Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach | Paper Citation Record

Observation df127baa-659f-4b7c-951d-65579cf92527 · outbound

This paper cites ElSawy, E.

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach ElSawy, E

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:32:14.294685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation fb3566a8-25d8-4013-a6b9-85c171a5cb38 · outbound

This paper cites Next generation 5G wireless networks: A comprehensive survey,.

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach Next generation 5G wireless networks: A comprehensive survey,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:32:14.280054Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1188a7df-3756-48fa-8114-41cf394e550b · outbound

This paper cites White paper on 5G bearer require- ments,.

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach White paper on 5G bearer require- ments,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:32:14.265881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 932907fe-ac6d-42fd-955c-63dfaf2cc791 · outbound

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

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach On the road to 6G: Visions, requirements, key technologies, and testbeds,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:32:14.250973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3023b161-b685-4db7-abd2-1760f9c897a7 · outbound

This paper cites NR: The new 5G radio access technology,.

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach NR: The new 5G radio access technology,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:32:14.236237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e697128b-bada-401e-a730-af3c9f3236b7 · outbound

This paper cites Introducing 5G advanced,.

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach Introducing 5G advanced,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:32:14.219697Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 95939694-f224-49b7-ac4d-d87bb2ba0fd7 · outbound

This paper cites Multiple access integrated adaptive finite blocklength for ultra-low delay in 6G wireless networks,.

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach Multiple access integrated adaptive finite blocklength for ultra-low delay in 6G wireless networks,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:32:14.204265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 78d34a13-3f50-4da0-9cd3-8e6bfdb835e9 · outbound

This paper cites Resource allocation for high-reliability low-latency vehicular communications with packet retransmission,.

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach Resource allocation for high-reliability low-latency vehicular communications with packet retransmission,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:32:14.190013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 38a6c0a8-2464-4d4a-84ea-f3439d37d145 · outbound

This paper cites A comprehensive survey on mobility-aware D2D communications: Princi- ples, practice and challenges,.

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach A comprehensive survey on mobility-aware D2D communications: Princi- ples, practice and challenges,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:32:14.175200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d6faaf9f-f398-4903-bf38-17725bf3ba4b · outbound

This paper cites Delay optimal scheduling for ARQ-aided power-constrained packet transmission over multi-state fading channels,.

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach Delay optimal scheduling for ARQ-aided power-constrained packet transmission over multi-state fading channels,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:32:14.158592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6c660bc9-7079-4349-9339-a652bf4636ff · outbound

This paper cites Optimal delay-power tradeoff in wireless transmission with fixed modulation,.

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach Optimal delay-power tradeoff in wireless transmission with fixed modulation,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:32:14.142831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5cfb9fb5-54d1-44fd-9eb6-75d0259369fd · outbound

This paper cites Resource allocation for D2D-enabled vehicular communications,.

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach Resource allocation for D2D-enabled vehicular communications,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:32:14.126884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d734275e-7c87-481b-a634-2ee84828143b · outbound

This paper cites Joint rate control and power allocation for non-orthogonal multiple access systems,.

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach Joint rate control and power allocation for non-orthogonal multiple access systems,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:32:14.110569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2bff8cba-0230-47d2-9fbc-745f662db2fa · outbound

This paper cites Joint power control and rate allocation enabling ultra-reliability and energy efficiency in SIMO wireless networks,.

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach Joint power control and rate allocation enabling ultra-reliability and energy efficiency in SIMO wireless networks,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:32:14.094206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5617dc6f-1c56-4a55-aab5-e398d69a93ea · outbound

This paper cites Resource allocation for low-latency vehicular communications: An effective capacity perspective,.

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach Resource allocation for low-latency vehicular communications: An effective capacity perspective,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:32:14.077699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4ea08f4c-c17c-4d1f-b701-8569a9fb009f · outbound

This paper cites Deep reinforcement learning based resource allocation for V2V communications,.

