Paper Citation Record · LEDGER

DeepTelecom: A Digital-Twin Deep Learning Dataset for Channel and MIMO Applications

As of 21 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 1 inbound Pith citation observation for arXiv:2508.14507.

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

pith.paper-citation-record.v1
2508.14507 v1

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T18:32:01.702556Z

measured 21 of 21 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-12T01:58:56.905017Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T02:01:15.219598Z

Reference resolution

20 of 20 outbound references displayed

verified exact1
verified fuzzy15
unresolved4
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a190d4ac-d119-460e-bbc5-c26495750251 · outbound

This paper cites Large-Scale AI in Telecom: Charting the Roadmap for Innovation, Scalability, and Enhanced Digital Experiences.

DeepTelecom: A Digital-Twin Deep Learning Dataset for Channel and MIMO Applications Large-Scale AI in Telecom: Charting the Roadmap for Innovation, Scalability, and Enhanced Digital Experiences

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-05T18:32:00.176272Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e90e19c5-ac29-4c54-bae6-a4bc2b2e73e1 · outbound

This paper cites Wireless large AI model: shaping the AI-empowered future of 6G and beyond.

DeepTelecom: A Digital-Twin Deep Learning Dataset for Channel and MIMO Applications Wireless large AI model: shaping the AI-empowered future of 6G and beyond

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-05T18:32:00.228906Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 719d956d-0d75-4a79-8216-1a7c44f95e94 · outbound

This paper cites A survey of efficient ray-tracing techniques for mobile radio propagation analysis,.

DeepTelecom: A Digital-Twin Deep Learning Dataset for Channel and MIMO Applications A survey of efficient ray-tracing techniques for mobile radio propagation analysis,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:32:02.170418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d4e33d26-8b25-456f-a6c0-09a0e37a2f74 · outbound

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

DeepTelecom: A Digital-Twin Deep Learning Dataset for Channel and MIMO Applications WAIR-D: Wireless AI Research Dataset

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-05T18:32:00.363220Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1eaad936-4dcf-4ea7-a051-c562bc3a42ee · outbound

This paper cites BUPTCMCC-6G-DataAI+: A generative channel dataset for 6G AI air interface research.

DeepTelecom: A Digital-Twin Deep Learning Dataset for Channel and MIMO Applications BUPTCMCC-6G-DataAI+: A generative channel dataset for 6G AI air interface research

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-08-05T18:32:01.917843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e2388bf1-311b-4882-b7f3-78aa85ff7e47 · outbound

This paper cites DataAI-6G: a system parameters configurable channel dataset for AI-6G research,.

DeepTelecom: A Digital-Twin Deep Learning Dataset for Channel and MIMO Applications DataAI-6G: a system parameters configurable channel dataset for AI-6G research,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:32:02.159771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4872826e-7485-49bb-9012-665ffa77814c · outbound

This paper cites Pervasive wireless channel modeling theory and applications to 6G GBSMs for all frequency bands and all scenarios,.

DeepTelecom: A Digital-Twin Deep Learning Dataset for Channel and MIMO Applications Pervasive wireless channel modeling theory and applications to 6G GBSMs for all frequency bands and all scenarios,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:32:02.149182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b054d9c5-1b9c-4d44-a598-85b4dae6cddf · outbound

This paper cites A complete study of space- time-frequency statistical properties of the 6G pervasive channel model,.

DeepTelecom: A Digital-Twin Deep Learning Dataset for Channel and MIMO Applications A complete study of space- time-frequency statistical properties of the 6G pervasive channel model,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:32:02.138411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e6287300-8724-4e7f-9119-4db765c9122d · outbound

This paper cites M 3SC: A generic dataset for mixed multi-modal (MMM) sensing and communication integration,.

DeepTelecom: A Digital-Twin Deep Learning Dataset for Channel and MIMO Applications M 3SC: A generic dataset for mixed multi-modal (MMM) sensing and communication integration,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:32:02.127679Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 38b585fb-5fb7-42d1-85ed-6e7df4f658d2 · outbound

This paper cites DeepMIMO: A Generic Deep Learning Dataset for Millimeter Wave and Massive MIMO Applications.

