Pith Number

pith:D2KERVFX

pith:2026:D2KERVFX5EPO76UDIHYU2LDWEP

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Graph Signal Diffusion Models for Wireless Resource Allocation

Alejandro Ribeiro, Samar Hadou, Shirin Saeedi Bidokhti, Yigit Berkay Uslu

A diffusion model trained on expert allocations can sample near-optimal power controls for graph-structured wireless networks.

arxiv:2604.05175 v2 · 2026-04-06 · eess.SP · cs.IT · cs.LG · math.IT

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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

In a power-control case study, we show that time-sharing the generated power allocations achieves near-optimal ergodic sum-rate utility and near-feasible ergodic minimum-rates, with strong generalization and transferability across network states.

C2weakest assumption

That the primal-dual expert algorithm produces representative samples from the true conditional distributions over allocations and that time-sharing of diffusion samples is sufficient to achieve ergodic performance without violating constraints.

C3one line summary

A graph-conditioned diffusion model learns to sample near-optimal wireless resource allocations by matching distributions from an expert primal-dual algorithm.

Formal links

2 machine-checked theorem links

Cited by

3 papers in Pith

Generative Diffusion Models of Stochastic Graph Signals

Stability of Flow Models for Graph Signals

Graph Signal Diffusion Models for Wireless Resource Allocation

Receipt and verification

First computed	2026-07-30T00:08:14.041255Z
Builder	pith-number-builder-2026-05-17-v1
Signature	unsigned_v0
Schema	pith-number/v1.0

Canonical hash

1e9448d4b7e91eeffa8341f14d2c7623e57f4b3e86aff5f7a174781273d9631d

Aliases

arxiv: 2604.05175 · arxiv_version: 2604.05175v2 · doi: 10.48550/arxiv.2604.05175 · pith_short_12: D2KERVFX5EPO · pith_short_16: D2KERVFX5EPO76UD · pith_short_8: D2KERVFX

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/D2KERVFX5EPO76UDIHYU2LDWEP \
  | 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: 1e9448d4b7e91eeffa8341f14d2c7623e57f4b3e86aff5f7a174781273d9631d

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "9a1833ebad478d5cbc2de126f06fe0a330d3168cbf2ab42452aeef4af3243918",
    "cross_cats_sorted": [
      "cs.IT",
      "cs.LG",
      "math.IT"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "eess.SP",
    "submitted_at": "2026-04-06T21:12:25Z",
    "title_canon_sha256": "f7dc7b60f4c2791cb8bd74d41df134dc63a30eb74477e91fba56e90b6cd3c4bc"
  },
  "schema_version": "1.0",
  "source": {
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    "kind": "arxiv",
    "version": 2
  }
}