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Paper Citation Record · LEDGER

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems

As of 13 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2412.01029.

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

pith.paper-citation-record.v1
2412.01029 v1

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T04:51:01.547796Z

measured 45 of 45 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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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 fuzzy37
  • unresolved5
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External citation measurements

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Outbound references

Observation c64c77b8-00d0-4e62-aa43-3e39e5a87555 · outbound

This paper cites Survey on 6G frontiers: Trends, appl ications, requirements, technologies and future research,.

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems Survey on 6G frontiers: Trends, appl ications, requirements, technologies and future research,

Reference 1

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 7c6a228f-894a-49dc-b210-0d29f681ff1d · outbound

This paper cites Terahertz Near-Field Communications and Sensing.

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems Terahertz Near-Field Communications and Sensing

Reference 2

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no resolver link, observed 2026-08-12T04:51:01.356171Z

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Observation a58c6273-5138-4030-8dc5-8d1d318474a6 · outbound

This paper cites Near-field int egrated sensing, positioning, and communication: A downli nk and uplink framework,.

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems Near-field int egrated sensing, positioning, and communication: A downli nk and uplink framework,

Reference 3

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Observation a8ab7ea2-a15d-490b-9c2b-7222d02e5755 · outbound

This paper cites Near-Field integrated sensing and communication: Opportunities and challenges,.

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems Near-Field integrated sensing and communication: Opportunities and challenges,

Reference 4

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 23f5094f-a070-4741-a3dd-2cd50123978b · outbound

This paper cites Near-Field User Localization and Channel Estimation for XL-MIMO Systems: Fundamentals, Recent Advances, and Outlooks.

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems Near-Field User Localization and Channel Estimation for XL-MIMO Systems: Fundamentals, Recent Advances, and Outlooks

Reference 5

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local_arxiv, observed 2026-08-12T04:51:01.694121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 7d5b7ef3-18f0-4875-9617-6129ab91c8b5 · outbound

This paper cites A tutorial on extremely large -scale MIMO for 6G: Fundamentals, signal processing, and applicat ions,.

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems A tutorial on extremely large -scale MIMO for 6G: Fundamentals, signal processing, and applicat ions,

Reference 6

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 4e5c2e23-abf7-489f-9f1e-f88e85623546 · outbound

This paper cites Near-field MIMO com munications for 6G: Fundamentals, challenges, potentials , and future directions,.

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems Near-field MIMO com munications for 6G: Fundamentals, challenges, potentials , and future directions,

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 9e24aa00-6fbc-4d49-8ea4-8d5c8f08c11b · outbound

This paper cites Ho lographic MIMO communications: Theoretical foundations, enabling t echnologies, and future directions,.

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems Ho lographic MIMO communications: Theoretical foundations, enabling t echnologies, and future directions,

Reference 8

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation dcda028a-c478-45ba-9761-78fd8b347481 · outbound

This paper cites Uplink Performance of Cell-Free Extremely Large-Scale MIMO Systems.

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems Uplink Performance of Cell-Free Extremely Large-Scale MIMO Systems

Reference 9

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local_arxiv, observed 2026-08-12T04:51:01.673768Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation fcaddff6-de27-449b-b51e-1412bf5530f4 · outbound

This paper cites Beam focusing for near-field multiuser MI MO communications,.

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems Beam focusing for near-field multiuser MI MO communications,

Reference 10

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raw_fallback, observed 2026-08-12T04:51:02.175040Z

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Observation 00f27c8b-b4b2-4cde-ac82-96cabc98cc88 · outbound

This paper cites Nyquist sampling and degrees of freedom of electromag netic fields,.

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems Nyquist sampling and degrees of freedom of electromag netic fields,

Reference 11

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Observation 0731036c-654d-4d72-95c1-c443eed874ea · outbound

This paper cites Towards 6G MIMO: Massive Spatial Multiplexing, Dense Arrays, and Interplay Between Electromagnetics and Processing.

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems Towards 6G MIMO: Massive Spatial Multiplexing, Dense Arrays, and Interplay Between Electromagnetics and Processing

Reference 12

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Source-reported events for the cited work

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Observation ccff913a-b5cc-4639-8b85-f4de3c76b86a · outbound

This paper cites Joint task offloading and resource allocatio n in aerial-terrestrial UA V networks with edge and fog computin g for post-disaster rescue,.

