Paper Citation Record · LEDGER

A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks

As of 16 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2608.01840.

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

pith.paper-citation-record.v1
2608.01840 v1

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T19:54:34.651037Z

measured 45 of 45 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

45 of 45 outbound references displayed

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verified fuzzy0
unresolved45
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 78dd8867-6918-40e2-94f3-e0c167c53e9d · outbound

This paper cites Study on channel model for frequencies from 0.5 to 100 ghz,.

A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks Study on channel model for frequencies from 0.5 to 100 ghz,

Reference 1

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Observation ec0d61bb-a459-4659-8e3c-9fd6b03e2764 · outbound

This paper cites TR 36.777, 3rd generation partnership project; technical speci- fication group radio access network; study on enhanced lte support for aerial vehicles,.

A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks TR 36.777, 3rd generation partnership project; technical speci- fication group radio access network; study on enhanced lte support for aerial vehicles,

Reference 2

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Observation 34f45a41-7c6c-499e-ae28-51887d1b1dee · outbound

This paper cites TR 38.811,3rd generation partnership project; technical specifi- cation group radio access network; study on new radio (nr) to support non-terrestrial networks,.

A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks TR 38.811,3rd generation partnership project; technical specifi- cation group radio access network; study on new radio (nr) to support non-terrestrial networks,

Reference 3

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Observation c737b9ce-de4f-4f5b-9f9d-bb781b4cbae5 · outbound

This paper cites an unresolved cited work.

A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks Unresolved cited work

Reference 4

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Observation 9666359f-6481-4d6d-9ec6-8494a67c4930 · outbound

This paper cites Ray-optical modeling of wireless coverage enhancement using engi- neered electromagnetic surfaces: Experimental verification at 28 ghz,.

A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks Ray-optical modeling of wireless coverage enhancement using engi- neered electromagnetic surfaces: Experimental verification at 28 ghz,

Reference 5

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Observation 3b1ab1c8-b2ca-40a0-80e1-01f916a82a49 · outbound

This paper cites Millimetre Waves:Modelling and Simulation to Engineer for Coverage,.

A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks Millimetre Waves:Modelling and Simulation to Engineer for Coverage,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-04T19:54:34.548531Z

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Observation 631ccbce-8cbb-4b50-bdc1-7ac79da1a6e5 · outbound

This paper cites Yin and X.

A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks Yin and X

Reference 7

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Observation 2d64096b-1f29-455f-97b5-0772e1a13fae · outbound

This paper cites A statistical model of mobile-to-mobile land communication channel,.

A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks A statistical model of mobile-to-mobile land communication channel,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-04T19:54:34.554478Z

Source-reported events for the cited work

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Observation e3ad7fff-55f3-4306-9427-73e27084c2cb · outbound

This paper cites Modeling, analysis, and simulation of mimo mobile-to-mobile fading channels,.

A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks Modeling, analysis, and simulation of mimo mobile-to-mobile fading channels,

Reference 9

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Source-reported events for the cited work

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Observation 9760d94d-dfb8-4c37-ac12-40664e0842fb · outbound

This paper cites An adaptive geometry-based stochastic model for non-isotropic mimo mobile-to-mobile channels,.

A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks An adaptive geometry-based stochastic model for non-isotropic mimo mobile-to-mobile channels,

Reference 10

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Observation bb04ba44-eaf7-4084-b13d-374bcd02f7a5 · outbound

This paper cites Space-time correlated mobile-to-mobile channels: Modelling and simulation,.

A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks Space-time correlated mobile-to-mobile channels: Modelling and simulation,

Reference 11

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Source-reported events for the cited work

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Observation 22982a9f-3d37-4bc3-832e-9e343b2f1755 · outbound

This paper cites Statistical characteristics of measured mimo wireless channel data and comparison to conventional models,.

A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks Statistical characteristics of measured mimo wireless channel data and comparison to conventional models,

Reference 12

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Observation fe7cda54-3c7c-4895-905a-8de542b41d60 · outbound

This paper cites Impact of clustering in statistical indoor propagation models on link capacity,.

