Pith. sign in

Paper Citation Record · LEDGER

Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems

As of 22 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2506.22448.

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

pith.paper-citation-record.v1
2506.22448 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:16:09.061450Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+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

43 of 43 outbound references displayed

  • verified exact1
  • verified fuzzy41
  • unresolved1
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5f65b8b0-a382-4492-b202-b2ad5ed89999 · outbound

This paper cites 6G wireless networks: Vision, requirements, architec- ture, and key technologies,.

Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems 6G wireless networks: Vision, requirements, architec- ture, and key technologies,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:16:09.550149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:16:08.917700Z digest=sha256:158b2020d1eba3c6a48b24bef95d3839d215341458433bcb4987f00ae4424fbb

Observation 162f7dc6-4142-47f7-b7c4-e1e94dac2212 · outbound

This paper cites Terahertz-band joint ultra-massive MIMO radar-communications: Model-based and model- free hybrid beamforming,.

Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems Terahertz-band joint ultra-massive MIMO radar-communications: Model-based and model- free hybrid beamforming,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:16:09.539329Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:16:08.921661Z digest=sha256:fb710f06c9d44b7496eeb5c14419eb18ec402e8d755d83088d2d6dc841c518cb

Observation e82f0453-1c3c-44bf-9496-9c5d82f023e6 · outbound

This paper cites Terahertz band communication: An old problem revisited and research directions for the next decade,.

Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems Terahertz band communication: An old problem revisited and research directions for the next decade,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:16:09.528572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:16:08.925092Z digest=sha256:3d4e04e8d5e49465f4c147c43f96b72eb330015d80e893860d96ee4151beff4f

Observation 4bd23a4e-7782-4b17-a2d8-982fea52f004 · outbound

This paper cites Integrated sensing and communication for RIS-assisted backscatter systems,.

Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems Integrated sensing and communication for RIS-assisted backscatter systems,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:16:09.518054Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:16:08.928496Z digest=sha256:a4c02f6df70cdc67ff186f08e388565b44d15b5373ebb111b3a7a6cc1adcd677

Observation 23529400-e92d-488a-b64e-46dac9e50141 · outbound

This paper cites RIS- assisted integrated sensing and backscatter communications for future IoT networks,.

Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems RIS- assisted integrated sensing and backscatter communications for future IoT networks,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:16:09.507632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:16:08.932046Z digest=sha256:2c26b6806fd229a6be6f159002c92c3aaeb13fb24366429bb2f4b4be66c64acf

Observation f425b39e-e957-4d79-80e0-2cf6ecf0d5f5 · outbound

This paper cites Stacked Intelligent Metasurfaces for Wireless Communications: Applications and Challenges.

Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems Stacked Intelligent Metasurfaces for Wireless Communications: Applications and Challenges

Reference 6

Resolution
verified exact
local_arxiv, observed 2026-08-07T04:16:09.109852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:16:08.935422Z digest=sha256:e93a16490bb39e6fe815962effd222e88e16817a6e3e840acd297e44ba0c0820

Observation 3ec11dad-ff93-40cd-b650-d92a294e3231 · outbound

This paper cites Multi-user MISO with stacked intelligent metasurfaces: A DRL-based sum-rate optimization approach,.

Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems Multi-user MISO with stacked intelligent metasurfaces: A DRL-based sum-rate optimization approach,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:16:09.497183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:16:08.939722Z digest=sha256:394c7df6ee452addba13039330b537a3d68637465e4a3a0de494a0d4a00b1b61

Observation 4dddf204-0ed0-4915-83fc-066c9035738d · outbound

This paper cites Smart radio environments empowered by reconfig- urable intelligent surfaces: How it works, state of research, and the road ahead,.

Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems Smart radio environments empowered by reconfig- urable intelligent surfaces: How it works, state of research, and the road ahead,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:16:09.486645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:16:08.942889Z digest=sha256:d8f52ac22b89e0daccc852418167ff29e432e4b1a664d251d3133ff2bf7953bc

Observation fc1db7d6-2e55-47bf-86b6-1290990f167d · outbound

This paper cites Reconfigurable intelligent surfaces for 6G systems: Principles, applications, and research directions,.

Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems Reconfigurable intelligent surfaces for 6G systems: Principles, applications, and research directions,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:16:09.476154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:16:08.946160Z digest=sha256:295985b126f459b28dcc37a36f2d6af3b8add59c897e544c529d84abb88b81f2

Observation 1516119b-e4e5-48e7-81dd-f5ad9415296f · outbound

This paper cites Coverage enhancement by deploying ris in 5G commer- cial mobile networks: Field trials,.

Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems Coverage enhancement by deploying ris in 5G commer- cial mobile networks: Field trials,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:16:09.465219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:16:08.949274Z digest=sha256:1b4bbc3187ca9138141adefec3b5e5f9a4a41c819d827535f7f1b9399c9b75b9

Observation 7940fee5-2bf6-4734-84b8-51e7dad20b07 · outbound

This paper cites Reconfigurable intelligent surfaces: Principles and op- portunities,.

Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems Reconfigurable intelligent surfaces: Principles and op- portunities,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:16:09.454883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:16:08.952471Z digest=sha256:74895b1bfea45c6478ee21c457a90a67839dd15a1c568dbf8d808356987d1bb8

Observation f985bb3a-5107-43a8-b831-d6561f6f44f5 · outbound

This paper cites Intelligent reflecting surface enhanced wireless network via joint active and passive beamforming,.

Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems Intelligent reflecting surface enhanced wireless network via joint active and passive beamforming,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:16:09.433627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:16:08.959064Z digest=sha256:4c757108a63447662b77a219a0fb875c2d91142a9697d5701740c29092dbbe2e

Observation 52852b25-4422-4813-a99f-3eb9c1cb8e2a · outbound

This paper cites Weighted sum- rate maximization for intelligent reflecting surface enhanced wireless networks,.

Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems Weighted sum- rate maximization for intelligent reflecting surface enhanced wireless networks,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:16:09.423081Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:16:08.962624Z digest=sha256:ce30f1bbee91d1a79891dff37db934f1da0af73be5319de785f11c9f47c3f594

Observation bbbf67d7-0a46-4055-83c3-c518cf3ad08b · outbound

This paper cites Intelligent reflecting surface enhanced wireless network: Joint active and passive beamforming design,.

Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems Intelligent reflecting surface enhanced wireless network: Joint active and passive beamforming design,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:16:09.444454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:16:08.965733Z digest=sha256:fea708b2543a03fda692ee406bf7c37ff2d87b8a8b1a39e7c26dbeb1d26a448c

Observation e8554eb9-d2a0-4409-8288-800333fc753f · outbound

This paper cites Robust beamforming for RIS-assisted wireless communications with discrete phase shifts,.

Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems Robust beamforming for RIS-assisted wireless communications with discrete phase shifts,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:16:09.401418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:16:08.972241Z digest=sha256:ad99155a8bc33cd1f11796b6902ef3ecb48d6796624be4780781c7c24ee50475

Observation ccdc37a1-2176-415d-9122-a33dbc0b97d1 · outbound

This paper cites Quantized phase alignment by discrete phase shifts for reconfigurable intelligent surface-assisted communication systems,.

Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems Quantized phase alignment by discrete phase shifts for reconfigurable intelligent surface-assisted communication systems,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:16:09.391012Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:16:08.975375Z digest=sha256:f6406dc0f9996becca9b00fde5afbe0b71068deccf64d72c9fa55d7028e8384e

Observation a53bd792-9465-4080-a03c-916e614eb4e9 · outbound

This paper cites Rate optimization and power allocation in RIS- assisted multi-user OFDM communication,.

Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems Rate optimization and power allocation in RIS- assisted multi-user OFDM communication,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:16:09.380366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:16:08.978493Z digest=sha256:acee76195ea6c4daed016923a7ef045145e8bff18c30dc581682e26e3951d395

Observation 01f0798e-90f3-42a5-b6bf-35086b3685d2 · outbound

This paper cites Joint beamforming optimization for reconfigurable intelligent surface-enabled MISO-OFDM systems,.

Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems Joint beamforming optimization for reconfigurable intelligent surface-enabled MISO-OFDM systems,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:16:09.369752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:16:08.981443Z digest=sha256:215cc943f4729d42c48f1fca1c67a5896f41d923374e8ef6aa3b7b09d3c2cbbb

Observation 43664943-c5cd-494b-b7e2-76241f70ba4e · outbound

This paper cites Harmony search-based optimization for multi-RISs MU-MISO OFDMA systems,.

Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems Harmony search-based optimization for multi-RISs MU-MISO OFDMA systems,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:16:09.359414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:16:08.984768Z digest=sha256:8c6125c06d8ad5458b2d0caa12750320f6a0b49d241ce2a5b6049bdac9e6444e

Observation d1fb8903-83ff-4b25-b773-f888285f323d · outbound

This paper cites Sum-rate maximization for IRS-assisted UA V OFDMA communication systems,.

Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems Sum-rate maximization for IRS-assisted UA V OFDMA communication systems,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:16:09.349007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:16:08.987980Z digest=sha256:295acd4533941e5da032637f461424a4f8c0ecf9842fe8e5c6380cea9ccbf504

Observation fc75d55d-744c-4328-8ce8-18006d1edc6e · outbound

This paper cites AI empowered wireless communications: From bits to semantics,.

Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems AI empowered wireless communications: From bits to semantics,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:16:09.338451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:16:08.991077Z digest=sha256:73c1034cb654b7b7d89ec5b44b169b8555f0f343d4e7ef9006b2515b652f846d

Observation e2eec440-7134-4772-9d4b-70c8702fca81 · outbound

This paper cites RIS-assisted mmwave channel estimation using convolutional neural networks,.

Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems RIS-assisted mmwave channel estimation using convolutional neural networks,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:16:09.328012Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:16:08.994112Z digest=sha256:6cec74eaf0f60ca3d366332e9ed783709d8b401128457876befd083a9f5cdbbd

Observation 7bebda7d-c49c-475c-bda7-eda57aed14e5 · outbound

This paper cites Deep learning based multi-user power allocation and hybrid precoding in massive MIMO systems,.

Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems Deep learning based multi-user power allocation and hybrid precoding in massive MIMO systems,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:16:09.317317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:16:08.997156Z digest=sha256:0b6f97ea5f6839c77681a800637ce695d9f9fa9e96d318538eaf5cdf6fb75007

Observation 601d7c52-85f4-490c-834b-bdce54e8f0a8 · outbound

This paper cites Deep channel learning for large intelligent surfaces aided mm-Wave massive MIMO systems,.

Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems Deep channel learning for large intelligent surfaces aided mm-Wave massive MIMO systems,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:16:09.306797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:16:09.000352Z digest=sha256:90ad908d0bd37e6df4e88a5943027100282c09dcd44c66dd3d3f686cfe419fc1

Observation 5a8332c3-058d-4307-9ece-ecd58c17dda2 · outbound

This paper cites Enabling large intelligent surfaces with compressive sensing and deep learning,.

Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems Enabling large intelligent surfaces with compressive sensing and deep learning,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:16:09.296341Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:16:09.003526Z digest=sha256:022330154a191aeff5e827fb12f5cbbd3cbcedc0b286c3a02661f7fca914b5a1

Observation 99c7d821-1ec1-44c7-83e2-92e7e2aaa38f · outbound

This paper cites Deep learning for physical-layer 5G wireless tech- niques: Opportunities, challenges and solutions,.

Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems Deep learning for physical-layer 5G wireless tech- niques: Opportunities, challenges and solutions,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:16:09.285897Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:16:09.006946Z digest=sha256:47f692135b5c522dd27065e86571dd0d51d784126493f025a008006c09547bb4

Observation c1ec36d7-1aaa-4edd-bc17-de4acec0519b · outbound

This paper cites Deep unsupervised learning for joint antenna selection and hybrid beamforming,.

Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems Deep unsupervised learning for joint antenna selection and hybrid beamforming,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:16:09.275476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:16:09.010251Z digest=sha256:576f81b27134817bf91a6ba43d5e63ddd95f3b0f635f0ea07c381410817036cd

Observation 2dec1198-18ca-4b9b-8e20-9511e2187b9d · outbound

This paper cites Semi-supervised learning via cross- prediction-powered inference for wireless systems,.

Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems Semi-supervised learning via cross- prediction-powered inference for wireless systems,

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:16:09.264839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:16:09.013330Z digest=sha256:ccb1053e05d65ee899f35cd442c0cc71d104108dc437729930a6fed0e359ca7b

Observation 3a494724-098b-4bbe-a45f-aa3526f5279e · outbound

This paper cites Channel quality prediction for TSCH blacklisting in highly dynamic networks: A self-supervised deep learning approach,.

Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems Channel quality prediction for TSCH blacklisting in highly dynamic networks: A self-supervised deep learning approach,

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:16:09.253612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:16:09.016442Z digest=sha256:cbb95b0cf3e486dd1f5e1aef80153ec5f9aa979ad37dc7ba5721ab4c17fe0eea

Observation 220de73f-1329-42e1-95a0-5a9f6d828fff · outbound

This paper cites Unsupervised learning for passive beamforming,.

Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems Unsupervised learning for passive beamforming,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:16:09.243131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:16:09.019938Z digest=sha256:a251483ca4251f2454fc9ff2e3103392a768b6d52ec7c2d0bba5f708304a9219

Observation c5f549af-9caf-4b2c-a181-078d84013daf · outbound

This paper cites Unsupervised learning- based joint active and passive beamforming design for reconfigurable intelligent surfaces aided wireless networks,.

Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems Unsupervised learning- based joint active and passive beamforming design for reconfigurable intelligent surfaces aided wireless networks,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:16:09.232684Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:16:09.023064Z digest=sha256:2036da0afc3dd440d9e9a67556bcc6e014c1c3b547b7dc728bb29d03a3a95664

Observation 6aad197d-5de9-4b5c-a742-c17608906118 · outbound

This paper cites Unsupervised learning for joint beamforming design in RIS-aided ISAC systems,.

Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems Unsupervised learning for joint beamforming design in RIS-aided ISAC systems,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:16:09.222266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:16:09.026220Z digest=sha256:f903aa7b919d5f3ba189f6a7ddc72e7ccb171dde66b0d11e703583f066400031

Observation 6f132204-33e3-42a5-ab88-4239d2d14f3d · outbound

This paper cites IRS-enhanced OFDMA: Joint re- source allocation and passive beamforming optimization,.

Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems IRS-enhanced OFDMA: Joint re- source allocation and passive beamforming optimization,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:16:09.211642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:16:09.029359Z digest=sha256:e5fbe8069d8d10454d0d387544361157b40dd89a97d56960d7c1da0bf238e7fb

Observation 1be4aa11-0612-4aa0-bf29-48bc67284408 · outbound

This paper cites Deep reinforcement learning based power minimization for RIS-assisted MISO-OFDM systems,.

Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems Deep reinforcement learning based power minimization for RIS-assisted MISO-OFDM systems,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:16:09.200980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:16:09.032562Z digest=sha256:ed341c044ed1733be1b1d0276e3702691eedbfbfb8f72f5f4cf1e225ab0fae36

Observation 37eeb00e-4ff0-4edd-9c0c-76fcd99ae0f2 · outbound

This paper cites IRS-enhanced OFDM: Power allocation and passive array optimization,.

Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems IRS-enhanced OFDM: Power allocation and passive array optimization,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:16:09.190229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:16:09.035866Z digest=sha256:9e566b6e62686280adde610881fb4fbcc11ecc4551cee7c0914eaf5477c0e34a

Observation 7cd878de-9d74-471c-bde2-a43e7c37ec72 · outbound

This paper cites Intelligent reflecting surface meets OFDM: Protocol design and rate maximization,.

Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems Intelligent reflecting surface meets OFDM: Protocol design and rate maximization,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:16:09.179193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:16:09.038866Z digest=sha256:9ad6e582e009798b89b7c7ea2080fac1318b3abbbc082c27d812792fd2e0e47c

Observation f52efdb3-3329-4096-8247-b980f4e840dd · outbound

This paper cites SOQ: Structural reinforcement learning for constrained delay minimization with channel state information,.

Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems SOQ: Structural reinforcement learning for constrained delay minimization with channel state information,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:16:09.167072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:16:09.041941Z digest=sha256:e9fa73f1a879d339370e18db8b16148dd1e5709a3ace4ac268be0d15e4fa4cad

Observation 36f13531-ef16-4513-aff9-7a9613148bf6 · outbound

This paper cites Spectrum sharing in vehicular networks based on multi-agent reinforcement learning,.

Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems Spectrum sharing in vehicular networks based on multi-agent reinforcement learning,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:16:09.155867Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:16:09.045313Z digest=sha256:e5f9af0806edcf75cba6b1624f14056a6e97dc8c2be48e62f07eb61a5ccde155

Observation 3c62ed9f-5b5e-453f-b3dc-e6dcd755982b · outbound

This paper cites Categorical Reparameterization with Gumbel-Softmax.

Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems Categorical Reparameterization with Gumbel-Softmax

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-07T04:16:09.048532Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:16:09.048532Z digest=sha256:c0b3cfed72f5e8e15ba92c8df925118fb1ae3398bcf2b39dd0c16ca534016779

Observation 5c85294f-ebe3-47e3-b29e-9f2e0f714efe · outbound

This paper cites Towards optimal power control via ensembling deep neural networks,.

Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems Towards optimal power control via ensembling deep neural networks,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:16:09.144746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:16:09.051982Z digest=sha256:d712cdf2afe6f15a4b8b6bd6aede1137240e97438b04cd444423d884077bada1

Observation 7332b4f7-cde6-415e-88a7-091b7a03a0ac · outbound

This paper cites Wireless communications through reconfigurable intelligent surfaces,.

Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems Wireless communications through reconfigurable intelligent surfaces,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:16:09.133376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:16:09.055080Z digest=sha256:d7b2c084f0e0b2b47d9d611b42da1e207759fd90fcda3e1540a026ccfe351b48

Observation c394f406-dfd2-4fa5-8462-5b7ff8511ae4 · outbound

This paper cites Hybrid beamforming for reconfigurable intelligent surface based multi-user communications: Achievable rates with limited discrete phase shifts,.

Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems Hybrid beamforming for reconfigurable intelligent surface based multi-user communications: Achievable rates with limited discrete phase shifts,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:16:09.412206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:16:09.058265Z digest=sha256:672c27ce4f9beae4a20d07f9a644a822995e167c9e28ce2bbcfd4c5255360cc1

Observation 407c4551-8524-4723-be95-215c68c68aa5 · outbound

This paper cites Learning resilient radio resource management policies with graph neural networks,.

Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems Learning resilient radio resource management policies with graph neural networks,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:16:09.121874Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:16:09.061450Z digest=sha256:486acd118bd996fb388a146d179cd188ae73085c7075f139f3e9826bee5985af

Pith citing papers

No inbound Pith citation observations are available.