Pith Number

pith:45QZRB3N

pith:2026:45QZRB3NCVWH2MPOVGGIZ37OE7

not attested not anchored not stored refs resolved

MAxLM: Multi-Agent Language Model-Based Scheduling and Resource Allocation in MU-MIMO-OFDMA-Enabled Wireless Networks

Adnan Quadri, Hongxiang Li

A multi-agent system using pretrained language models optimizes scheduling and resource allocation to increase uplink throughput in MU-MIMO-OFDMA wireless networks.

arxiv:2605.16144 v1 · 2026-05-15 · eess.SP · cs.MA · cs.NI

Open paper page JSON Open Graph Bundle Merged state Verified badge What is a Pith Number?

Add to your LaTeX paper

\usepackage{pith}
\pithnumber{45QZRB3NCVWH2MPOVGGIZ37OE7}

Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more · Embed verified badge

Record completeness

1 Bitcoin timestamp

2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

✓ Portable graph bundle live · download bundle · merged state

The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

Numerical results confirm that our proposed technique achieves higher UL-SA throughput than the benchmark techniques.

C2weakest assumption

The assumption that a general pretrained language model, without domain-specific fine-tuning or explicit mathematical modeling of the wireless channel, can reliably produce near-optimal scheduling decisions across varying numbers of stations and antenna configurations.

C3one line summary

A multi-agent language model approach delivers higher uplink throughput than benchmarks for scheduling and resource allocation in MU-MIMO-OFDMA WLANs.

References

15 extracted · 15 resolved · 0 Pith anchors

[1] R. Zhang, K. Xiong, Y. Lu, B. Gao, P. Fan, and K. B. Letaief, ‘‘Joint coordinated beamforming and power splitting ratio optimization in mu-miso swipt-enabled hetnets: A multi- agent ddqn-based approac 2021

[2] A. Quadri and H. Li, ‘‘Resource allocation using deep learning in uplink 802.11 ax networks,’’ in GLOBECOM 2023-2023 IEEE Global Communications Conference. IEEE, 2023, pp. 4020–4025 2023

[3] R. Balakrishnan, K. Sankhe, V. S. Somayazulu, R. Van- nithamby, and J. Sydir, ‘‘Deep reinforcement learning based traﬀic-and channel-aware ofdma resource allocation,’’ in 2019 IEEE Global Communicatio 2019

[4] Y. S. Nasir and D. Guo, ‘‘Multi-agent deep reinforcement learning for dynamic power allocation in wireless networks,’’ IEEE Journal on Selected Areas in Communications, vol. 37, no. 10, pp. 2239–2250, 2019

[5] N. Naderializadeh, J. J. Sydir, M. Simsek, and H. Nikopour, ‘‘Resource management in wireless networks via multi-agent deep reinforcement learning,’’ IEEE Transactions on Wireless Communications, vol. 2021

Formal links

2 machine-checked theorem links

Receipt and verification

First computed	2026-05-20T00:01:54.893382Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

e76198876d156c7d31eea98c8cefee27f8478e039d09c0c5c699a6f4c9c4bc99

Aliases

arxiv: 2605.16144 · arxiv_version: 2605.16144v1 · doi: 10.48550/arxiv.2605.16144 · pith_short_12: 45QZRB3NCVWH · pith_short_16: 45QZRB3NCVWH2MPO · pith_short_8: 45QZRB3N

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/45QZRB3NCVWH2MPOVGGIZ37OE7 \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: e76198876d156c7d31eea98c8cefee27f8478e039d09c0c5c699a6f4c9c4bc99

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "f0bc79865cda9750960742c04a9605ca72bfc88bff54d69ebcf49fe180637151",
    "cross_cats_sorted": [
      "cs.MA",
      "cs.NI"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "eess.SP",
    "submitted_at": "2026-05-15T16:24:40Z",
    "title_canon_sha256": "dcdc387c02c1c7a2ed878443f4cddc4deda06617974a6a4e0fcd0adba2e1b7e0"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.16144",
    "kind": "arxiv",
    "version": 1
  }
}