Paper Citation Record · LEDGER

Bilinear Subspace Variational Bayesian Inference for Joint Scattering Environment Sensing and Data Recovery in ISAC Systems

As of 17 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 0 inbound Pith citation observations for arXiv:2502.00811.

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

pith.paper-citation-record.v1
2502.00811 v2

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T17:46:07.913159Z

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One-hop event checks from named stored sources.

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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

27 of 27 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6749a0c4-9869-4996-974e-9930a58f238e · outbound

This paper cites An overview of signal processing techniques for joint communication and radar sensing,.

Bilinear Subspace Variational Bayesian Inference for Joint Scattering Environment Sensing and Data Recovery in ISAC Systems An overview of signal processing techniques for joint communication and radar sensing,

Reference 1

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Observation dda43e9d-6a53-4743-be3e-9b55f6417b58 · outbound

This paper cites Integrated sensing and communications: Toward dual-functional wire- less networks for 6G and beyond,.

Bilinear Subspace Variational Bayesian Inference for Joint Scattering Environment Sensing and Data Recovery in ISAC Systems Integrated sensing and communications: Toward dual-functional wire- less networks for 6G and beyond,

Reference 2

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Observation 75ea3d47-2b5f-4a4e-a785-abb202664913 · outbound

This paper cites Joint radar and communication design: Applications, state-of-the-art, and the road ahead,.

Bilinear Subspace Variational Bayesian Inference for Joint Scattering Environment Sensing and Data Recovery in ISAC Systems Joint radar and communication design: Applications, state-of-the-art, and the road ahead,

Reference 3

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Observation e33bbc42-7c43-4bcb-9f66-26fea7ff3fdf · outbound

This paper cites A survey on fundamental limits of integrated sensing and communication,.

Bilinear Subspace Variational Bayesian Inference for Joint Scattering Environment Sensing and Data Recovery in ISAC Systems A survey on fundamental limits of integrated sensing and communication,

Reference 4

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Observation 4b47f8b6-0450-4658-872c-4242f80699a2 · outbound

This paper cites Distributed compressive CSIT estimation and feedback for FDD multi-user massive MIMO systems,.

Bilinear Subspace Variational Bayesian Inference for Joint Scattering Environment Sensing and Data Recovery in ISAC Systems Distributed compressive CSIT estimation and feedback for FDD multi-user massive MIMO systems,

Reference 5

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Observation 16a34363-71b0-47c7-87aa-0c619165917b · outbound

This paper cites Closed-loop autonomous pilot and compressive CSIT feedback resource adaptation in multi-user FDD massive MIMO systems,.

Bilinear Subspace Variational Bayesian Inference for Joint Scattering Environment Sensing and Data Recovery in ISAC Systems Closed-loop autonomous pilot and compressive CSIT feedback resource adaptation in multi-user FDD massive MIMO systems,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:46:08.289545Z

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Observation 4ffb9bd2-838a-4f9e-b942-6bd1d3511eed · outbound

This paper cites Joint pilot optimization, target detection and channel estimation for integrated sensing and communication systems,.

Bilinear Subspace Variational Bayesian Inference for Joint Scattering Environment Sensing and Data Recovery in ISAC Systems Joint pilot optimization, target detection and channel estimation for integrated sensing and communication systems,

Reference 7

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Observation 17ed4414-5592-498e-acbd-f959e3a15410 · outbound

This paper cites Joint scattering environment sensing and channel estimation based on non-stationary Markov random field,.

Bilinear Subspace Variational Bayesian Inference for Joint Scattering Environment Sensing and Data Recovery in ISAC Systems Joint scattering environment sensing and channel estimation based on non-stationary Markov random field,

Reference 8

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This paper cites Semiblind channel estimation and data detection for OFDM systems with optimal pilot design,.

Bilinear Subspace Variational Bayesian Inference for Joint Scattering Environment Sensing and Data Recovery in ISAC Systems Semiblind channel estimation and data detection for OFDM systems with optimal pilot design,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:46:08.265323Z

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Observation eee2b45c-6d30-4283-a4f2-02e8af5286c8 · outbound

This paper cites Bilinear generalized approxi- mate message passing-part I: Derivation,.

Bilinear Subspace Variational Bayesian Inference for Joint Scattering Environment Sensing and Data Recovery in ISAC Systems Bilinear generalized approxi- mate message passing-part I: Derivation,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:46:08.253963Z

Source-reported events for the cited work

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Observation 25668143-38e0-4882-a655-620ad4aca89d · outbound

This paper cites Bilinear gaussian belief propagation for large MIMO channel and data estimation,.

Bilinear Subspace Variational Bayesian Inference for Joint Scattering Environment Sensing and Data Recovery in ISAC Systems Bilinear gaussian belief propagation for large MIMO channel and data estimation,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:46:08.241618Z

Source-reported events for the cited work

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Observation 1caa4fa5-29ef-48a1-b629-3569233fc2f9 · outbound

This paper cites Turbo-like joint data-and-channel estimation in quantized massive mimo systems,.

Bilinear Subspace Variational Bayesian Inference for Joint Scattering Environment Sensing and Data Recovery in ISAC Systems Turbo-like joint data-and-channel estimation in quantized massive mimo systems,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:46:08.229561Z

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Observation d835d4a2-6b07-40e0-8aaf-1c4987721351 · outbound

This paper cites Variational Bayes’ joint channel estimation and soft symbol decoding for uplink massive MIMO systems with low resolution ADCs,.

Bilinear Subspace Variational Bayesian Inference for Joint Scattering Environment Sensing and Data Recovery in ISAC Systems Variational Bayes’ joint channel estimation and soft symbol decoding for uplink massive MIMO systems with low resolution ADCs,

Reference 13

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Source-reported events for the cited work

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Observation 853c6c3a-527f-4cce-8a48-718e5ea14bc0 · outbound

This paper cites Massive MIMO-OFDM systems with low resolution ADCs: Cramér-rao bound, sparse channel estimation, and soft symbol decod- ing,.

