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Paper Citation Record · LEDGER

Deep Learning for Joint Narrowband Interference Cancellation and Soft Demodulation in OFDM Systems

As of 11 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2607.08717.

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

pith.paper-citation-record.v1
2607.08717 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-10T02:40:21.675520Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+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

35 of 35 outbound references displayed

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  • verified fuzzy34
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 205cdcc3-909f-495e-82ff-f629d2a4710f · outbound

This paper cites Interference management issues for the future 5G network: A review,.

Deep Learning for Joint Narrowband Interference Cancellation and Soft Demodulation in OFDM Systems Interference management issues for the future 5G network: A review,

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation ed6aa7e8-bb5a-4efa-934f-ca68e0d10f82 · outbound

This paper cites URLLC in Beyond 5G and 6G Networks: An Interference Management Perspective,.

Deep Learning for Joint Narrowband Interference Cancellation and Soft Demodulation in OFDM Systems URLLC in Beyond 5G and 6G Networks: An Interference Management Perspective,

Reference 2

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 8d0a59e5-9da3-4962-9207-e033f65a5862 · outbound

This paper cites From 5G to 6G Networks: A Survey on AI-Based Jamming and Interference Detection and Mitigation,.

Deep Learning for Joint Narrowband Interference Cancellation and Soft Demodulation in OFDM Systems From 5G to 6G Networks: A Survey on AI-Based Jamming and Interference Detection and Mitigation,

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 1e0c8867-6a0a-4aed-8705-2a3ba536f5d4 · outbound

This paper cites A Systematic Review of Interference Mitigation Techniques in Current and Future UA V-Assisted Wireless Networks,.

Deep Learning for Joint Narrowband Interference Cancellation and Soft Demodulation in OFDM Systems A Systematic Review of Interference Mitigation Techniques in Current and Future UA V-Assisted Wireless Networks,

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 760f37b8-092e-4d16-9334-321d7442ddc5 · outbound

This paper cites Integrating Terrestrial and Satellite Multibeam Systems Toward 6G: Techniques and Challenges for Interference Mitigation,.

Deep Learning for Joint Narrowband Interference Cancellation and Soft Demodulation in OFDM Systems Integrating Terrestrial and Satellite Multibeam Systems Toward 6G: Techniques and Challenges for Interference Mitigation,

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 886b5a2f-8ddc-4745-afb8-b24033c85138 · outbound

This paper cites Interference Management for Integrated Sensing and Communication Systems: A Survey,.

Deep Learning for Joint Narrowband Interference Cancellation and Soft Demodulation in OFDM Systems Interference Management for Integrated Sensing and Communication Systems: A Survey,

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-07-10T02:40:21.675520Z digest=sha256:0687889a7b90a7c96e8b81848ca3298ab834a8fa73cfd21cf5c4fec2de8fdb43

Observation f69166f0-c595-417a-8365-33d3e6bfd46e · outbound

This paper cites Interference Burden in Wireless Communi- cations: A Comprehensive Survey From PHY Layer Perspective,.

Deep Learning for Joint Narrowband Interference Cancellation and Soft Demodulation in OFDM Systems Interference Burden in Wireless Communi- cations: A Comprehensive Survey From PHY Layer Perspective,

Reference 7

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raw_fallback, observed 2026-07-10T02:46:43.274664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 862f250d-c694-45a1-8f81-68ba4751c26f · outbound

This paper cites Upper Mid-Band Spectrum for 6G: Vision, Opportunity and Challenges,.

Deep Learning for Joint Narrowband Interference Cancellation and Soft Demodulation in OFDM Systems Upper Mid-Band Spectrum for 6G: Vision, Opportunity and Challenges,

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-07-10T02:40:21.675520Z digest=sha256:2846c3bfd0ccf7d0aa2ee4496e38a732fb8feeb98db915273c2c62915d757e7c

Observation 835b737b-ac05-4ae6-a307-2c81a5a307fe · outbound

This paper cites Spectrum Sharing Across Terrestrial and Non-Terrestrial Services in the FR3 Upper Mid- band,.

Deep Learning for Joint Narrowband Interference Cancellation and Soft Demodulation in OFDM Systems Spectrum Sharing Across Terrestrial and Non-Terrestrial Services in the FR3 Upper Mid- band,

Reference 9

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation c5e56803-e484-452c-bbd1-a26d6faeba23 · outbound

This paper cites 6G Wireless Communications in 7– 24 GHz Band: Opportunities, Techniques, and Challenges,.