A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks Impact of clustering in statistical indoor propagation models on link capacity,

Reference 13

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Observation ca32a491-5337-4708-a750-8efd15169b42 · outbound

This paper cites Geometry- based stochastic channel model for high-speed railway communications,.

A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks Geometry- based stochastic channel model for high-speed railway communications,

Reference 14

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Observation 97eb05c1-56c5-40a4-abe8-4fd2ad1bdd1f · outbound

This paper cites A geometry-based stochastic mimo model for vehicle-to-vehicle communications,.

A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks A geometry-based stochastic mimo model for vehicle-to-vehicle communications,

Reference 15

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Observation e6ef11ee-7e8b-48c8-ae53-f8032612f792 · outbound

This paper cites Geometry-based stochastic channel model for two-story lobby environment at 10 ghz,.

A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks Geometry-based stochastic channel model for two-story lobby environment at 10 ghz,

Reference 16

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Observation 8d23f5f8-ce61-40a9-9c9a-b76a714dc89c · outbound

This paper cites A geometry-based stochastic channel model for the millimeter-wave band in a 3gpp high-speed train scenario,.

A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks A geometry-based stochastic channel model for the millimeter-wave band in a 3gpp high-speed train scenario,

Reference 17

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Observation cf668e8e-556f-471e-af4a-2aa96db068bf · outbound

This paper cites Generative- adversarial-network-based wireless channel modeling: Challenges and opportunities,.

A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks Generative- adversarial-network-based wireless channel modeling: Challenges and opportunities,

Reference 18

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Unavailable: canonical work link unavailable.

Observation bdabf0da-0576-4300-a8b9-5ce560cd4186 · outbound

This paper cites Mimo-gan: Generative mimo channel modeling,.

A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks Mimo-gan: Generative mimo channel modeling,

Reference 19

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Observation c0eb8898-56bf-4fc6-9998-90f4e2d3add7 · outbound

This paper cites Generative neural network channel modeling for millimeter-wave uav communication,.

A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks Generative neural network channel modeling for millimeter-wave uav communication,

Reference 20

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Observation 9647b40d-a089-4cf7-b9d5-3a543f23820e · outbound

This paper cites Multi-frequency channel modeling for millimeter wave and thz wireless communication via generative adversarial networks,.

A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks Multi-frequency channel modeling for millimeter wave and thz wireless communication via generative adversarial networks,

Reference 21

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Source-reported events for the cited work

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Observation abc579ac-ee26-4f25-b37c-01c30855a790 · outbound

This paper cites Channelgan: Deep learning- based channel modeling and generating,.

A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks Channelgan: Deep learning- based channel modeling and generating,

Reference 22

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Source-reported events for the cited work

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Observation 609473a1-59ea-4df1-91e0-3ec517a0bedf · outbound

This paper cites Propagation Channel Modeling by Deep learning Techniques.

A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks Propagation Channel Modeling by Deep learning Techniques

Reference 23

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Source-reported events for the cited work

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Observation 74fa8e5c-db6c-4778-b65b-008f9af2aff9 · outbound

This paper cites Addressing posterior collapse with mutual information for improved variational neural ma- chine translation,.

A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks Addressing posterior collapse with mutual information for improved variational neural ma- chine translation,

Reference 24

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Observation 5386bf1b-c5cf-49f3-8edb-4a2950020e9b · outbound

This paper cites Tse and P.

A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks Tse and P

Reference 25

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Source-reported events for the cited work

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Observation 05d289d0-ce3d-402d-9870-b48a6e45459c · outbound

This paper cites an unresolved cited work.

A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks Unresolved cited work

Reference 26

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Observation 4e8c5a53-fb42-4a3e-863a-0be3bfb91348 · outbound

This paper cites Remcomm [online],.

A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks Remcomm [online],

Reference 27

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Observation c2607f65-4d7a-40d5-9e75-5fd5af1d68d5 · outbound

This paper cites Imagenet-trained cnns are biased towards texture; in- creasing shape bias improves accuracy and robustness,.