Bilinear Subspace Variational Bayesian Inference for Joint Scattering Environment Sensing and Data Recovery in ISAC Systems Massive MIMO-OFDM systems with low resolution ADCs: Cramér-rao bound, sparse channel estimation, and soft symbol decod- ing,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:46:08.210639Z

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Observation c4a9f708-da52-47da-9d82-f4bc2a69c6ad · outbound

This paper cites TST-MUSIC for joint DOA- delay estimation,.

Bilinear Subspace Variational Bayesian Inference for Joint Scattering Environment Sensing and Data Recovery in ISAC Systems TST-MUSIC for joint DOA- delay estimation,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:46:08.198769Z

Source-reported events for the cited work

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Observation 3475501e-3756-49f5-8308-72151290ac13 · outbound

This paper cites Subspace constrained variational Bayesian inference for structured compressive sensing with a dynamic grid,.

Bilinear Subspace Variational Bayesian Inference for Joint Scattering Environment Sensing and Data Recovery in ISAC Systems Subspace constrained variational Bayesian inference for structured compressive sensing with a dynamic grid,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:46:08.185205Z

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Observation 79897e70-6d1e-4fac-a1f4-0f3836a1cca1 · outbound

This paper cites Cloud-assisted cooperative localization for vehicle platoons: A turbo approach,.

Bilinear Subspace Variational Bayesian Inference for Joint Scattering Environment Sensing and Data Recovery in ISAC Systems Cloud-assisted cooperative localization for vehicle platoons: A turbo approach,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:46:08.173221Z

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Observation 6ad7daa1-0e33-4373-ba07-1786b1553196 · outbound

This paper cites Joint channel parameter estimation and scatterers localization,.

Bilinear Subspace Variational Bayesian Inference for Joint Scattering Environment Sensing and Data Recovery in ISAC Systems Joint channel parameter estimation and scatterers localization,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:46:08.161009Z

Source-reported events for the cited work

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Observation 61b2e721-c2db-4524-9139-e29b6ba10691 · outbound

This paper cites Robust recovery of structured sparse signals with uncertain sensing matrix: A Turbo-VBI approach,.

Bilinear Subspace Variational Bayesian Inference for Joint Scattering Environment Sensing and Data Recovery in ISAC Systems Robust recovery of structured sparse signals with uncertain sensing matrix: A Turbo-VBI approach,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:46:08.146355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e808fd94-e4db-4918-962e-edca3da5d249 · outbound

This paper cites Factor graphs and the sum-product algorithm,.

Bilinear Subspace Variational Bayesian Inference for Joint Scattering Environment Sensing and Data Recovery in ISAC Systems Factor graphs and the sum-product algorithm,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:46:08.133604Z

Source-reported events for the cited work

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Observation 8e1a770b-4776-49f6-870b-9e0c5ae4d043 · outbound

This paper cites The variational approximation for Bayesian inference,.

Bilinear Subspace Variational Bayesian Inference for Joint Scattering Environment Sensing and Data Recovery in ISAC Systems The variational approximation for Bayesian inference,

Reference 21

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Observation f2438b05-bcc1-4a84-881e-18cac7fa02ed · outbound

This paper cites Fast inverse-free sparse Bayesian learning via relaxed evidence lower bound maximization,.

Bilinear Subspace Variational Bayesian Inference for Joint Scattering Environment Sensing and Data Recovery in ISAC Systems Fast inverse-free sparse Bayesian learning via relaxed evidence lower bound maximization,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:46:08.106066Z

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Observation 5c8b6ec8-e0d6-4192-8d26-8264f27d7c61 · outbound

This paper cites Successive Linear Approximation VBI for Joint Sparse Signal Recovery and Dynamic Grid Parameters Estimation.

Bilinear Subspace Variational Bayesian Inference for Joint Scattering Environment Sensing and Data Recovery in ISAC Systems Successive Linear Approximation VBI for Joint Sparse Signal Recovery and Dynamic Grid Parameters Estimation

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-08-09T17:46:07.952072Z

Source-reported events for the cited work

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Observation 3a6178f5-9004-4e81-9baa-dbb6b6747d78 · outbound

This paper cites Signal recovery from random mea- surements via orthogonal matching pursuit,.

Bilinear Subspace Variational Bayesian Inference for Joint Scattering Environment Sensing and Data Recovery in ISAC Systems Signal recovery from random mea- surements via orthogonal matching pursuit,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:46:08.094297Z

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Observation 5d8a3aee-ccf9-433d-aba9-2ed460e8379d · outbound

This paper cites Detection of the number of coherent signals by the MDL principle,.

Bilinear Subspace Variational Bayesian Inference for Joint Scattering Environment Sensing and Data Recovery in ISAC Systems Detection of the number of coherent signals by the MDL principle,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:46:08.081564Z

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Observation 60fccbc4-2956-47c3-9097-65ffb5277f21 · outbound

This paper cites Super-resolution toa estimation with diversity for indoor geolocation,.

Bilinear Subspace Variational Bayesian Inference for Joint Scattering Environment Sensing and Data Recovery in ISAC Systems Super-resolution toa estimation with diversity for indoor geolocation,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:46:08.069422Z

Source-reported events for the cited work

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Observation 1ccb4e43-3a29-4d01-98d3-dc62e1715289 · outbound

This paper cites Wiley 5G Ref, 2021.

Bilinear Subspace Variational Bayesian Inference for Joint Scattering Environment Sensing and Data Recovery in ISAC Systems Wiley 5G Ref, 2021

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:46:08.057594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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