Deep Learning for Joint Narrowband Interference Cancellation and Soft Demodulation in OFDM Systems 6G Wireless Communications in 7– 24 GHz Band: Opportunities, Techniques, and Challenges,

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation e8d371e3-544a-459f-a09d-8b741cee7b67 · outbound

This paper cites The effect of narrowband interfer- ence on wideband wireless communication systems,.

Deep Learning for Joint Narrowband Interference Cancellation and Soft Demodulation in OFDM Systems The effect of narrowband interfer- ence on wideband wireless communication systems,

Reference 11

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raw_fallback, observed 2026-07-10T02:46:43.302540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation d29123af-4ae9-4f1c-acb2-9870baa96395 · outbound

This paper cites Narrowband interference mitigation in OFDM systems,.

Deep Learning for Joint Narrowband Interference Cancellation and Soft Demodulation in OFDM Systems Narrowband interference mitigation in OFDM systems,

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 977ed91c-c7d2-4512-a3f9-30895d59df98 · outbound

This paper cites Multiple Interacting Narrowband Interferences Suppression Algorithm for OFDM Systems,.

Deep Learning for Joint Narrowband Interference Cancellation and Soft Demodulation in OFDM Systems Multiple Interacting Narrowband Interferences Suppression Algorithm for OFDM Systems,

Reference 13

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raw_fallback, observed 2026-07-10T02:46:43.304711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-07-10T02:40:21.675520Z digest=sha256:307cc20796adf1011f79c8eea90d878376547cc969b0813aa335760da4fb5043

Observation 099105ac-b624-45bb-ae73-f238e9e93cc4 · outbound

This paper cites Narrowband Interference Mitigation Techniques: A Survey,.

Deep Learning for Joint Narrowband Interference Cancellation and Soft Demodulation in OFDM Systems Narrowband Interference Mitigation Techniques: A Survey,

Reference 14

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 5e1fa75d-d1e1-4346-9139-490a1a095965 · outbound

This paper cites Deep Learning- Based Multi-Tone Interference Suppression for Short Polar Codes,.

Deep Learning for Joint Narrowband Interference Cancellation and Soft Demodulation in OFDM Systems Deep Learning- Based Multi-Tone Interference Suppression for Short Polar Codes,

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-07-10T02:40:21.675520Z digest=sha256:71e749c81e1dd0e93a52a2bb67afae3b16df25caccd054c61005679d45dff740

Observation a29c52b1-b198-40d4-8b47-98f3306b5a4a · outbound

This paper cites Eliminating NB-IoT Interference to LTE System: A Sparse Machine Learning-Based Approach,.

Deep Learning for Joint Narrowband Interference Cancellation and Soft Demodulation in OFDM Systems Eliminating NB-IoT Interference to LTE System: A Sparse Machine Learning-Based Approach,

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation fb455b22-0a5a-4b62-80e8-7d5198d14cde · outbound

This paper cites Joint Impulsive Noise and Narrowband Inter- ference Mitigation in Time-Varying OFDM Communications,.

Deep Learning for Joint Narrowband Interference Cancellation and Soft Demodulation in OFDM Systems Joint Impulsive Noise and Narrowband Inter- ference Mitigation in Time-Varying OFDM Communications,

Reference 17

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raw_fallback, observed 2026-07-10T02:46:43.282553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-07-10T02:40:21.675520Z digest=sha256:4446f98f9909572f6d2063662d0ba7608371e5a931160a54602eb956b55125f4

Observation db6693ab-55b7-4af5-91d8-f1f14cb39fdc · outbound

This paper cites Improving Soft Decoding by Spectral Leakage Reduction in Presence of Narrow Band Interference in PLC,.

Deep Learning for Joint Narrowband Interference Cancellation and Soft Demodulation in OFDM Systems Improving Soft Decoding by Spectral Leakage Reduction in Presence of Narrow Band Interference in PLC,

Reference 18

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raw_fallback, observed 2026-07-10T02:46:43.258397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-07-10T02:40:21.675520Z digest=sha256:8fc1e1ad68125de2f8c38c49aaef42910affd3f2583cb51e3d124e0236d134df

Observation cb4cdabc-ba7b-46a9-ae9f-6b7d979b22da · outbound

This paper cites NBI Spectral Leakage Mitigation Based on Compressed Sensing in OFDM Systems,.

