Pith Number

pith:Q3FO5VHK

pith:2026:Q3FO5VHKA5MW7EPYP3SLUZOM3Z

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Analog RF Computing: A New Paradigm for Energy-Efficient Edge AI Over MU-MIMO Systems

Vincent W.S. Wong, Wentao Yu

In MU-MIMO systems a base station broadcasts weight-encoded RF waveforms so clients perform neural-network matrix-vector multiplications with passive mixers, cutting client energy use by nearly two orders of magnitude.

arxiv:2605.14331 v1 · 2026-05-14 · eess.SP · cs.AI · cs.ET · cs.IT · cs.LG · math.IT

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4 Citations open

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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

Simulations under 3GPP specifications show that analog RF computing can significantly reduce client-side energy consumption by nearly two orders of magnitude compared to digital computing, while mixed-precision inference requires even lower energy consumption than uniform-precision inference.

C2weakest assumption

The derived tractable models for analog MVM accuracy and energy consumption accurately represent real-world passive mixer behavior, wireless channel effects, and hardware impairments without significant unmodeled errors.

C3one line summary

Analog RF computing performs neural network matrix-vector multiplications via RF waveform mixing at clients in MU-MIMO systems, reducing energy consumption by nearly two orders of magnitude compared to digital computing.

References

34 extracted · 34 resolved · 0 Pith anchors

[1] Edge artificial intelligence for 6G: Vision, enabling technologies, and applications, 2022

[2] Computing’s energy problem (and what we can do about it), 2014

[3] Deep reinforcement learning for task offloading in mobile edge computing systems, 1985

[4] Joint optimal pricing and task scheduling in mobile cloud computing systems, 2017

[5] Razavi,RF Microelectronics, 2nd ed 2011

Receipt and verification

First computed	2026-05-17T23:39:08.292647Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

86caeed4ea07596f91f87ee4ba65ccde79b98f3ba5232d646f09da5eec2d8975

Aliases

arxiv: 2605.14331 · arxiv_version: 2605.14331v1 · doi: 10.48550/arxiv.2605.14331 · pith_short_12: Q3FO5VHKA5MW · pith_short_16: Q3FO5VHKA5MW7EPY · pith_short_8: Q3FO5VHK

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/Q3FO5VHKA5MW7EPYP3SLUZOM3Z \
  | 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: 86caeed4ea07596f91f87ee4ba65ccde79b98f3ba5232d646f09da5eec2d8975

Canonical record JSON

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    "abstract_canon_sha256": "bf16141a959fde6ed06501378365bb4ed89d738e487ff231abd51ac7847775b3",
    "cross_cats_sorted": [
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    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "eess.SP",
    "submitted_at": "2026-05-14T03:50:27Z",
    "title_canon_sha256": "1d15ceca4d66afd4601a8dc0b25d545a946507e0b7cf1bd2038fa161ca44c7d1"
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