Paper Citation Record · LEDGER

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning

As of 17 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 3 inbound Pith citation observations for arXiv:2411.11070.

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

pith.paper-citation-record.v1
2411.11070 v1

Coverage vector

measured 46 of 46 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T19:04:08.585731Z

measured 49 of 49 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:26:19.816502Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-11T06:26:01.199724Z

Reference resolution

46 of 46 outbound references displayed

verified exact1
verified fuzzy40
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ccb62485-7443-4300-a710-730fece06b44 · outbound

This paper cites On the road to 6G: Visions, requirements, key technologies and testbeds,.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning On the road to 6G: Visions, requirements, key technologies and testbeds,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-12T19:04:08.389561Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 70e44e47-3b4f-4d21-a431-1cd6a6e8c44a · outbound

This paper cites Next Generation Advanced Transceiver Technologies for 6G and Beyond.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning Next Generation Advanced Transceiver Technologies for 6G and Beyond

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-12T19:04:08.394838Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9ff8ea1f-a46d-4ddc-bfce-6a9558ebc7fd · outbound

This paper cites Massive MIMO for next generation wireless systems,.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning Massive MIMO for next generation wireless systems,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-12T19:04:08.399666Z

Source-reported events for the cited work

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Observation 976d32c2-f090-4897-a875-97c26baad917 · outbound

This paper cites A comprehensive overview on 5G-and - beyond networks with UA Vs: From communications to sensing a nd intelligence,.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning A comprehensive overview on 5G-and - beyond networks with UA Vs: From communications to sensing a nd intelligence,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:04:09.286592Z

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 84cbfdc0-0623-4fcf-9e6a-a952512547b7 · outbound

This paper cites Deplo ying dense networks for maximal energy efﬁciency: Small cells meet mas sive MIMO,.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning Deplo ying dense networks for maximal energy efﬁciency: Small cells meet mas sive MIMO,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:04:09.271105Z

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 cc2ee462-12af-4d4c-a217-9d707fc22a58 · outbound

This paper cites User-centric 5G cellular networks: Resource allocation and comparison w ith the cell-free massive MIMO approach,.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning User-centric 5G cellular networks: Resource allocation and comparison w ith the cell-free massive MIMO approach,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:04:09.255005Z

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 e58349c1-d816-448e-83bd-e3d351f9bfaa · outbound

This paper cites Prospective multiple antenna technologies for beyo nd 5G,.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning Prospective multiple antenna technologies for beyo nd 5G,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-12T19:04:08.418078Z

Source-reported events for the cited work

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Observation b1944103-8d81-47e2-98ae-6fbe2efa19cc · outbound

This paper cites Cell-free massive MIMO versus small cells,.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning Cell-free massive MIMO versus small cells,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-12T19:04:08.422039Z

Source-reported events for the cited work

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Observation 48003128-5b71-486e-8fa3-658d06e63d00 · outbound

This paper cites Precoding and power optimization in cell-free massive MIM O sys- tems,.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning Precoding and power optimization in cell-free massive MIM O sys- tems,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:04:09.217843Z

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 4544066d-8b87-45a5-920a-f4642d8bb09f · outbound

This paper cites Energy efﬁciency of the cell-free massive MIMO upl ink with optimal uniform quantization,.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning Energy efﬁciency of the cell-free massive MIMO upl ink with optimal uniform quantization,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:04:09.203937Z

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 866f08b5-783d-48bb-b2a0-6382e8799206 · outbound

This paper cites Reconﬁgurable intelligent surface-assisted ce ll-free massive MIMO systems over spatially-correlated channels,.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning Reconﬁgurable intelligent surface-assisted ce ll-free massive MIMO systems over spatially-correlated channels,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:04:09.187444Z

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 4fa0cf79-558d-4551-8df6-8b32cd890673 · outbound

This paper cites Toward gr een communication in 6G-enabled massive internet of things,.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning Toward gr een communication in 6G-enabled massive internet of things,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:04:09.172952Z