Deep Learning for Joint Narrowband Interference Cancellation and Soft Demodulation in OFDM Systems NBI Spectral Leakage Mitigation Based on Compressed Sensing in OFDM Systems,

Reference 19

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raw_fallback, observed 2026-07-10T02:46:43.253443Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-07-10T02:40:21.675520Z digest=sha256:4215bd4ad5a007354b0b594bb551be459da20ca15be303929c8bc7cb8ab977ea

Observation 2f31a4e2-5c61-48ab-b7d3-b408076f5c4a · outbound

This paper cites Narrowband Interference Cancellation for OFDM Based on Deep Learning and Compressed Sensing,.

Deep Learning for Joint Narrowband Interference Cancellation and Soft Demodulation in OFDM Systems Narrowband Interference Cancellation for OFDM Based on Deep Learning and Compressed Sensing,

Reference 20

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verified fuzzy
raw_fallback, observed 2026-07-10T02:46:43.299825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-07-10T02:40:21.675520Z digest=sha256:f0728e88748f264860b09dad0520fc83383dfc939cf0061c578200cea2e26d6d

Observation a443d60e-1c60-450e-8dc0-f335415dba9c · outbound

This paper cites Interference Suppression Using Deep Learning: Current Approaches and Open Chal- lenges,.

Deep Learning for Joint Narrowband Interference Cancellation and Soft Demodulation in OFDM Systems Interference Suppression Using Deep Learning: Current Approaches and Open Chal- lenges,

Reference 21

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raw_fallback, observed 2026-07-10T02:46:43.290938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-07-10T02:40:21.675520Z digest=sha256:c901c8f1c7143bfd09fd02f968c3a15ff236fb8d5c6c6f05f80011d748afc8c5

Observation 19946e4a-606a-4286-8bfa-a0bfb0dcc937 · outbound

This paper cites Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit,.

Deep Learning for Joint Narrowband Interference Cancellation and Soft Demodulation in OFDM Systems Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit,

Reference 22

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raw_fallback, observed 2026-07-10T02:46:43.267215Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-07-10T02:40:21.675520Z digest=sha256:66ebd82be7e970a611cd39d1f0b05587e0ed404c58776ea78473abcf17f45689

Observation 8cf7da71-7a9b-4840-b590-c3b19a75b2a3 · outbound

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

Deep Learning for Joint Narrowband Interference Cancellation and Soft Demodulation in OFDM Systems An Introduction to Deep Learning for the Physical Layer,

Reference 23

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raw_fallback, observed 2026-07-10T02:46:43.257445Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-07-10T02:40:21.675520Z digest=sha256:2fc4e548d85f73a12be1d184255ce1c839fc596360cff91da46cadc80baf3214

Observation bdd9226e-1d9e-46af-a6b1-32e2316a3811 · outbound

This paper cites Model-Driven Deep Learning for Physical Layer Communications,.

Deep Learning for Joint Narrowband Interference Cancellation and Soft Demodulation in OFDM Systems Model-Driven Deep Learning for Physical Layer Communications,

Reference 24

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raw_fallback, observed 2026-07-10T02:46:43.249922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-07-10T02:40:21.675520Z digest=sha256:3cd93f4aa48d2d70c6a11066f3285fbeba01e7f94448525cbfd4ca83d8bb7315

Observation 84dc8514-05da-4c57-a0bb-499663c7d91c · outbound

This paper cites Narrowband Interference Detection via Deep Learning,.

Deep Learning for Joint Narrowband Interference Cancellation and Soft Demodulation in OFDM Systems Narrowband Interference Detection via Deep Learning,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T02:46:43.248168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-07-10T02:40:21.675520Z digest=sha256:cfd11a8bae88a983f6d5201529abdc86aff9334e0c334acf904d935870684881

Observation cd12e7e2-a72f-45be-a906-6917a961d463 · outbound

This paper cites Deep Learning Noncoherent UWB Receiver Design,.

Deep Learning for Joint Narrowband Interference Cancellation and Soft Demodulation in OFDM Systems Deep Learning Noncoherent UWB Receiver Design,

Reference 26

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raw_fallback, observed 2026-07-10T02:46:43.292671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-07-10T02:40:21.675520Z digest=sha256:7d3eb22d5182ffee321ad36957e6f583498b766aa0a2615e84e502898d36c767

Observation 23c4883e-b9e0-41ef-9068-9778473587fd · outbound

This paper cites ”Machine LLRning.

Deep Learning for Joint Narrowband Interference Cancellation and Soft Demodulation in OFDM Systems ”Machine LLRning

Reference 27

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verified fuzzy
raw_fallback, observed 2026-07-10T02:46:43.263587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-07-10T02:40:21.675520Z digest=sha256:fbfc1a127879284790f7210ffb94ec523f608247a93ee2fe3ce45a6a0c3da02b

Observation 65298172-6b50-473a-8d98-b8bdf94cb1db · outbound

This paper cites Design and Implementation of a Low-Complexity Neural Detector for Correlated Noise,.

