Paper Citation Record · LEDGER

On-board AI-based Channel Estimation for LEO NTNs

As of 17 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2607.15127.

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

pith.paper-citation-record.v1
2607.15127 v1

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T00:07:50.830707Z

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

18 of 18 outbound references displayed

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verified fuzzy0
unresolved18
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malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7713ab5d-eb60-4764-bf28-edb1e9a95388 · outbound

This paper cites Design of a standard-compliant real-time neural receiver for 5G NR,.

On-board AI-based Channel Estimation for LEO NTNs Design of a standard-compliant real-time neural receiver for 5G NR,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-02T00:07:49.277548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9786118a-4d84-4fc7-9f49-6923d2082e27 · outbound

This paper cites Deeprx: Fully convolutional deep learning receiver,.

On-board AI-based Channel Estimation for LEO NTNs Deeprx: Fully convolutional deep learning receiver,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-02T00:07:49.404482Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c2dbd2da-e13b-4db8-815f-4a7fc6170111 · outbound

This paper cites Eqdeeprx: Learning a scalable mimo receiver,.

On-board AI-based Channel Estimation for LEO NTNs Eqdeeprx: Learning a scalable mimo receiver,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-02T00:07:49.551339Z

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Observation 815e664a-11c0-4ae7-a70d-48d1f3aeaa6b · outbound

This paper cites 3GPP highlights issue 7,.

On-board AI-based Channel Estimation for LEO NTNs 3GPP highlights issue 7,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-02T00:07:49.782079Z

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Observation b9d69563-4c03-405a-b076-93407e751521 · outbound

This paper cites Recommendation itu-r m.2160-0: Framework and overall objectives of the future development of imt for 2030 and beyond,.

On-board AI-based Channel Estimation for LEO NTNs Recommendation itu-r m.2160-0: Framework and overall objectives of the future development of imt for 2030 and beyond,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-02T00:07:49.879852Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 11be46c1-e488-4250-8ab8-38c43f0af08f · outbound

This paper cites The path to 5g-advanced and 6g non-terrestrial network systems,.

On-board AI-based Channel Estimation for LEO NTNs The path to 5g-advanced and 6g non-terrestrial network systems,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-02T00:07:49.932607Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 698395c8-cdcf-45e2-9b2a-b48f8e9470ec · outbound

This paper cites Channel prediction with temporal convolutional networks: A new paradigm to enable non- orthogonal multiple access in 6g ntn,.

On-board AI-based Channel Estimation for LEO NTNs Channel prediction with temporal convolutional networks: A new paradigm to enable non- orthogonal multiple access in 6g ntn,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-02T00:07:49.994369Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 86857d68-b12f-4a8a-bd0a-b3abdea5193b · outbound

This paper cites Revolutionizing future connectivity: A contemporary survey on ai-empowered satellite-based non-terrestrial networks in 6g,.

On-board AI-based Channel Estimation for LEO NTNs Revolutionizing future connectivity: A contemporary survey on ai-empowered satellite-based non-terrestrial networks in 6g,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-02T00:07:50.068294Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5299dcf1-1286-43ac-bdd5-0a2a09672c71 · outbound

This paper cites Enhanced 6g non-terrestrial network link performance using deep learning-based channel estimation and doppler compensation techniques,.

On-board AI-based Channel Estimation for LEO NTNs Enhanced 6g non-terrestrial network link performance using deep learning-based channel estimation and doppler compensation techniques,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-02T00:07:50.147278Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 52e69d9e-80a0-4431-8bdb-f87aa53ef0fc · outbound

This paper cites A compute&memory efficient model-driven neural 5G receiver for edge AI-assisted RAN,.

On-board AI-based Channel Estimation for LEO NTNs A compute&memory efficient model-driven neural 5G receiver for edge AI-assisted RAN,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-02T00:07:50.203223Z

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Observation 241ef510-f02c-41c4-8115-7f1aecac4e64 · outbound

This paper cites QuaDRiGa: A 3- D multi-cell channel model with time evolution for enabling virtual field trials,.

On-board AI-based Channel Estimation for LEO NTNs QuaDRiGa: A 3- D multi-cell channel model with time evolution for enabling virtual field trials,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-02T00:07:50.288207Z

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Unavailable: canonical work link unavailable.

Observation a963fb4a-e670-4ba0-9ec2-d4140f527f05 · outbound

This paper cites Solutions for NR to support Non-Terrestrial Networks (NTN),.

On-board AI-based Channel Estimation for LEO NTNs Solutions for NR to support Non-Terrestrial Networks (NTN),

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-02T00:07:50.373127Z

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Observation c1412bf4-5dcf-4d46-86a4-2363631bf398 · outbound

This paper cites Lmmse channel estimation in ofdm context: a review,.

On-board AI-based Channel Estimation for LEO NTNs Lmmse channel estimation in ofdm context: a review,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-02T00:07:50.434404Z

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Observation 57a970b6-4696-40aa-bbdd-a5dac9d5dddc · outbound

This paper cites Designing Network Design Strategies Through Gradient Path Analysis.

On-board AI-based Channel Estimation for LEO NTNs Designing Network Design Strategies Through Gradient Path Analysis

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-02T00:07:50.482544Z

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Observation 07eb4a30-06ae-4f43-aba7-955941f9b546 · outbound

This paper cites YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors,.

On-board AI-based Channel Estimation for LEO NTNs YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-02T00:07:50.506424Z

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Unavailable: canonical work link unavailable.

Observation 57ef63a7-1522-46b6-9bad-14308c1b99e3 · outbound

This paper cites Xception: Deep learning with depthwise separable convolu- tions,.

On-board AI-based Channel Estimation for LEO NTNs Xception: Deep learning with depthwise separable convolu- tions,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-02T00:07:50.574979Z

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Observation 37822e29-fa5c-438f-a745-873d289b72d8 · outbound

This paper cites Sionna: An Open-Source Library for Next-Generation Physical Layer Research.

On-board AI-based Channel Estimation for LEO NTNs Sionna: An Open-Source Library for Next-Generation Physical Layer Research

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-02T00:07:50.687363Z

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Unavailable: canonical work link unavailable.

Observation aa19d304-964a-40d0-866c-0691e413efe0 · outbound

This paper cites Available: https://github.com/Mahdi-Abdollahpour/mdx.

On-board AI-based Channel Estimation for LEO NTNs Available: https://github.com/Mahdi-Abdollahpour/mdx

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-02T00:07:50.830707Z

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Pith citing papers

No inbound Pith citation observations are available.