A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks Imagenet-trained cnns are biased towards texture; in- creasing shape bias improves accuracy and robustness,

Reference 28

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Observation d6c5c251-00ba-4015-86e5-5fdd8d2e5b27 · outbound

This paper cites Wasserstein generative ad- versarial networks,.

A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks Wasserstein generative ad- versarial networks,

Reference 29

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Observation a426e51f-c470-4c6a-be0c-0b98d77c2307 · outbound

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A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks Generative adversarial nets,

Reference 30

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Observation 57d7e8f5-60f1-46ee-9c0c-e3619b509f19 · outbound

This paper cites Villani et al.

A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks Villani et al

Reference 31

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Source-reported events for the cited work

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Observation 48de964e-7268-473f-bd7c-02b68b8abfb6 · outbound

This paper cites Improved training of wasserstein gans,.

A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks Improved training of wasserstein gans,

Reference 32

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Source-reported events for the cited work

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Observation 77eddbc6-cb44-4144-96c1-66edc3a4e0af · outbound

This paper cites Geometry-based stochastic wireless channel mod- eling GitHub repository,.

A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks Geometry-based stochastic wireless channel mod- eling GitHub repository,

Reference 33

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Source-reported events for the cited work

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Observation 2a854658-91a3-462c-bc64-0d296a7c7743 · outbound

This paper cites FCC seeks comment on maximizing efficient use of 12 GHz band,.

A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks FCC seeks comment on maximizing efficient use of 12 GHz band,

Reference 34

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Observation 21b33290-e948-49d8-a5b9-a13c09153a9e · outbound

This paper cites 6G working group position paper,.

A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks 6G working group position paper,

Reference 35

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This paper cites Cellular wireless networks in the upper mid-band,.

A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks Cellular wireless networks in the upper mid-band,

Reference 36

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Observation cae40f85-a73e-4c31-a863-8d8a2e07e374 · outbound

This paper cites Electrical characteristics of the surface of the earth,.

A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks Electrical characteristics of the surface of the earth,

Reference 37

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Source-reported events for the cited work

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Observation 97dd801c-8279-4dc3-a45e-4e356ffc1245 · outbound

This paper cites Effects of building materials and structures on radiowave prop- agation above about 100 mhz,.

A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks Effects of building materials and structures on radiowave prop- agation above about 100 mhz,

Reference 38

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A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks Multipath propagation and parameterization of its characteristics,

Reference 39

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Observation 5e17aede-153f-4f21-8d61-862d9df2290e · outbound

This paper cites Correlation matrix distance, a meaningful measure for evaluation of non-stationary mimo channels,.

A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks Correlation matrix distance, a meaningful measure for evaluation of non-stationary mimo channels,

Reference 40

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This paper cites Spatially consistent air-to-ground channel modeling via generative neural networks,.

A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks Spatially consistent air-to-ground channel modeling via generative neural networks,

Reference 41

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This paper cites Millimeter-wave uav coverage in ur- ban environments,.

A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks Millimeter-wave uav coverage in ur- ban environments,

Reference 42

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Source-reported events for the cited work

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This paper cites Study of Radio Frequency (RF) and Electromagnetic Compati- bility (EMC) requirements for Active Antenna Array System (AAS) base station,.

A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks Study of Radio Frequency (RF) and Electromagnetic Compati- bility (EMC) requirements for Active Antenna Array System (AAS) base station,

Reference 43

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Observation 6d75d9e8-096e-4986-ad1a-77ea4ba9bc77 · outbound

This paper cites Available: https://www.fcc.gov/document/fcc-seeks- comment-maximizing-efficient-use-12-ghz-band.

A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks Available: https://www.fcc.gov/document/fcc-seeks- comment-maximizing-efficient-use-12-ghz-band

Reference 2021

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This paper cites Available: https://www.fcc.gov/sites/default/files/ Consolidated_6G_Paper_FCCTAC23_Final_for_Web.pdf.

A Geometry-based Stochastic Wireless Channel Model using Generative Neural Networks Available: https://www.fcc.gov/sites/default/files/ Consolidated_6G_Paper_FCCTAC23_Final_for_Web.pdf

Reference 2023

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Pith citing papers

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