Energy Saving for Cell-Free Massive MIMO Networks: A Multi-Agent Deep Reinforcement Learning Approach

Energy Saving for Cell-Free Massive MIMO Networks: A Multi-Agent Deep Reinforcement Learning Approach | Signal Canvas | ScienceToStartup

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Canonical route: /signal-canvas/energy-saving-for-cell-free-massive-mimo-networks-a-multi-agent-deep-reinforcement-learning-approach

stale

Proof freshness: stale
Proof status: unverified
Display score: 4/10
Last proof check: 2026-04-10
Score updated: 2026-04-09
Score fresh until: 2026-05-09
References: 17
Source count: 3
Coverage: 67%

This page is showing the last landed evidence receipt and score bundle because the latest proof data is outside the freshness window.

Agent Handoff

Canonical ID energy-saving-for-cell-free-massive-mimo-networks-a-multi-agent-deep-reinforcement-learning-approach | Route /signal-canvas/energy-saving-for-cell-free-massive-mimo-networks-a-multi-agent-deep-reinforcement-learning-approach

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curl https://sciencetostartup.com/api/v1/agent-handoff/signal-canvas/energy-saving-for-cell-free-massive-mimo-networks-a-multi-agent-deep-reinforcement-learning-approach

MCP example

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source_context

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Evidence Receipt

Route status: building

Claims: 0

References: 17

Proof: Verification pending

Freshness state: computing

Source paper: Energy Saving for Cell-Free Massive MIMO Networks: A Multi-Agent Deep Reinforcement Learning Approach

PDF: https://arxiv.org/pdf/2604.07133v1

Source count: 3

Coverage: 67%

Last proof check: 2026-04-10T00:15:48.850Z

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Not build-ready: Energy Saving for Cell-Free Massive MIMO Networks: A Multi-Agent Deep Reinforcement Learning Approach

/buildability/energy-saving-for-cell-free-massive-mimo-networks-a-multi-agent-deep-reinforcement-learning-approach

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Subject: Energy Saving for Cell-Free Massive MIMO Networks: A Multi-Agent Deep Reinforcement Learning Approach

Verdict

Ignore

Verdict is Ignore because current viability and proof state do not clear the buildability gate.

Energy Saving for Cell-Free Massive MIMO Networks: A Multi-Agent Deep Reinforcement Learning Approach

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