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems Joint task offloading and resource allocatio n in aerial-terrestrial UA V networks with edge and fog computin g for post-disaster rescue,

Reference 13

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Source-reported events for the cited work

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Observation ab956a1a-c765-4c46-86ad-500a42fed173 · outbound

This paper cites UA V-enabled covert federated learning,.

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems UA V-enabled covert federated learning,

Reference 14

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 4c13d4f1-b56c-4738-be80-7d326e23a889 · outbound

This paper cites Angular-distance based channel estimation for holographic MIMO,.

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems Angular-distance based channel estimation for holographic MIMO,

Reference 15

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 433b62d1-2df1-4412-b823-b5aa57f1243b · outbound

This paper cites Channel estimation for XL-MIMO systems with polar-domain m ulti-scale residual dense network,.

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems Channel estimation for XL-MIMO systems with polar-domain m ulti-scale residual dense network,

Reference 16

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raw_fallback, observed 2026-08-12T04:51:02.103336Z

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Observation 8e5a24f5-5de7-4f59-af53-8aebfabea699 · outbound

This paper cites Hybrid -Field channel estimation for XL-MIMO systems with stochas tic gradient pursuit algorithm,.

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems Hybrid -Field channel estimation for XL-MIMO systems with stochas tic gradient pursuit algorithm,

Reference 17

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation f2f5ef2c-24b3-443d-b49e-9080edb4519b · outbound

This paper cites Near-Field Communications: What Will Be Different?.

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems Near-Field Communications: What Will Be Different?

Reference 18

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Observation 31f2d5f9-81cc-4e38-9f81-f77a81479997 · outbound

This paper cites Near-Field Communications: A Comprehensive Survey.

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems Near-Field Communications: A Comprehensive Survey

Reference 19

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Observation edd7dce5-e170-464c-ace6-f21fb41241b3 · outbound

This paper cites Beam squint assist ed user localization in near-field integrated sensing and co mmunications systems,.

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems Beam squint assist ed user localization in near-field integrated sensing and co mmunications systems,

Reference 20

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Observation 552f37f1-234a-4a05-bcd0-cb79f9b37a3d · outbound

This paper cites Nea r-field channel reconstruction and user localization for EL AA systems,.

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems Nea r-field channel reconstruction and user localization for EL AA systems,

Reference 21

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 04684bea-053f-46ed-8438-8e3a879923ba · outbound

This paper cites Near-field rai nbow: Wideband beam training for XL-MIMO,.

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems Near-field rai nbow: Wideband beam training for XL-MIMO,

Reference 22

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Observation d7203655-b854-444c-8f76-d05e704e4af3 · outbound

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

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems Near-field wideband beamforming for e xtremely large antenna arrays,

Reference 23

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raw_fallback, observed 2026-08-12T04:51:02.028844Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation dd359b55-a408-481e-a3bb-b5cfbbb0214b · outbound

This paper cites Delay-phase prec oding for wideband THz massive MIMO,.

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems Delay-phase prec oding for wideband THz massive MIMO,

Reference 24

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raw_fallback, observed 2026-08-12T04:51:02.014416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T04:51:01.457042Z digest=sha256:2e943f6f949b07b009b9ab241a10e4f833341ff74955e4975edd193d876f60d4

Observation e01e86f8-4fd3-4f22-98a4-1a8166b489b0 · outbound

This paper cites Spat ial non-stationary near-field channel modeling and validat ion for massive MIMO systems,.

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems Spat ial non-stationary near-field channel modeling and validat ion for massive MIMO systems,

Reference 25

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raw_fallback, observed 2026-08-12T04:51:02.000294Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 804986e8-b689-4265-89ff-122eafb01150 · outbound

This paper cites Cram´ er-Rao bounds for ne ar-field sensing with extremely large-scale MIMO,.

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems Cram´ er-Rao bounds for ne ar-field sensing with extremely large-scale MIMO,

Reference 26

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raw_fallback, observed 2026-08-12T04:51:01.984714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T04:51:01.466031Z digest=sha256:1985bb95370edad43cd1a372e039c0ba2d83f825ce11e917fb427522aeaeb181

Observation 9f364262-e895-4f3b-8403-923486293326 · outbound

This paper cites Cra m´ er-Rao bounds of near-field positioning based on electrom agnetic propagation model,.

