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ARXIV:2605.31279 · WIRELESS AI · SUBMITTED 01 JUN · 20:26 UTC · FRESHNESS STALE
ARXIV:2605.31279WIRELESS AISUBMITTED 01 JUN · 20:26 UTCFRESHNESS STALERuiqi Kong · He Chen · Xiaojun Lin · arXiv
GUIDE is a physics-guided deep unfolding framework for practical cross-band channel prediction in AI-RAN, achieving significant beamforming gains with faster inference.
Opportunity summary
Pain GUIDE is a physics-guided deep unfolding framework for practical cross-band channel prediction in AI-RAN, achieving significant beamforming gains with faster inference.
Evidence 0 refs | 3 sources | 50% coverage
Blocker Evidence unverified
GUIDE is a physics-guided deep unfolding framework for practical cross-band channel prediction in AI-RAN, achieving significant beamforming gains with faster inference. Existing approaches achieve one but not both.
To make cross-band channel prediction practical for AI-native RAN, algorithms must generalize across diverse environments and support real-time inference. Existing approaches achieve one but not both.
ScienceToStartup currently rates this 4.0/10 on the public viability pass. To make cross-band channel prediction practical for AI-native RAN, algorithms must generalize across diverse environments and support real-time inference.
Wireless AI moved forward this cycle; last verified June 2026. Public score 4.0/10.
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mobile layout uses overflow-hidden min-w-0 break-wordsOpportunity summary
Score4.0Public score shown from the verified overall while the stale axis breakdown refreshesAnalysis summary
GUIDE is a physics-guided deep unfolding framework for practical cross-band channel prediction in AI-RAN, achieving significant beamforming gains with faster inference.
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Paper Pack
10.48550/arXiv.2605.31279GUIDE is a physics-guided deep unfolding framework for practical cross-band channel prediction in AI-RAN, achieving significant beamforming gains with faster inference.
Abstract
To make cross-band channel prediction practical for AI-native RAN, algorithms must generalize across diverse environments and support real-time inference. Existing approaches achieve one but not both. To bridge this gap, we introduce GUIDE, a physics-guided deep unfolding framework that embeds wireless channel physics into differentiable layers. Without retraining in unseen environments, GUIDE achieves 2.75x beamforming gain than the deep learning-based baseline FIRE with only a slight increase in inference time, and 1.39x beamforming gain than the strongest model-based baseline R2F2 while running over 1610x faster.
Source availability
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Extraction status
Parse run pending anchorsA parse run id is attached, but no public source anchors are materialized yet.
Proof status
unverified0 refs; 3 sources; 50% coverage.
What was readable
Derived fallback: Estimated from adjacent evidence; not verified from source.
Viability
Time to MVP
Commercial
Export
Preparing verified analysis
Dimensions overall score 4.0
PROBLEM
GUIDE is a physics-guided deep unfolding framework for practical cross-band channel prediction in AI-RAN, achieving significant beamforming gains with faster inference. Existing approaches achieve one but not both.
METHOD
To make cross-band channel prediction practical for AI-native RAN, algorithms must generalize across diverse environments and support real-time inference. Existing approaches achieve one but not both.
RESULT
ScienceToStartup currently rates this 4.0/10 on the public viability pass. To make cross-band channel prediction practical for AI-native RAN, algorithms must generalize across diverse environments and support real-time inference.
WHY NOW
Wireless AI moved forward this cycle; last verified June 2026. Public score 4.0/10.
{"file name": "input.pdf", "number of pages": 2, "author": "Ruiqi Kong; He Chen; Xiaojun Lin", "title": "Practical Cross-Band Channel Prediction for AI-RAN via Physics-Guided Deep Unfolding"
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Concepts
Methods
Materials
Markets
Competitors
GUIDE is a physics-guided deep unfolding framework for practical cross-band channel prediction in AI-RAN, achieving significant beamforming gains with faster inference.
Segment
Wireless AI
Adoption evidence
No public code link in the paper record yet
Commercial read
4.0/10 public viability
Direct
Adjacent
Substitute
Unknown
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CITED BY
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Foundation
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Commercially relevant
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2/3 checks · 67%
Build Passport
Build passport pending - Proof Lab budget No verified cost estimate / $7.00 cap
status
missing
reason
passport_row_missing
proof status
unverified
cost/budget
No verified cost estimate
confidence low
next verification path
Build brief missing until Build Passport data exists.
Source missing: Build Passport payload.
Experiment plan missing until prototype path is available.
No prototype path attached.
Validation checklist missing until required assets, cost, and regulatory flags are verified.
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Evidence coverage
OpportunityKernel evidence_receipt
0 refs / 3 sources / 50% coverage
stale
Verify missing sources before using this as buyer proof. verified:false
Build readiness
BuildPassport EvidenceState
passport absent
stale
Run Proof Lab or inspect typed missing state. verified:false
Artifact maturity
GitHub and Hugging Face maturity payloads
No public artifact surface observed
stale
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Technical feasibility
partial
Current read
Runnable path is not fully verified.
Evidence
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Gaps
Next test
Run minimal reproduction from the Build Passport prototype path.
Market urgency
missing
Current read
Buyer urgency is not verified from source.
Evidence
0 references, 3 sources, 50% evidence coverage.
Gaps
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Collect buyer interview, deployment evidence, or cited demand signal.
Buyer clarity
missing
Current read
No budget owner is verified for this paper.
Evidence
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Defensibility
missing
Current read
Defensibility signals are missing.
Evidence
No defensibility receipt attached.
Gaps
Next test
Refresh defensibility bars with source receipts.
Integration burden
missing
Current read
No public implementation surface observed.
Evidence
No GitHub or Hugging Face payload attached.
Gaps
Next test
Write integration checklist from prototype path and target workflow.
Capital intensity
missing
Current read
No observed cost estimate is verified.
Evidence
Cost passport has no observed_usd value.
Gaps
Next test
Run cost passport or mark the cost field not applicable.
Regulatory load
missing
Current read
No regulatory classification is attached.
Evidence
Build Passport ledger does not include regulatory flags.
Gaps
Next test
Classify regulatory flags before commercialization planning.
No named scientific founder assigned.
Paper authors are not treated as operators without consent.
People
No named person assigned.
Gaps
Next verification path
Prototype owner missing.
Build Passport does not name an implementer.
People
No named person assigned.
Gaps
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Operator workflow not sourced.
No buyer or workflow interview attached.
People
No named person assigned.
Gaps
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No CRM or outreach source attached.
People
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Gaps
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Regulatory need unclassified.
No clinical or regulatory source attached.
People
No named person assigned.
Gaps
Next verification path
ARTIFACTS
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DEFENSIBILITY
Defensibility and confidence evidence pending.
WATCHTOWER
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FORESIGHT
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OPPORTUNITYKERNEL CHANGES SINCE LAST VIEW
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RELATED PAPER UPDATES
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TIMELINE
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BUZZ
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