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach Deep reinforcement learning based resource allocation for V2V communications,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:32:14.062968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 065823a1-4328-4c9e-8e3e-c19a201a9f0a · outbound

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

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach Spectrum sharing in vehicular networks based on multi-agent reinforcement learning,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:32:14.048258Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 62dba366-d087-4146-9d0f-ff000d18541a · outbound

This paper cites Intelligent delay-aware partial computing task offloading for multiuser industrial internet of things through edge computing,.

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach Intelligent delay-aware partial computing task offloading for multiuser industrial internet of things through edge computing,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:32:14.033215Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a7b9d7c4-c5b5-46f2-ba99-e98c65605f92 · outbound

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

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach SOQ: Structural reinforcement learning for constrained delay minimization with channel state information,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:32:14.018008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c5f59b33-8176-42c3-9b47-607d9494ca06 · outbound

This paper cites Semi-supervised classification with graph convolutional networks,.

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach Semi-supervised classification with graph convolutional networks,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-15T20:32:13.424368Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 514b92c2-0af5-477b-8ece-3801213de86c · outbound

This paper cites Graph attention networks,.

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach Graph attention networks,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-15T20:32:13.428906Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 38106887-b6ec-46d9-97a4-2131e17537d5 · outbound

This paper cites Graph neural networks: A review of methods and applications,.

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach Graph neural networks: A review of methods and applications,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:32:13.981384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 812544d7-777e-41d5-acc8-98d99ca613de · outbound

This paper cites Learning decentralized wireless resource allocations with graph neural networks,.

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach Learning decentralized wireless resource allocations with graph neural networks,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:32:13.966054Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c76b9619-bd19-485e-8eb1-90276bd49247 · outbound

This paper cites Optimal wireless resource allocation with random edge graph neural networks,.

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach Optimal wireless resource allocation with random edge graph neural networks,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:32:13.951958Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 333f8f15-b932-4fc2-a6b4-34b89a43bede · outbound

This paper cites Graph neural networks for scalable radio resource management: Architecture design and theoretical analysis,.

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach Graph neural networks for scalable radio resource management: Architecture design and theoretical analysis,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:32:13.937493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation de463e44-4040-4014-a7b0-55eecc8d4fa7 · outbound

This paper cites Decentralized inference with graph neural networks in wireless communication systems,.

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach Decentralized inference with graph neural networks in wireless communication systems,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:32:13.922673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ee40256d-ec84-4f67-8df1-7473a5d3bb30 · outbound

This paper cites Graph neural networks for wireless communications: From theory to practice,.

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach Graph neural networks for wireless communications: From theory to practice,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:32:13.908454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 85ad2c5d-993d-4a26-9843-35022f362ab2 · outbound

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

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach Learning resilient radio resource management policies with graph neural networks,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:32:13.893218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 8e423613-88a4-40d5-8319-64184a4e3ff7 · outbound

This paper cites Learning repre- sentations by back-propagating errors,.

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach Learning repre- sentations by back-propagating errors,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:32:13.876804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 041dc68e-0ce5-476f-8a82-31cb5666c6ec · outbound

This paper cites Long short-term memory,.

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach Long short-term memory,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:32:13.862935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 961112bd-9cad-49ee-9e23-41406a6bb294 · outbound

This paper cites Attention is all you need,.

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach Attention is all you need,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:32:13.848368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 63c1feed-d755-443a-ba2a-48bc77071259 · outbound

This paper cites Graph representation learning for wireless communications,.

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach Graph representation learning for wireless communications,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:32:13.834823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0614551f-cea7-418e-a592-38e20d3d8289 · outbound

This paper cites Graph neural networks for wireless networks: Graph representation, architecture and evaluation,.

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach Graph neural networks for wireless networks: Graph representation, architecture and evaluation,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:32:13.821018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 33a754cb-9780-4e1d-bdf2-d445fdbee618 · outbound

This paper cites State-augmented learn- able algorithms for resource management in wireless networks,.