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems Cra m´ er-Rao bounds of near-field positioning based on electrom agnetic propagation model,

Reference 27

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raw_fallback, observed 2026-08-12T04:51:01.969048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T04:51:01.470470Z digest=sha256:cf38671bdc334cc28f61ff5c53705912b6de92f3f3b81e3ddfffb4ea22047f0e

Observation f56c909b-a348-4dc6-856b-fb72a5a1a500 · outbound

This paper cites Cram´ er-Rao bounds for near-field localization,.

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems Cram´ er-Rao bounds for near-field localization,

Reference 28

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raw_fallback, observed 2026-08-12T04:51:01.953506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T04:51:01.474916Z digest=sha256:5813d3970e982e639d7e314a4c950537d98c81c34739c4bea70fad283d5a7a13

Observation e6e94538-cc58-4665-a77b-a006e3f852e7 · outbound

This paper cites Pe rformance bounds for near-field localization with widely-s paced multi-subarray mmWave/THz MIMO,.

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems Pe rformance bounds for near-field localization with widely-s paced multi-subarray mmWave/THz MIMO,

Reference 29

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raw_fallback, observed 2026-08-12T04:51:01.937938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T04:51:01.479145Z digest=sha256:e199d8fb92b42740e979f540b1ead99e7bcacb6052ab13d37a553fadb4675f5f

Observation 0f68dc16-aebc-4f25-9146-086906626034 · outbound

This paper cites Near-field positioning and attitude sensing based on electromagnetic propagation modeling,.

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems Near-field positioning and attitude sensing based on electromagnetic propagation modeling,

Reference 30

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raw_fallback, observed 2026-08-12T04:51:01.922958Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T04:51:01.483421Z digest=sha256:cb3c0f5e45e33fa022b9d2010c2a94e275145c1a6287562be99153c3180bfd6c

Observation e65a62b3-9b13-455c-88be-88a36c9575ec · outbound

This paper cites Scalable near- field localization based on array partitioning and angle-of - arrival fusion,.

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems Scalable near- field localization based on array partitioning and angle-of - arrival fusion,

Reference 31

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raw_fallback, observed 2026-08-12T04:51:01.907821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T04:51:01.487845Z digest=sha256:d64105a36971ba5b0e7988add2dd24d708def634b5ce209555b2903a5f41f7e1

Observation c0b2ce7f-4da8-44c5-82b0-d250b8785dcb · outbound

This paper cites A low-complexity ne ar-field localization method based on electric field model,.

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems A low-complexity ne ar-field localization method based on electric field model,

Reference 32

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raw_fallback, observed 2026-08-12T04:51:01.893100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T04:51:01.492037Z digest=sha256:879ddbad3886160464bc123cf202804fd0485fa0207c8f3c9d2d2fb3ba3e2b0f

Observation 0eb73007-6b00-4e17-b967-68363bd6b8a5 · outbound

This paper cites Adaptive Downlink Localization and User Tracking in Near-Field and Far-Field: A Trade-Off Analysis.

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems Adaptive Downlink Localization and User Tracking in Near-Field and Far-Field: A Trade-Off Analysis

Reference 33

Resolution
verified exact
local_arxiv, observed 2026-08-12T04:51:01.606106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T04:51:01.496334Z digest=sha256:e08da711a089ed08f9fb4f859d87324af8533de86b493249b589f43449a175d5

Observation deb2dfb0-079d-4bbb-8f8b-324b57612556 · outbound

This paper cites Near- field localization with 1-bit quantized hybrid A/D reception,.

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems Near- field localization with 1-bit quantized hybrid A/D reception,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:51:01.878341Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T04:51:01.500785Z digest=sha256:1a0838765db34efafa91f88a53d1357a8465cb65ec0b7f5a1896731a9e326d8c

Observation 1f7a7eba-8115-4ca7-beaa-5b3da063fb89 · outbound

This paper cites Near-field in tegrated sensing, positioning, and communication: A downl ink and uplink framework,.

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems Near-field in tegrated sensing, positioning, and communication: A downl ink and uplink framework,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:51:01.863280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T04:51:01.504987Z digest=sha256:67e8ac000900697e73a0d6d75ab048af014bb053a1264a7781e32bf77692171a

Observation 00a2b5c7-ee95-4670-a4cb-cdaca011966d · outbound

This paper cites Joint Channel Estimation and Cooperative Localization for Near-Field Ultra-Massive MIMO.

