Pith Number

pith:FKPWZCKE

pith:2026:FKPWZCKES7TJXTV2SFZMXWESLK

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Map2APS: A Physically Grounded Benchmark for Direct Angle Power Spectrum Prediction from Urban Geometry

Junxi Huang, Kailong Wang, Nan Cheng, Ruijin Sun, Xiucheng Wang, Zhisheng Yin

Map2APS benchmark enables direct prediction of angle power spectra from urban maps with 0.948 cosine similarity on unseen layouts.

arxiv:2605.14989 v1 · 2026-05-14 · eess.SP

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\pithnumber{FKPWZCKES7TJXTV2SFZMXWESLK}

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4 Citations open

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✓ 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

On the full held-out test set of 249,993 samples, MS-AReg achieves a cosine similarity of 0.948, a peak location error of 1.20°, and an inference latency of 0.101 ms/sample.

C2weakest assumption

That intelligent ray-tracing simulations provide sufficiently accurate ground truth for real-world angle power spectra and that the 51 equal-height urban maps with cross-map splits adequately represent generalization to unseen city layouts.

C3one line summary

Map2APS is a new large-scale benchmark with 2.55 million samples from 51 urban maps for predicting angle power spectra from geometry, featuring a cross-map split and MS-AReg baseline with 0.948 cosine similarity.

References

13 extracted · 13 resolved · 1 Pith anchors

[1] Millimeter wave mobile communications for 5g cellular: It will work! 2013 · doi:10.1109/access.2013.2260813

[2] An overview of signal processing techniques for millimeter wave MIMO systems, 2016

[3] TR 38.901: Study on channel model for frequencies from 0.5 to 100 ghz, 2022

[4] DeepMIMO: A generic deep learning dataset for millimeter wave and massive MIMO applications, 2019

[5] Radiounet: Fast radio map estimation with convolutional neural networks, 2021 · doi:10.1109/twc.2021.3054977

Receipt and verification

First computed	2026-05-17T23:38:55.035977Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

2a9f6c894497e69bceba9172cbd8925a9de768ce2af25b629a3a6635f6da0516

Aliases

arxiv: 2605.14989 · arxiv_version: 2605.14989v1 · doi: 10.48550/arxiv.2605.14989 · pith_short_12: FKPWZCKES7TJ · pith_short_16: FKPWZCKES7TJXTV2 · pith_short_8: FKPWZCKE

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/FKPWZCKES7TJXTV2SFZMXWESLK \
  | 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: 2a9f6c894497e69bceba9172cbd8925a9de768ce2af25b629a3a6635f6da0516

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "d45a7afbdf35e7d309fed597950f424214b02f3ae8b2f55c97f93d03caf7666a",
    "cross_cats_sorted": [],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "eess.SP",
    "submitted_at": "2026-05-14T15:52:20Z",
    "title_canon_sha256": "015378a738657e760f7007f8d80e5ee5c0dddaabc01604085e896fab9410eaa4"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.14989",
    "kind": "arxiv",
    "version": 1
  }
}