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 d4764e20-288a-4951-97f5-a5f553662fd7 · outbound

This paper cites Smart radio environments emp owered by reconﬁgurable intelligent surfaces: How it works, state of research, and the road ahead,.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning Smart radio environments emp owered by reconﬁgurable intelligent surfaces: How it works, state of research, and the road ahead,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:04:09.157992Z

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 cd426267-f62a-448a-9a43-876c1cd0aa14 · outbound

This paper cites Intelligent surfaces empowered wireless network: Recent advances and the road to 6G,.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning Intelligent surfaces empowered wireless network: Recent advances and the road to 6G,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:04:09.143339Z

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 ab746297-a46e-4a98-96c8-83bd246541fb · outbound

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

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning Recon- ﬁgurable intelligent surfaces for 6G systems: Principles, applications, and research directions,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:04:09.129785Z

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 a658ceb0-9296-4834-b3a3-700a3d507386 · outbound

This paper cites Multi-agent r einforcement learning-based joint precoding and phase shift optimizati on for RIS- aided cell-free massive MIMO systems,.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning Multi-agent r einforcement learning-based joint precoding and phase shift optimizati on for RIS- aided cell-free massive MIMO systems,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:04:09.116352Z

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 875437bd-dfc8-43c5-aec7-4b2985ae5ae8 · outbound

This paper cites Intelligent reﬂ ecting surface aided full-duplex communication: Passive beamfor ming and deployment design,.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning Intelligent reﬂ ecting surface aided full-duplex communication: Passive beamfor ming and deployment design,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:04:09.101945Z

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 91a2c98b-4c3d-472c-8b9b-6b23d646251e · outbound

This paper cites Resource alloc ation in intelligent reﬂecting surface assisted NOMA systems,.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning Resource alloc ation in intelligent reﬂecting surface assisted NOMA systems,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:04:09.086464Z

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 0d0e5d03-c709-4912-94a5-eec80c29b3ec · outbound

This paper cites Robust sec ure UA V communications with the aid of reconﬁgurable intelligent s urfaces,.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning Robust sec ure UA V communications with the aid of reconﬁgurable intelligent s urfaces,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:04:09.068963Z

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 4461428d-7c5e-4985-9ccc-87e8f154317b · outbound

This paper cites RIS-aided cell-free massive MIMO systems for 6 G: Fundamentals, system design, and applications,.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning RIS-aided cell-free massive MIMO systems for 6 G: Fundamentals, system design, and applications,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:04:09.052416Z

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 e60a21c2-f0a3-4660-95d7-a802d32fdf7b · outbound

This paper cites A joint precoding framework for wid eband reconﬁgurable intelligent surface-aided cell-free netwo rk,.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning A joint precoding framework for wid eband reconﬁgurable intelligent surface-aided cell-free netwo rk,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:04:09.035659Z

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 d5261745-9232-48c6-a9d1-39967495b657 · outbound

This paper cites Cooperat ive beamforming for RIS-aided cell-free massive MIMO networks ,.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning Cooperat ive beamforming for RIS-aided cell-free massive MIMO networks ,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:04:09.014889Z

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 fb4d212d-ffbb-4424-b8e3-7883268bc9e2 · outbound

This paper cites Linear precoder design for si - multaneous information and energy transfer over two-user M IMO interference channels,.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning Linear precoder design for si - multaneous information and energy transfer over two-user M IMO interference channels,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:04:08.998558Z

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 2da923cd-cf3c-4c8c-bade-0e0917e61e38 · outbound

This paper cites Energy efﬁcient AP selection for cell-free massive MIMO sy stems: Deep reinforcement learning approach,.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning Energy efﬁcient AP selection for cell-free massive MIMO sy stems: Deep reinforcement learning approach,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:04:08.983525Z

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 2c8f312a-fc21-4243-b7af-9f36f84f0252 · outbound