Deep Learning for Joint Narrowband Interference Cancellation and Soft Demodulation in OFDM Systems Design and Implementation of a Low-Complexity Neural Detector for Correlated Noise,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T02:46:43.260020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-07-10T02:40:21.675520Z digest=sha256:f78b3ec03bdae252f834c8638798539da3307ab97b08d6cf601e76a34750ddf8

Observation b7fbd4f0-97d2-46ca-a21a-aaaa05bae850 · outbound

This paper cites Interference Mitigation in Turbo-Coded OFDM Systems Using Robust LLRs,.

Deep Learning for Joint Narrowband Interference Cancellation and Soft Demodulation in OFDM Systems Interference Mitigation in Turbo-Coded OFDM Systems Using Robust LLRs,

Reference 29

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raw_fallback, observed 2026-07-10T02:46:43.265379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-07-10T02:40:21.675520Z digest=sha256:4965662a5310f5017daf25d13314ef09cf4cc0cb8645dd81d59b3a37078a8362

Observation 05fc360e-08a4-4250-970b-6b3fb910c582 · outbound

This paper cites Liu,Research on the Key Technologies in Narrowband Interference and Impulsive Noise Mitigation and Cancellation, ser.

Deep Learning for Joint Narrowband Interference Cancellation and Soft Demodulation in OFDM Systems Liu,Research on the Key Technologies in Narrowband Interference and Impulsive Noise Mitigation and Cancellation, ser

Reference 30

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raw_fallback, observed 2026-07-10T02:46:43.285381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-07-10T02:40:21.675520Z digest=sha256:2276e1ed00aa83158c11dfec2ceea71abb2b6f23c7f6ab5cf1221da91f7c6535

Observation d52d87c0-347c-4cb8-ac52-39ad44ffafde · outbound

This paper cites Complex Signal Denoising and Interference Mitigation for Automotive Radar Using Convolutional Neural Networks,.

Deep Learning for Joint Narrowband Interference Cancellation and Soft Demodulation in OFDM Systems Complex Signal Denoising and Interference Mitigation for Automotive Radar Using Convolutional Neural Networks,

Reference 31

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raw_fallback, observed 2026-07-10T02:46:43.264687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-07-10T02:40:21.675520Z digest=sha256:dac14caf19bc325fe3526e4351af0fa2a160ddbeb4cb58360d977e4d1118dabc

Observation d188d72f-0dc1-4cfe-b1eb-85701b99ebbb · outbound

This paper cites TensorFlow: A system for large-scale machine learning.

Deep Learning for Joint Narrowband Interference Cancellation and Soft Demodulation in OFDM Systems TensorFlow: A system for large-scale machine learning

Reference 32

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local_arxiv, observed 2026-07-10T02:46:42.946542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-07-10T02:40:21.675520Z digest=sha256:192aa5748ff9d056c48280cde847f3acdc312c14973845bb9713e387c317f294

Observation d5209514-3e92-4e14-8f36-68474c6ff1c2 · outbound

This paper cites Hoydis, S.

Deep Learning for Joint Narrowband Interference Cancellation and Soft Demodulation in OFDM Systems Hoydis, S

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T02:46:43.253823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-07-10T02:40:21.675520Z digest=sha256:3591a2bffbade9416b534200c9589132832d925c01beb1b4ef5911a77feaf6cf

Observation 607e84ec-5d16-4245-a772-353768357f2c · outbound

This paper cites 17.1 NVIDIA GB10: SoC Built for AI Acceleration,.

Deep Learning for Joint Narrowband Interference Cancellation and Soft Demodulation in OFDM Systems 17.1 NVIDIA GB10: SoC Built for AI Acceleration,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T02:46:43.256777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-07-10T02:40:21.675520Z digest=sha256:ac3564f32893cc1fec23fd94b8384a07700aa68d46fe4493d6d5c4c3e9c7dbe6

Observation 4b733764-15d1-45f5-8553-69d8062d0c2d · outbound

This paper cites TensorRT Implementations of Model Quantization on Edge SoC,.

Deep Learning for Joint Narrowband Interference Cancellation and Soft Demodulation in OFDM Systems TensorRT Implementations of Model Quantization on Edge SoC,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T02:46:43.255090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-07-10T02:40:21.675520Z digest=sha256:0aeffe35b22354cd02ffe554d9ba06632031ae26d7b6b7d699876fa4410b0ede

Pith citing papers

No inbound Pith citation observations are available.