Pith Number

pith:TCUHRESB

pith:2026:TCUHRESBZIOO2GLWQZVLYF2XFP

not attested not anchored not stored refs resolved

Efficient Implementation of an Adaptive Transformer Accelerator for Massive MIMO Outdoor Localization

Ilayda Yaman, Liang Liu, Ove Edfors, Sijia Cheng

An FPGA accelerator for adaptive Transformer-based 5G massive MIMO localization skips low-energy beams row-wise to deliver roughly 2x speedup with under 10% accuracy loss.

arxiv:2605.13507 v1 · 2026-05-13 · cs.AR

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

Add to your LaTeX paper

\usepackage{pith}
\pithnumber{TCUHRESBZIOO2GLWQZVLYF2XFP}

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

The design achieves up to 65% row sparsity, yielding peak computational speedups of approximately 2x while limiting the average localization accuracy degradation to below 10%, relative to the floating-point baseline model. The accelerator attains below 1.15m localization accuracy across scenarios, with inference latency of 0.51-2.11ms and throughput of up to 1961 positions/s.

C2weakest assumption

That real-world beam-delay channel representations exhibit sufficient and stable sparsity to allow row-wise skipping with only minor accuracy impact, and that the single-layer perceptron router provides reliable, low-latency model selection without introducing instability across environments.

C3one line summary

An FPGA accelerator for a sparsity-exploiting adaptive Transformer achieves up to 2x speedup and sub-2ms latency for massive MIMO localization with under 10% accuracy loss on real measurements.

References

28 extracted · 28 resolved · 0 Pith anchors

[1] Service requirements for the 5G system, 2022

[2] Study on NR positioning enhancements, 2021

[3] Attention-Aided Outdoor Localization in Commercial 5G NR Sys- tems, 2024

[4] Adaptive Attention-Based Model for 5G Radio-Based Outdoor Localization, 2025

[5] A survey on 5G massive MIMO localization, 2019

Receipt and verification

First computed	2026-05-18T02:44:24.621868Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

98a8789241ca1ced1976866abc17572be08ac749e492cb772ecdeaaa68bd40ca

Aliases

arxiv: 2605.13507 · arxiv_version: 2605.13507v1 · doi: 10.48550/arxiv.2605.13507 · pith_short_12: TCUHRESBZIOO · pith_short_16: TCUHRESBZIOO2GLW · pith_short_8: TCUHRESB

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/TCUHRESBZIOO2GLWQZVLYF2XFP \
  | 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: 98a8789241ca1ced1976866abc17572be08ac749e492cb772ecdeaaa68bd40ca

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "4f17152d09bf83d76740f9cf5fa9c1ede398e521daa01e1a28ce65d79ada8d7b",
    "cross_cats_sorted": [],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.AR",
    "submitted_at": "2026-05-13T13:27:33Z",
    "title_canon_sha256": "76fbe20fb5b0389bb0825b22971c73b09233518d409fcd0cd063ea2490d311c1"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.13507",
    "kind": "arxiv",
    "version": 1
  }
}