This paper cites Energy e fﬁciency maximization in RIS-aided cell-free network with limited b ackhaul,.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning Energy e fﬁciency maximization in RIS-aided cell-free network with limited b ackhaul,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:04:08.968203Z

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 f8808982-8659-4b5d-a5b3-b6a28f47a3ff · outbound

This paper cites Energy-ef ﬁcient cell-free network assisted by hybrid RISs,.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning Energy-ef ﬁcient cell-free network assisted by hybrid RISs,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:04:08.953284Z

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 210119c2-031a-4343-81b7-420c24f46ba6 · outbound

This paper cites On energ y efﬁciency of wideband RIS-aided cell-free network,.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning On energ y efﬁciency of wideband RIS-aided cell-free network,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:04:08.938339Z

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 d232a982-be57-416c-95e8-d50ae032e91c · outbound

This paper cites De ep rein- forcement learning for energy efﬁciency maximization in ca che-enabled cell-free massive MIMO networks: Single-and multi-agent a pproaches,.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning De ep rein- forcement learning for energy efﬁciency maximization in ca che-enabled cell-free massive MIMO networks: Single-and multi-agent a pproaches,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:04:08.922997Z

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 64be9bd0-e213-4c7a-9cbe-d3fa4ae03c0f · outbound

This paper cites Reconﬁgurable intelligen t surface as- sisted multiuser miso systems exploiting deep reinforceme nt learning,.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning Reconﬁgurable intelligen t surface as- sisted multiuser miso systems exploiting deep reinforceme nt learning,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:04:08.908432Z

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 d3073b11-d34d-4b85-bf42-5c020de73324 · outbound

This paper cites A distributed mac hine learning-based approach for IRS-enhanced cell-free MIMO n etworks,.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning A distributed mac hine learning-based approach for IRS-enhanced cell-free MIMO n etworks,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:04:08.890908Z

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 b8d937d4-3ca9-40b4-ac93-68653d1d7c46 · outbound

This paper cites Multi-agent reinforc ement learn- ing: A selective overview of theories and algorithms,.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning Multi-agent reinforc ement learn- ing: A selective overview of theories and algorithms,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:04:08.874492Z

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 e5f16935-6215-4ee3-bbc1-2d2b3dd7c7cf · outbound

This paper cites Multi-agent reinforcement learning-based pilot assignm ent for cell- free massive MIMO systems,.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning Multi-agent reinforcement learning-based pilot assignm ent for cell- free massive MIMO systems,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:04:08.857547Z

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 0843e8e8-8beb-4cc7-866b-b8d8304005d4 · outbound

This paper cites Double-laye r power control for mobile cell-free XL-MIMO with multi-agent rein forcement learning,.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning Double-laye r power control for mobile cell-free XL-MIMO with multi-agent rein forcement learning,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:04:08.842822Z

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 eac3f60f-3afe-415b-97bb-b6403004ef7a · outbound

This paper cites Access point clustering in cell-free massive MIMO using conventio nal and federated multi-agent reinforcement learning,.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning Access point clustering in cell-free massive MIMO using conventio nal and federated multi-agent reinforcement learning,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:04:08.828491Z

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 cc920d69-bb79-41e4-b2b6-743dc1061086 · outbound

This paper cites Uplink Power Control for Extremely Large-Scale MIMO with Multi-Agent Reinforcement Learning and Fuzzy Logic.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning Uplink Power Control for Extremely Large-Scale MIMO with Multi-Agent Reinforcement Learning and Fuzzy Logic

Reference 35

Resolution: verified exact; local_arxiv, observed 2026-08-12T19:04:08.629381Z

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 4890995e-efef-41a8-bac7-4b327ff8dccd · outbound

This paper cites Multi-agent r einforcement learning for distributed resource allocation in cell-free massive MIMO- enabled mobile edge computing network,.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning Multi-agent r einforcement learning for distributed resource allocation in cell-free massive MIMO- enabled mobile edge computing network,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:04:08.814224Z

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 16845aad-9ea1-4301-8f66-c857dd9579fa · outbound

This paper cites Multi-agent deep reinforcement learning for beam codebook design in RIS -aided systems,.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning Multi-agent deep reinforcement learning for beam codebook design in RIS -aided systems,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:04:08.798825Z

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 7fa8858a-3598-463a-913a-e8042384a039 · outbound

This paper cites Distributed learning for wireless commu nications: Methods, applications and challenges,.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning Distributed learning for wireless commu nications: Methods, applications and challenges,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:04:08.783761Z

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 6a2d4538-4af0-4a39-a438-7f481cd9f75b · outbound

This paper cites Smart and reconﬁgurable wireless communications: From IRS model ing to algorithm design,.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning Smart and reconﬁgurable wireless communications: From IRS model ing to algorithm design,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:04:08.768250Z

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 4f5bbbb8-6b37-4b94-94c7-71eda38d2b12 · outbound

This paper cites Making cell-free mas sive MIMO competitive with MMSE processing and centralized implemen tation,.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning Making cell-free mas sive MIMO competitive with MMSE processing and centralized implemen tation,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:04:08.753465Z

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 698f4121-1283-4389-a8b4-8eeb46d68eb7 · outbound

This paper cites Limited-fronthaul cell-free massive MIMO w ith local mmse receiver under rician fading and phase shifts,.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning Limited-fronthaul cell-free massive MIMO w ith local mmse receiver under rician fading and phase shifts,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:04:08.738850Z

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 8062cca5-ad1e-43be-90f7-9939a791101a · outbound

This paper cites On the total energy efﬁciency of cell-free massive MIMO,.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning On the total energy efﬁciency of cell-free massive MIMO,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:04:08.722458Z

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 c54cab2b-b14e-4c5a-ae04-7bc0acfadeb5 · outbound

This paper cites Reconﬁgurable intelligent surfaces for energy ef ﬁciency in wireless communication,.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning Reconﬁgurable intelligent surfaces for energy ef ﬁciency in wireless communication,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:04:08.706918Z

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 cabb37bb-8b02-4eb6-b38a-f57e72e4163b · outbound

This paper cites Power control in cellular massive MIMO with varying user activity : A deep learning solution,.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning Power control in cellular massive MIMO with varying user activity : A deep learning solution,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:04:08.691330Z

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 a2153883-daaf-4881-8183-03fb0aabff40 · outbound

This paper cites Emergent communication in multi-agent reinfor cement learning for future wireless networks,.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning Emergent communication in multi-agent reinfor cement learning for future wireless networks,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:04:08.675893Z

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 23812b77-d8bd-4dcd-aae0-4938e659db39 · outbound

This paper cites H´ ajek,Metamathematics of fuzzy logic.

Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning H´ ajek,Metamathematics of fuzzy logic

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:04:08.661467Z

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.

Pith citing papers

Observation 5612c2ad-aa8b-4c4d-8611-614c2aba6afa · inbound

Multi-Agent Reinforcement Learning in Wireless Distributed Networks for 6G cites this paper.

Multi-Agent Reinforcement Learning in Wireless Distributed Networks for 6G Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning

Reference 242

Resolution: unresolved; no resolver link, observed 2026-08-08T17:54:46.826752Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f9ff4517-4691-46b9-a40f-a8a329bc88a5 · inbound

Energy-Efficient SIM-assisted Communications: How Many Layers Do We Need? cites this paper.

Energy-Efficient SIM-assisted Communications: How Many Layers Do We Need? Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-16T11:26:19.816502Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 19fbcce5-1125-4107-b6a8-cd43552ca350 · inbound

Energy Saving for Cell-Free Massive MIMO Networks: A Multi-Agent Deep Reinforcement Learning Approach cites this paper.

Energy Saving for Cell-Free Massive MIMO Networks: A Multi-Agent Deep Reinforcement Learning Approach Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-11T06:26:01.204974Z

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.