Paper Citation Record · LEDGER

Deep Reinforcement Learning-Based Scheduling for Wi-Fi Multi-Access Point Coordination

As of 23 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 0 inbound Pith citation observations for arXiv:2507.19377.

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

pith.paper-citation-record.v1
2507.19377 v1

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T17:57:55.037291Z

measured 25 of 25 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

25 of 25 outbound references displayed

verified exact1
verified fuzzy17
unresolved7
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 01b848b3-d597-4801-8f01-1f2bf392035f · outbound

This paper cites Limita- tions of the IEEE 802.11 DCF, PCF, EDCA and HCCA to handle real- time traffic,.

Deep Reinforcement Learning-Based Scheduling for Wi-Fi Multi-Access Point Coordination Limita- tions of the IEEE 802.11 DCF, PCF, EDCA and HCCA to handle real- time traffic,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:57:55.465794Z

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 9000b7d4-9b56-4158-9ae5-724e66427e7c · outbound

This paper cites What will Wi-Fi 8 be? A primer on IEEE 802.11 bn ultra high reliability,.

Deep Reinforcement Learning-Based Scheduling for Wi-Fi Multi-Access Point Coordination What will Wi-Fi 8 be? A primer on IEEE 802.11 bn ultra high reliability,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-15T17:57:54.941641Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6366c372-5671-47f2-8509-f7c7dc61f7ca · outbound

This paper cites Spatial Reuse in IEEE 802.11bn Coordinated Multi-AP WLANs: A Throughput Analysis.

Deep Reinforcement Learning-Based Scheduling for Wi-Fi Multi-Access Point Coordination Spatial Reuse in IEEE 802.11bn Coordinated Multi-AP WLANs: A Throughput Analysis

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-15T17:57:54.945888Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation febd9033-d62e-47ce-a4e7-566c8c3d9f74 · outbound

This paper cites Wi-Fi 8 Unveiled: Key Features, Multi-AP Coordination, and the Role of C-TDMA,.

Deep Reinforcement Learning-Based Scheduling for Wi-Fi Multi-Access Point Coordination Wi-Fi 8 Unveiled: Key Features, Multi-AP Coordination, and the Role of C-TDMA,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:57:55.448287Z

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 c65cb956-4ab5-42b6-8cea-b4cdeb3af91e · outbound

This paper cites Enabling Reliable Latency in Wi-Fi 8 Through Multi-AP Joint Scheduling,.

Deep Reinforcement Learning-Based Scheduling for Wi-Fi Multi-Access Point Coordination Enabling Reliable Latency in Wi-Fi 8 Through Multi-AP Joint Scheduling,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:57:55.437971Z

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 ea0e49eb-0fef-4a3d-9af6-307da1764a11 · outbound

This paper cites Collaborative spatial reuse in wireless networks via selfish multi-armed bandits,.

Deep Reinforcement Learning-Based Scheduling for Wi-Fi Multi-Access Point Coordination Collaborative spatial reuse in wireless networks via selfish multi-armed bandits,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:57:55.427735Z

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 1e1b7306-618a-4fe8-ae29-ed00dc7ae1b4 · outbound

This paper cites Potential and pitfalls of multi-armed bandits for decen- tralized spatial reuse in WLANs,.

Deep Reinforcement Learning-Based Scheduling for Wi-Fi Multi-Access Point Coordination Potential and pitfalls of multi-armed bandits for decen- tralized spatial reuse in WLANs,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:57:55.416754Z

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 612989ef-beab-49e7-a267-1a3feda7e585 · outbound

This paper cites Improving the spatial reuse in IEEE 802.11 ax WLANs: A multi-armed bandit approach,.

Deep Reinforcement Learning-Based Scheduling for Wi-Fi Multi-Access Point Coordination Improving the spatial reuse in IEEE 802.11 ax WLANs: A multi-armed bandit approach,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:57:55.407047Z

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 210aae00-361e-4a38-96b8-820137c63f1f · outbound

This paper cites Reinforcement Learning Approaches to Improve Spatial Reuse in Wireless Local Area Networks,.

Deep Reinforcement Learning-Based Scheduling for Wi-Fi Multi-Access Point Coordination Reinforcement Learning Approaches to Improve Spatial Reuse in Wireless Local Area Networks,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:57:55.397233Z

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 be70907b-8328-4b20-8184-d469bac67204 · outbound

This paper cites Machine Learning and Wi-Fi: Unveiling the Path Toward AI/ML-Native IEEE 802.11 Networks,.

Deep Reinforcement Learning-Based Scheduling for Wi-Fi Multi-Access Point Coordination Machine Learning and Wi-Fi: Unveiling the Path Toward AI/ML-Native IEEE 802.11 Networks,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:57:55.387230Z

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 e362ad63-38fd-4bc1-8e05-b3d6027f891a · outbound

This paper cites Coordinated Multi-Armed Bandits for Improved Spatial Reuse in Wi-Fi.

Deep Reinforcement Learning-Based Scheduling for Wi-Fi Multi-Access Point Coordination Coordinated Multi-Armed Bandits for Improved Spatial Reuse in Wi-Fi

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-08-15T17:57:55.240926Z

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 13f38d5d-ee0b-4dab-ac3d-cd8159b9b027 · outbound

This paper cites IEEE 802.11bn Multi-AP Coordinated Spatial Reuse With Hierarchical Multi-Armed Bandits,.

