Paper Citation Record · LEDGER

Joint User Priority and Power Scheduling for QoS-Aware WMMSE Precoding: A Constrained-Actor Attentive-Critic Approach

As of 23 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:2506.16074.

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

pith.paper-citation-record.v1
2506.16074 v1

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:51:48.640455Z

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+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

15 of 15 outbound references displayed

verified exact0
verified fuzzy14
unresolved1
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6604f713-dc0d-4637-95aa-3b5fa33b2702 · outbound

This paper cites Multiagent deep-reinforcement- learning-based resource allocation for heterogeneous qos guarantees for vehicular networks,.

Joint User Priority and Power Scheduling for QoS-Aware WMMSE Precoding: A Constrained-Actor Attentive-Critic Approach Multiagent deep-reinforcement- learning-based resource allocation for heterogeneous qos guarantees for vehicular networks,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:51:51.066312Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 73999219-10e6-40bf-8610-8b46b97d25e3 · outbound

This paper cites Energy-efficient star-ris-aided mu-mimo for next-generation urllc sys- tems,.

Joint User Priority and Power Scheduling for QoS-Aware WMMSE Precoding: A Constrained-Actor Attentive-Critic Approach Energy-efficient star-ris-aided mu-mimo for next-generation urllc sys- tems,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:51:50.895095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c9a4b1a1-7cb9-4a36-922f-2df4f110a445 · outbound

This paper cites Rethinking WMMSE: Can its complexity scale linearly with the number of BS antennas?.

Joint User Priority and Power Scheduling for QoS-Aware WMMSE Precoding: A Constrained-Actor Attentive-Critic Approach Rethinking WMMSE: Can its complexity scale linearly with the number of BS antennas?

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:51:50.759767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 1b9c0ec2-cfd1-447b-b4e3-e282bcf2496a · outbound

This paper cites Iterative algorithm induced deep-unfolding neural networks: Precoding design for multiuser MIMO systems,.

Joint User Priority and Power Scheduling for QoS-Aware WMMSE Precoding: A Constrained-Actor Attentive-Critic Approach Iterative algorithm induced deep-unfolding neural networks: Precoding design for multiuser MIMO systems,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:51:50.595617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation b4743ecb-8b7b-425f-b1f5-24eff73b47f4 · outbound

This paper cites Robust wmmse-based precoder with practice- oriented design for massive mu-mimo,.

Joint User Priority and Power Scheduling for QoS-Aware WMMSE Precoding: A Constrained-Actor Attentive-Critic Approach Robust wmmse-based precoder with practice- oriented design for massive mu-mimo,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:51:50.411043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation d9c0112b-6654-4887-b10f-1af5cd047b6d · outbound

This paper cites Low complexity multiuser mimo scheduling for weighted sum rate maximization,.

Joint User Priority and Power Scheduling for QoS-Aware WMMSE Precoding: A Constrained-Actor Attentive-Critic Approach Low complexity multiuser mimo scheduling for weighted sum rate maximization,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:51:50.234869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 8055aa3e-9581-4c2d-9289-ecaa452a1bfc · outbound

This paper cites A survey on opportunistic scheduling in wireless communications,.

Joint User Priority and Power Scheduling for QoS-Aware WMMSE Precoding: A Constrained-Actor Attentive-Critic Approach A survey on opportunistic scheduling in wireless communications,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:51:50.047975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 5e9c131a-b68f-4704-ad95-0fd87ea2c3cc · outbound

This paper cites Generalizable resource scaling of 5G slices using constrained reinforce- ment learning,.

Joint User Priority and Power Scheduling for QoS-Aware WMMSE Precoding: A Constrained-Actor Attentive-Critic Approach Generalizable resource scaling of 5G slices using constrained reinforce- ment learning,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:51:49.872658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 89c509c3-dfd6-405d-82d7-d8beeaeda31b · outbound

This paper cites Clara: A constrained reinforcement learning based resource allocation framework for network slicing,.

Joint User Priority and Power Scheduling for QoS-Aware WMMSE Precoding: A Constrained-Actor Attentive-Critic Approach Clara: A constrained reinforcement learning based resource allocation framework for network slicing,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:51:49.716208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c6ef42fb-ff25-4355-b6fb-c2e639e1bf5f · outbound

This paper cites Soft actor-critic- based multi-user multi-tti mimo precoding in multi-modal real-time broadband communications,.

Joint User Priority and Power Scheduling for QoS-Aware WMMSE Precoding: A Constrained-Actor Attentive-Critic Approach Soft actor-critic- based multi-user multi-tti mimo precoding in multi-modal real-time broadband communications,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:51:49.526659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 667f0cfc-f37b-4e6f-90c8-7d41756cd78f · outbound

This paper cites Benchmarking Batch Deep Reinforcement Learning Algorithms.

Joint User Priority and Power Scheduling for QoS-Aware WMMSE Precoding: A Constrained-Actor Attentive-Critic Approach Benchmarking Batch Deep Reinforcement Learning Algorithms

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T23:51:48.290281Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 06329b62-9005-4e82-8397-e1cd2ee9d6f5 · outbound

This paper cites Constrained policy optimization,.

Joint User Priority and Power Scheduling for QoS-Aware WMMSE Precoding: A Constrained-Actor Attentive-Critic Approach Constrained policy optimization,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:51:49.365147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 9df551e8-db6c-4866-b6d7-7e8a1967de9c · outbound

This paper cites Successive convex approx- imation based off-policy optimization for constrained reinforcement learning,.

Joint User Priority and Power Scheduling for QoS-Aware WMMSE Precoding: A Constrained-Actor Attentive-Critic Approach Successive convex approx- imation based off-policy optimization for constrained reinforcement learning,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:51:49.174973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c56142ca-5479-495c-a833-7fe13d2ceaea · outbound

This paper cites A finite-time analysis of Q-learning with neural network function approximation,.

Joint User Priority and Power Scheduling for QoS-Aware WMMSE Precoding: A Constrained-Actor Attentive-Critic Approach A finite-time analysis of Q-learning with neural network function approximation,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:51:49.035625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a05719ba-decd-4f9a-a690-005765d19355 · outbound

This paper cites Multi-agent deep reinforcement learning for dynamic power allocation in wireless networks,.

Joint User Priority and Power Scheduling for QoS-Aware WMMSE Precoding: A Constrained-Actor Attentive-Critic Approach Multi-agent deep reinforcement learning for dynamic power allocation in wireless networks,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:51:48.845702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Pith citing papers

No inbound Pith citation observations are available.