Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T04:16:09.061450Z
Paper Citation Record · LEDGER
Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems
As of 8 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.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
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 2026-08-08T06:32:00.761636+00:00.
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 2026-08-08T06:32:00.761636+00:00.
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 2026-08-08T06:32:00.761636+00:00.
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 2026-08-08T06:32:00.761636+00:00.
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 2026-08-08T06:32:00.761636+00:00.
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 2026-08-08T06:32:00.761636+00:00.
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 2026-08-08T06:32:00.761636+00:00.
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 2026-08-08T06:32:00.761636+00:00.
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 2026-08-08T06:32:00.761636+00:00.
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 2026-08-08T06:32:00.761636+00:00.
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 2026-08-08T06:32:00.761636+00:00.
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 2026-08-08T06:32:00.761636+00:00.
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 2026-08-08T06:32:00.761636+00:00.
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 2026-08-08T06:32:00.761636+00:00.
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 2026-08-08T06:32:00.761636+00:00.
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 2026-08-08T06:32:00.761636+00:00.
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 2026-08-08T06:32:00.761636+00:00.
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 2026-08-08T06:32:00.761636+00:00.
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 2026-08-08T06:32:00.761636+00:00.
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 2026-08-08T06:32:00.761636+00:00.
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 2026-08-08T06:32:00.761636+00:00.
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 2026-08-08T06:32:00.761636+00:00.
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 2026-08-08T06:32:00.761636+00:00.
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 2026-08-08T06:32:00.761636+00:00.
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 2026-08-08T06:32:00.761636+00:00.
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 2026-08-08T06:32:00.761636+00:00.
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 2026-08-08T06:32:00.761636+00:00.
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 2026-08-08T06:32:00.761636+00:00.
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 2026-08-08T06:32:00.761636+00:00.
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 2026-08-08T06:32:00.761636+00:00.
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 2026-08-08T06:32:00.761636+00:00.
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 2026-08-08T06:32:00.761636+00:00.
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 2026-08-08T06:32:00.761636+00:00.
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 2026-08-08T06:32:00.761636+00:00.
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 2026-08-08T06:32:00.761636+00:00.
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 2026-08-08T06:32:00.761636+00:00.
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 2026-08-08T06:32:00.761636+00:00.
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 2026-08-08T06:32:00.761636+00:00.
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.
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 2026-08-08T06:32:00.761636+00:00.
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 2026-08-08T06:32:00.761636+00:00.
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 2026-08-08T06:32:00.761636+00:00.
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 2026-08-08T06:32:00.761636+00:00.
Pith citing papers
No inbound Pith citation observations are available.