69-4952-b1b8-f656f5217f05 · outbound

This paper cites Deep learning for TDD and FDD Massive MIMO: Mapping channels in space and frequency,.

Unified Generalization for Frequency-Domain Channel Extrapolation Across Near-Field and Far-Field Scenarios Deep learning for TDD and FDD Massive MIMO: Mapping channels in space and frequency,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T10:07:01.663321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 974cf901-2726-4066-a9bd-3ac8265a9dd4 · outbound

This paper cites Time- frequency-space joint extrapolation for 6G near-field non-stationary massive MIMO channels,.

Unified Generalization for Frequency-Domain Channel Extrapolation Across Near-Field and Far-Field Scenarios Time- frequency-space joint extrapolation for 6G near-field non-stationary massive MIMO channels,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T10:07:01.651196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 46881d52-fe9b-4587-9a23-45750e7c1dd5 · outbound

This paper cites Deep learning for fading channel prediction,.

Unified Generalization for Frequency-Domain Channel Extrapolation Across Near-Field and Far-Field Scenarios Deep learning for fading channel prediction,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T10:07:01.630833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 3139069c-b4a7-4733-a564-96d78a36b7cf · outbound

This paper cites Loss function fusion for learning-based CSI extrapolation enhancement,.

Unified Generalization for Frequency-Domain Channel Extrapolation Across Near-Field and Far-Field Scenarios Loss function fusion for learning-based CSI extrapolation enhancement,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T10:07:01.639874Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 575f60ef-864b-42d1-927d-793ea0becacd · outbound

This paper cites Path evolution model for endogenous channel digital twin toward 6G wireless networks,.

Unified Generalization for Frequency-Domain Channel Extrapolation Across Near-Field and Far-Field Scenarios Path evolution model for endogenous channel digital twin toward 6G wireless networks,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T10:07:01.632541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a01132f9-9e62-4053-b851-e4c0c0c461f2 · outbound

This paper cites Generalizable learning for frequency-domain channel extrapolation under distribution shift,.

Unified Generalization for Frequency-Domain Channel Extrapolation Across Near-Field and Far-Field Scenarios Generalizable learning for frequency-domain channel extrapolation under distribution shift,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T10:07:01.670779Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 8ddbe044-c403-469e-8287-cf09a90ae614 · outbound

This paper cites Deep learning for efficient CSI feedback in massive MIMO: Adapting to new environments and small datasets,.

Unified Generalization for Frequency-Domain Channel Extrapolation Across Near-Field and Far-Field Scenarios Deep learning for efficient CSI feedback in massive MIMO: Adapting to new environments and small datasets,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T10:07:01.690181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 2dd84cb8-e1be-4819-9863-889d98521b38 · outbound

This paper cites AI enlightens wireless communication: A transformer backbone for CSI feedback,.

Unified Generalization for Frequency-Domain Channel Extrapolation Across Near-Field and Far-Field Scenarios AI enlightens wireless communication: A transformer backbone for CSI feedback,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T10:07:01.657095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 06160196-53dc-4b72-9b31-b36ed76fdbf4 · outbound

This paper cites User-centric online gossip training for autoencoder-based CSI feedback,.

Unified Generalization for Frequency-Domain Channel Extrapolation Across Near-Field and Far-Field Scenarios User-centric online gossip training for autoencoder-based CSI feedback,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T10:07:01.666981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 3ffc1fa7-24ec-4bbb-af33-e106aa1a26b2 · outbound

This paper cites HORCRUX: Accurate cross band channel prediction,.

Unified Generalization for Frequency-Domain Channel Extrapolation Across Near-Field and Far-Field Scenarios HORCRUX: Accurate cross band channel prediction,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T10:07:01.644423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 8ba6619c-c2f7-4b6a-a336-dc357975a040 · outbound

This paper cites Wavenumber domain beam training in XL-MIMO systems: Unifying far-field and near-field,.

Unified Generalization for Frequency-Domain Channel Extrapolation Across Near-Field and Far-Field Scenarios Wavenumber domain beam training in XL-MIMO systems: Unifying far-field and near-field,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T10:07:01.641953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 8c538464-84f3-45a4-8081-00aa906577cd · outbound

This paper cites Deep learning empowered CSI acquisition and feedback for B5G wireless systems,.

Unified Generalization for Frequency-Domain Channel Extrapolation Across Near-Field and Far-Field Scenarios Deep learning empowered CSI acquisition and feedback for B5G wireless systems,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T10:07:01.646612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 2083b9f9-40f4-4e4e-a4f9-59a0c170caaf · outbound

This paper cites Generalizable learning for massive MIMO CSI feedback in unseen environments,.

Unified Generalization for Frequency-Domain Channel Extrapolation Across Near-Field and Far-Field Scenarios Generalizable learning for massive MIMO CSI feedback in unseen environments,

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-06-30T09:04:32.903367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a6388b2a-dd45-4ba0-bdb5-d74d14db1a49 · outbound

This paper cites Massive MIMO channels with inter-user angle correlation: Open-access dataset, analysis and measurement-based validation,.

Unified Generalization for Frequency-Domain Channel Extrapolation Across Near-Field and Far-Field Scenarios Massive MIMO channels with inter-user angle correlation: Open-access dataset, analysis and measurement-based validation,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T10:07:01.649006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 6453ebed-0285-4de7-9532-8b62e3ca618f · outbound

This paper cites CSI Dataset espargos- 0002: Larger combined antenna array, indoor lab room with metal wall, LoS and NLoS areas,.

Unified Generalization for Frequency-Domain Channel Extrapolation Across Near-Field and Far-Field Scenarios CSI Dataset espargos- 0002: Larger combined antenna array, indoor lab room with metal wall, LoS and NLoS areas,

Reference 28

Resolution: verified exact; doi, observed 2026-06-30T09:04:32.376828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 30f03a14-aa21-4b1b-b04b-667bd2d10f6c · outbound

This paper cites WAIR-D: Wireless AI Research Dataset.

Unified Generalization for Frequency-Domain Channel Extrapolation Across Near-Field and Far-Field Scenarios WAIR-D: Wireless AI Research Dataset

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-06-30T09:04:32.905770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation ae6bfe98-2af8-4989-a271-a1157eeda97d · outbound

This paper cites Optshrink: An algorithm for improved low-rank sig- nal matrix denoising by optimal, data-driven singular value shrinkage,.

Unified Generalization for Frequency-Domain Channel Extrapolation Across Near-Field and Far-Field Scenarios Optshrink: An algorithm for improved low-rank sig- nal matrix denoising by optimal, data-driven singular value shrinkage,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T10:07:01.639641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Pith citing papers

No inbound Pith citation observations are available.