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems Joint Channel Estimation and Cooperative Localization for Near-Field Ultra-Massive MIMO

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-12T04:51:01.509607Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:51:01.509607Z digest=sha256:6235104bc0974b5e370fdcfb306767b414c2c6c48692ee31f50eb87dd5017e6e

Observation 680599c7-0186-4d2b-86d8-199f8fa22693 · outbound

This paper cites Near-field local ization and channel reconstruction for ELAA systems,.

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems Near-field local ization and channel reconstruction for ELAA systems,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:51:01.847624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T04:51:01.514086Z digest=sha256:b0eef760a5c33aa83f3b38612a1a82ee449b6a8e6767a378c78970c21485da61

Observation 20abc020-bcce-4fb0-a6a3-f4a7b6339ed3 · outbound

This paper cites Sensing user’s activity, channel , and location with near-field extra-large-scale MIMO,.

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems Sensing user’s activity, channel , and location with near-field extra-large-scale MIMO,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:51:01.832609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T04:51:01.518408Z digest=sha256:1cc8bff2cfc3e60e938e640002c0acdc00cad94becab722f0fc53bbe6ef3602b

Observation 8e4515a2-ad74-4fdd-b695-80934303a4f4 · outbound

This paper cites A ConvNet for the 2020s,.

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems A ConvNet for the 2020s,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:51:01.817899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T04:51:01.522572Z digest=sha256:abf1c6f81c195c2ffd53e3f3b86879321e72b568fd0ba41fe790dfa7de7e7a4a

Observation 24c2a977-f993-40d6-a23c-a25cb6f4a859 · outbound

This paper cites A low-complexity frame sync hronization and frequency offset compensation scheme for O FDM systems over fading channels,.

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems A low-complexity frame sync hronization and frequency offset compensation scheme for O FDM systems over fading channels,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:51:01.803290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T04:51:01.526818Z digest=sha256:2d1fae0b0d4dc5009afcd3b2aab6c3a2c1f96ec0591bd97794f5f4f14a3cbeb3

Observation 245bf6ac-c49b-4490-9660-1bb805c5551f · outbound

This paper cites Performance analysis of 5G OFDM frame synchronizat ion with various channel conditions,.

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems Performance analysis of 5G OFDM frame synchronizat ion with various channel conditions,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:51:01.785989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T04:51:01.530952Z digest=sha256:a9400a0126f1d8bef293d2bf0187ab7ae5e192eee4a69ad9aaac9be4bec19eb7

Observation 2698e053-5fbc-441e-81b1-d679255f9081 · outbound

This paper cites Terahertz band: The last piece of RF spectrum puzzl e for communication systems,.

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems Terahertz band: The last piece of RF spectrum puzzl e for communication systems,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:51:01.770746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T04:51:01.535078Z digest=sha256:937f829ef888751bf09c4fd3c1d0b25fdb2f9cc3768190302444256cbebf6d04

Observation 191b954f-ac8f-45b0-a4f3-9ae7e2b0b620 · outbound

This paper cites Str uctured massive access for scalable cell-free massive MIMO systems,.

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems Str uctured massive access for scalable cell-free massive MIMO systems,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:51:01.755109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T04:51:01.539173Z digest=sha256:e72c67797b191c806f4beb761f58276ccc98403a6c6a134d44510b08247dc735

Observation ff2dedf4-f310-44bf-9299-f5207e6960db · outbound

This paper cites Conditi onal and unconditional Cram´ er-Rao bounds for near-field lo calization in bistatic MIMO radar systems,.

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems Conditi onal and unconditional Cram´ er-Rao bounds for near-field lo calization in bistatic MIMO radar systems,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:51:01.740070Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T04:51:01.543713Z digest=sha256:0839bc6abcceb6ac37fb15c3fe54666fe060b3c7a0514690d16356080e6baae8

Observation 1877d2fb-90f8-4bd9-ba67-146d27d22903 · outbound

This paper cites CHISEL: Compression -aware high-accuracy embedded indoor localization with de ep learning,.

Deep Learning Based Near-Field User Localization with Beam Squint in Wideband XL-MIMO Systems CHISEL: Compression -aware high-accuracy embedded indoor localization with de ep learning,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:51:01.724632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T04:51:01.547796Z digest=sha256:3cddef4b833d4a12754bd56a21aaefbaab84594a2eb5244c6b97b7e190e1bb5c

Pith citing papers

No inbound Pith citation observations are available.