DeepTelecom: A Digital-Twin Deep Learning Dataset for Channel and MIMO Applications DeepMIMO: A Generic Deep Learning Dataset for Millimeter Wave and Massive MIMO Applications

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-05T18:32:00.791815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3eac277d-3671-4b5e-8c72-907cb5b0c26a · outbound

This paper cites ViWi: A deep learning dataset framework for vision-aided wireless communications,.

DeepTelecom: A Digital-Twin Deep Learning Dataset for Channel and MIMO Applications ViWi: A deep learning dataset framework for vision-aided wireless communications,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:32:02.116574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f571357b-c930-43dc-91bd-126ab1e04144 · outbound

This paper cites WiTh- Ray: A versatile ray-tracing simulator for smart wireless environments,.

DeepTelecom: A Digital-Twin Deep Learning Dataset for Channel and MIMO Applications WiTh- Ray: A versatile ray-tracing simulator for smart wireless environments,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:32:02.106332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4e90671b-0c30-479e-86f3-2c543e2b7b4b · outbound

This paper cites Sionna: An open-source library for next-generation physical layer research,.

DeepTelecom: A Digital-Twin Deep Learning Dataset for Channel and MIMO Applications Sionna: An open-source library for next-generation physical layer research,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:32:02.095569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 565fa9a0-2ae2-4514-8d05-ca7c4f6aa7b8 · outbound

This paper cites Integrated optical sensing, communication, and computation system for quadruped robots,.

DeepTelecom: A Digital-Twin Deep Learning Dataset for Channel and MIMO Applications Integrated optical sensing, communication, and computation system for quadruped robots,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:32:02.085463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5e1c21a0-9e85-466f-ac7f-ae1b2fcd2bb8 · outbound

This paper cites Real-time 3D reconstruction in dynamic scenes using point-based fusion,.

DeepTelecom: A Digital-Twin Deep Learning Dataset for Channel and MIMO Applications Real-time 3D reconstruction in dynamic scenes using point-based fusion,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:32:02.074109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3ca5c9e8-27df-480a-96c3-c8b1a034238a · outbound

This paper cites Stochastic learning-based robust beamforming design for RIS-aided millimeter-wave systems in the presence of random blockages,.

DeepTelecom: A Digital-Twin Deep Learning Dataset for Channel and MIMO Applications Stochastic learning-based robust beamforming design for RIS-aided millimeter-wave systems in the presence of random blockages,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:32:02.062177Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 1fb65d8c-5997-4ada-982e-1b83ac5a4376 · outbound

This paper cites Multi-sources information fusion learning for multi- points NLOS localization,.

DeepTelecom: A Digital-Twin Deep Learning Dataset for Channel and MIMO Applications Multi-sources information fusion learning for multi- points NLOS localization,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:32:02.051342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation af2926d3-2335-4ab4-80e8-561ca4fd74fc · outbound

This paper cites Multi-sources fusion learning for multi-points NLOS localization in OFDM system,.

DeepTelecom: A Digital-Twin Deep Learning Dataset for Channel and MIMO Applications Multi-sources fusion learning for multi-points NLOS localization in OFDM system,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:32:02.039286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 83db3c9b-55a9-4471-82b5-cda8c718385b · outbound

This paper cites Robust millimeter beamforming via self- supervised hybrid deep learning,.

DeepTelecom: A Digital-Twin Deep Learning Dataset for Channel and MIMO Applications Robust millimeter beamforming via self- supervised hybrid deep learning,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:32:02.026176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9fc6e8da-e915-4f6d-a981-eb2b58e73ee5 · outbound

This paper cites Robust Deep Learning-Based Physical Layer Communications: Strategies and Approaches,.

DeepTelecom: A Digital-Twin Deep Learning Dataset for Channel and MIMO Applications Robust Deep Learning-Based Physical Layer Communications: Strategies and Approaches,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:32:02.015115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Pith citing papers

Observation 5d9a1b8f-7bad-46b2-8f8d-425032039714 · inbound

Fidelity Where it Matters: Site-Specific Nonuniform Refinement for Wireless Digital Twins cites this paper.

Fidelity Where it Matters: Site-Specific Nonuniform Refinement for Wireless Digital Twins DeepTelecom: A Digital-Twin Deep Learning Dataset for Channel and MIMO Applications

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-12T02:01:15.221566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.