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach State-augmented learn- able algorithms for resource management in wireless networks,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:32:13.806318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 72f34248-6bd7-441d-aa3c-81da117bcbb2 · outbound

This paper cites Large-Scale Graph Reinforcement Learning in Wireless Control Systems.

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach Large-Scale Graph Reinforcement Learning in Wireless Control Systems

Reference 35

Resolution: verified exact; local_arxiv, observed 2026-08-15T20:32:13.610751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b53ea792-deee-476d-8acf-379bec060605 · outbound

This paper cites Mutual-interference-aware through- put enhancement in massive IoT: A graph reinforcement learning frame- work,.

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach Mutual-interference-aware through- put enhancement in massive IoT: A graph reinforcement learning frame- work,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:32:13.790979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 8a5e9ae3-00b6-4e13-9bf8-e5f3de396d11 · outbound

This paper cites Graph-reinforcement-learning-based task offloading for multiaccess edge computing,.

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach Graph-reinforcement-learning-based task offloading for multiaccess edge computing,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:32:13.776192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 10ae59de-3ff8-4e41-adff-c1116f89d45a · outbound

This paper cites Multi-flow transmission in wireless interference networks: A convergent graph learning approach,.

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach Multi-flow transmission in wireless interference networks: A convergent graph learning approach,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:32:13.760960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2b902d06-61c2-46aa-95dd-28981196d771 · outbound

This paper cites Graph neural network meets multi- agent reinforcement learning: Fundamentals, applications, and future directions,.

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach Graph neural network meets multi- agent reinforcement learning: Fundamentals, applications, and future directions,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:32:13.746529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 8fa90554-ab7f-4852-b926-e84690ccce19 · outbound

This paper cites Task placement and resource allocation for edge machine learning: A GNN-based multi- agent reinforcement learning paradigm,.

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach Task placement and resource allocation for edge machine learning: A GNN-based multi- agent reinforcement learning paradigm,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:32:13.730843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5e110983-7230-469d-b45d-074a112eab3e · outbound

This paper cites ASAP: Adaptive structure aware pooling for learning hierarchical graph representations,.

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach ASAP: Adaptive structure aware pooling for learning hierarchical graph representations,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:32:13.713310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2298bbca-6ccb-4005-af7e-a0afd676ee0a · outbound

This paper cites Proximal Policy Optimization Algorithms.

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach Proximal Policy Optimization Algorithms

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-15T20:32:13.522576Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 24826b6b-7e77-4852-99ca-b7fe4b61fdfe · outbound

This paper cites Resource man- agement with deep reinforcement learning,.

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach Resource man- agement with deep reinforcement learning,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:32:13.697889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation abd448f6-2160-4bfc-9388-15202626cf7d · outbound

This paper cites Downlink cellular network analysis with multi-slope path loss models,.

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach Downlink cellular network analysis with multi-slope path loss models,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:32:13.682199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation cc1b4868-25d6-49d9-9df7-1fcbcb6f4c2c · outbound

This paper cites Are we approaching the fundamental limits of wireless network densification?.

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach Are we approaching the fundamental limits of wireless network densification?

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:32:13.667590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b8bee1a9-dd87-4978-80f4-c5a00e537e1b · outbound

This paper cites ITLinQ: A new approach for spectrum sharing in device-to-device communication systems,.

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach ITLinQ: A new approach for spectrum sharing in device-to-device communication systems,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:32:13.651828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d4e83085-5653-4914-b17c-421d728090d4 · outbound

This paper cites An iteratively weighted MMSE approach to distributed sum-utility maximization for a MIMO interfering broadcast channel,.

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach An iteratively weighted MMSE approach to distributed sum-utility maximization for a MIMO interfering broadcast channel,

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-15T20:32:13.544502Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7922c5f1-661f-4006-be65-50ee573979e6 · outbound

This paper cites Addressing function approxi- mation error in actor-critic methods,.

Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach Addressing function approxi- mation error in actor-critic methods,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:32:13.627600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers