Paper Citation Record · LEDGER

Average Reward Reinforcement Learning for Wireless Radio Resource Management

As of 23 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2501.06700.

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

pith.paper-citation-record.v1
2501.06700 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:58:03.027593Z

measured 32 of 32 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

32 of 32 outbound references displayed

verified exact1
verified fuzzy27
unresolved4
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fe418e7b-8936-457b-be7e-cf0d22d8cbb8 · outbound

This paper cites Reinforcement learning: An introduction by richards’ sutton,.

Average Reward Reinforcement Learning for Wireless Radio Resource Management Reinforcement learning: An introduction by richards’ sutton,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:58:03.622682Z

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 63e51f31-3ce3-41dd-a0f5-29f0c4a04cee · outbound

This paper cites Average-reward off- policy policy evaluation with function approximation,.

Average Reward Reinforcement Learning for Wireless Radio Resource Management Average-reward off- policy policy evaluation with function approximation,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:58:03.606153Z

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 9be1150f-6663-4a75-9b9c-539ee364bde6 · outbound

This paper cites Off-policy average reward actor-critic with deterministic policy search,.

Average Reward Reinforcement Learning for Wireless Radio Resource Management Off-policy average reward actor-critic with deterministic policy search,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:58:03.589049Z

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 153af67c-6a51-4bce-a795-01b689aa1b11 · outbound

This paper cites Power control for a network of access points,.

Average Reward Reinforcement Learning for Wireless Radio Resource Management Power control for a network of access points,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:58:03.573092Z

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 444c08a9-f2dd-430c-992a-1da342f5233d · outbound

This paper cites Base station employing shared resources among antenna units,.

Average Reward Reinforcement Learning for Wireless Radio Resource Management Base station employing shared resources among antenna units,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:58:03.556489Z

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 832225f1-a78d-4760-b37c-37bcf3a5e033 · outbound

This paper cites Methods and apparatus for power management in a wireless communication system,.

Average Reward Reinforcement Learning for Wireless Radio Resource Management Methods and apparatus for power management in a wireless communication system,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:58:03.538941Z

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 9b85fed7-2f67-4e5f-a05b-86b4a65ceb9e · outbound

This paper cites Generalized global bandit and its application in cellular coverage optimization,.

Average Reward Reinforcement Learning for Wireless Radio Resource Management Generalized global bandit and its application in cellular coverage optimization,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:58:03.522036Z

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 3048fc99-bf64-4f0d-87f0-7383e2230e45 · outbound

This paper cites A non-stationary online learning approach to mobility management,.

Average Reward Reinforcement Learning for Wireless Radio Resource Management A non-stationary online learning approach to mobility management,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:58:03.505499Z

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 8b685e6b-9a91-481d-822e-971cf0f84b39 · outbound

This paper cites A Deep Q-Learning Method for Downlink Power Allocation in Multi-Cell Networks.

Average Reward Reinforcement Learning for Wireless Radio Resource Management A Deep Q-Learning Method for Downlink Power Allocation in Multi-Cell Networks

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-10T20:58:02.908832Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8f0986a6-d45d-476f-b06d-17ed7a5f424d · outbound

This paper cites Power allocation in multi-user cellular networks with deep Q learning approach,.

Average Reward Reinforcement Learning for Wireless Radio Resource Management Power allocation in multi-user cellular networks with deep Q learning approach,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:58:03.487857Z

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 d86cf87a-3445-470b-a252-e99e5069f05f · outbound

This paper cites Joint power control and channel allocation for interference mitigation based on reinforcement learning,.

Average Reward Reinforcement Learning for Wireless Radio Resource Management Joint power control and channel allocation for interference mitigation based on reinforcement learning,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:58:03.469648Z

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 e896803b-aba4-4573-b966-ed5796e76b39 · outbound

This paper cites Deep actor-critic learning for distributed power control in wireless mobile networks,.

Average Reward Reinforcement Learning for Wireless Radio Resource Management Deep actor-critic learning for distributed power control in wireless mobile networks,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:58:03.447250Z

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 a9e7afcb-a20d-4767-806d-f055c673c843 · outbound

This paper cites Deep reinforcement learning based wire- less network optimization: A comparative study,.

Average Reward Reinforcement Learning for Wireless Radio Resource Management Deep reinforcement learning based wire- less network optimization: A comparative study,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:58:03.429992Z

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 4a8fb1ba-fd12-4558-8c98-551e9435361f · outbound

This paper cites ColO- RAN: Developing Machine Learning-based xApps for Open RAN Closed-loop Control on Programmable Experimental Platforms,.

Average Reward Reinforcement Learning for Wireless Radio Resource Management ColO- RAN: Developing Machine Learning-based xApps for Open RAN Closed-loop Control on Programmable Experimental Platforms,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:58:03.412476Z

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 0efcb88b-4d34-4582-8df1-cf93c067722c · outbound

This paper cites FlexRAN: A flexible and programmable platform for software- defined radio access networks,.

Average Reward Reinforcement Learning for Wireless Radio Resource Management FlexRAN: A flexible and programmable platform for software- defined radio access networks,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:58:03.396691Z

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 04d1d7ad-6a01-41cf-9b35-9849bb3fec9e · outbound

This paper cites Deep reinforcement learning for joint spectrum and power allocation in cellular networks,.

Average Reward Reinforcement Learning for Wireless Radio Resource Management Deep reinforcement learning for joint spectrum and power allocation in cellular networks,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:58:03.376074Z

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 8c8a43ac-33d9-4d35-aeda-e0329a01963f · outbound

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

Average Reward Reinforcement Learning for Wireless Radio Resource Management Multi-agent deep reinforcement learning for dynamic power allocation in wireless networks,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:58:03.359596Z

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 abbb5159-d0a4-4f5a-a14c-376c7d667aa0 · outbound

This paper cites Multi- agent reinforcement learning for wireless user scheduling: Performance, scalablility, and generalization,.

Average Reward Reinforcement Learning for Wireless Radio Resource Management Multi- agent reinforcement learning for wireless user scheduling: Performance, scalablility, and generalization,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:58:03.340416Z

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 4786d838-3339-4a54-a55a-9d0ad12459ac · outbound

This paper cites Resource management in wireless networks via multi-agent deep reinforcement learning,.

Average Reward Reinforcement Learning for Wireless Radio Resource Management Resource management in wireless networks via multi-agent deep reinforcement learning,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-10T20:58:02.958639Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9f6fe38c-60b8-4321-a8e6-407c26949b68 · outbound

This paper cites Distributed MARL for scheduling in conflict graphs,.

Average Reward Reinforcement Learning for Wireless Radio Resource Management Distributed MARL for scheduling in conflict graphs,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:58:03.311863Z

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 d2de51e2-2bdd-4ffa-9194-8accdc97981a · outbound

This paper cites Offline reinforcement learning for wireless network optimization with mixture datasets,.

Average Reward Reinforcement Learning for Wireless Radio Resource Management Offline reinforcement learning for wireless network optimization with mixture datasets,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:58:03.295227Z

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 3daa3c11-e5c9-4b28-bc45-5af3768177b2 · outbound

This paper cites Advancing RAN slicing with offline reinforcement learning,.

Average Reward Reinforcement Learning for Wireless Radio Resource Management Advancing RAN slicing with offline reinforcement learning,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:58:03.279124Z

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 0fc23e0a-4c89-4b71-abaf-532fb6834614 · outbound

This paper cites Mean-variance policy iteration for risk-averse reinforcement learning,.

Average Reward Reinforcement Learning for Wireless Radio Resource Management Mean-variance policy iteration for risk-averse reinforcement learning,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:58:03.261064Z

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 e0aed05d-01fa-49d7-8e9f-d6d13de8f23a · outbound

This paper cites Averaged-dqn: Variance reduc- tion and stabilization for deep reinforcement learning,.

Average Reward Reinforcement Learning for Wireless Radio Resource Management Averaged-dqn: Variance reduc- tion and stabilization for deep reinforcement learning,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:58:03.243701Z

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 38faea7d-0567-4d26-9138-308f0ede6ca3 · outbound

This paper cites Average-Reward Reinforcement Learning with Trust Region Methods.

Average Reward Reinforcement Learning for Wireless Radio Resource Management Average-Reward Reinforcement Learning with Trust Region Methods

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-10T20:58:02.992888Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 79263734-8de1-48bf-9c0d-79864f8f6157 · outbound

This paper cites The NS-3 network simulator,.

Average Reward Reinforcement Learning for Wireless Radio Resource Management The NS-3 network simulator,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:58:03.224731Z

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 bf85f0c0-a91e-49a3-b59b-75d2d16428ae · outbound

This paper cites Network slicing architecture,.

Average Reward Reinforcement Learning for Wireless Radio Resource Management Network slicing architecture,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:58:03.206772Z

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 a0c4bc3e-559f-45c2-8445-4840f43886d2 · outbound

This paper cites NetworkGym: Democratizing Network AI via Sim-aaS,.

Average Reward Reinforcement Learning for Wireless Radio Resource Management NetworkGym: Democratizing Network AI via Sim-aaS,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:58:03.188710Z

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 77cd05a6-0482-4fbd-8745-f0df02bb77af · outbound

This paper cites Soft Actor-Critic Algorithms and Applications.

Average Reward Reinforcement Learning for Wireless Radio Resource Management Soft Actor-Critic Algorithms and Applications

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-10T20:58:03.012480Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 75f746b8-3394-412e-9bdd-861ba0a638f8 · outbound

This paper cites A Deeper Look at Discounting Mismatch in Actor-Critic Algorithms.

Average Reward Reinforcement Learning for Wireless Radio Resource Management A Deeper Look at Discounting Mismatch in Actor-Critic Algorithms

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-08-10T20:58:03.078406Z

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 8a8d116c-0e34-452f-9949-38b760fd7858 · outbound

This paper cites Revisiting the minimalist approach to offline reinforcement learning,.

Average Reward Reinforcement Learning for Wireless Radio Resource Management Revisiting the minimalist approach to offline reinforcement learning,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:58:03.171997Z

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 9bc0867d-2531-42e9-b963-a953fdb3ed79 · outbound

This paper cites Supported policy optimization for offline reinforcement learning,.

Average Reward Reinforcement Learning for Wireless Radio Resource Management Supported policy optimization for offline reinforcement learning,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:58:03.154181Z

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.