Deep Reinforcement Learning-Based Scheduling for Wi-Fi Multi-Access Point Coordination IEEE 802.11bn Multi-AP Coordinated Spatial Reuse With Hierarchical Multi-Armed Bandits,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:57:55.376352Z

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 fe47bd79-89bc-4598-aefc-82bb2ed53c1e · outbound

This paper cites Coordinated Spatial Reuse Scheduling With Machine Learning in IEEE 802.11 MAPC Networks,.

Deep Reinforcement Learning-Based Scheduling for Wi-Fi Multi-Access Point Coordination Coordinated Spatial Reuse Scheduling With Machine Learning in IEEE 802.11 MAPC Networks,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:57:55.364878Z

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 69d53bce-ec82-4d44-8a34-d72dec29694d · outbound

This paper cites ReinWiFi: Application-Layer QoS Optimization of WiFi Networks with Reinforcement Learning,.

Deep Reinforcement Learning-Based Scheduling for Wi-Fi Multi-Access Point Coordination ReinWiFi: Application-Layer QoS Optimization of WiFi Networks with Reinforcement Learning,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:57:55.352030Z

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 f16e290f-8c5e-45aa-8791-738856c472ea · outbound

This paper cites Spatial Deep Learning for Wireless Scheduling,.

Deep Reinforcement Learning-Based Scheduling for Wi-Fi Multi-Access Point Coordination Spatial Deep Learning for Wireless Scheduling,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-15T17:57:54.995909Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1502cfa1-e690-4136-a153-b8e292231651 · outbound

This paper cites Deep Reinforcement Learning Based Spatial Reuse for IEEE 802.11 bn,.

Deep Reinforcement Learning-Based Scheduling for Wi-Fi Multi-Access Point Coordination Deep Reinforcement Learning Based Spatial Reuse for IEEE 802.11 bn,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:57:55.339988Z

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 28fe4df0-68b5-42ad-8e6c-1fc77fde9edf · outbound

This paper cites IEEE 802.11-25/0502r0: Details on the unified MAPC framework,.

Deep Reinforcement Learning-Based Scheduling for Wi-Fi Multi-Access Point Coordination IEEE 802.11-25/0502r0: Details on the unified MAPC framework,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:57:55.325066Z

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 1a13a7e6-a782-48c7-b448-66591b3a9074 · outbound

This paper cites Gymnasium: A Standard Interface for Reinforcement Learning Environments.

Deep Reinforcement Learning-Based Scheduling for Wi-Fi Multi-Access Point Coordination Gymnasium: A Standard Interface for Reinforcement Learning Environments

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-15T17:57:55.008416Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 03a2c5e1-aa11-4b5d-9e9b-b96247611d27 · outbound

This paper cites A Markovian Decision Process,.

Deep Reinforcement Learning-Based Scheduling for Wi-Fi Multi-Access Point Coordination A Markovian Decision Process,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-15T17:57:55.015718Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0eaf4acc-3d85-45dd-8c76-48cbbee8f838 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Deep Reinforcement Learning-Based Scheduling for Wi-Fi Multi-Access Point Coordination Proximal Policy Optimization Algorithms

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-15T17:57:55.020453Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 79330872-9726-4387-87d9-55de78428a03 · outbound

This paper cites Actor-Critic Algorithms,.

Deep Reinforcement Learning-Based Scheduling for Wi-Fi Multi-Access Point Coordination Actor-Critic Algorithms,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:57:55.311452Z

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 7ab37ac2-024d-4f71-963b-371fe82332e2 · outbound

This paper cites TGax Simulation Scenarios,.

Deep Reinforcement Learning-Based Scheduling for Wi-Fi Multi-Access Point Coordination TGax Simulation Scenarios,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:57:55.297369Z

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 ca64168b-0ef2-461c-8aa2-f1bc0991ff4b · outbound

This paper cites 802.11be Packet Error Rate Simulation for an EHT MU Single-User Packet Format,.

Deep Reinforcement Learning-Based Scheduling for Wi-Fi Multi-Access Point Coordination 802.11be Packet Error Rate Simulation for an EHT MU Single-User Packet Format,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:57:55.282550Z

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 4f42c297-216a-41c7-a81e-18f91a010626 · outbound

This paper cites Stable-Baselines3: Reliable Reinforcement Learning Implementations,.

Deep Reinforcement Learning-Based Scheduling for Wi-Fi Multi-Access Point Coordination Stable-Baselines3: Reliable Reinforcement Learning Implementations,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:57:55.269040Z

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 6ae35746-0fd3-4793-9cd2-334d07f0cdab · outbound

This paper cites ReinWiFi: Application-Layer QoS Optimization of WiFi Networks with Reinforcement Learning.

Deep Reinforcement Learning-Based Scheduling for Wi-Fi Multi-Access Point Coordination ReinWiFi: Application-Layer QoS Optimization of WiFi Networks with Reinforcement Learning

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-15T17:57:54.991986Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.