BeamAgent: LLM-Aided MIMO Beamforming with Decoupled Intent Parsing and Alternating Optimization for Joint Site Selection and Precoding | ScienceToStartup | ScienceToStartup

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References (40)

[1]

Wireless Power Control Based on Large Language Models

2026Jiacheng Wang, Yucheng Sheng et al.

[2]

WirelessAgent++: Automated Agentic Workflow Design and Benchmarking for Wireless Networks

2026Jingwen Tong, Zijian Li et al.

[3]

Bridging 6G IoT and AI: LLM-Based Efficient Approach for Physical Layer's Optimization Tasks

Founder's Pitch

"An LLM-aided framework that translates natural language into structured spatial constraints for wireless communication optimization, achieving significant performance gains."

Wireless Communication Optimization•Score: 5•View PDF ↗

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BeamAgent: LLM-Aided MIMO Beamforming with Decoupled Intent Parsing and Alternating Optimization for Joint Site Selection and Precoding

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References (40)

Founder's Pitch

"An LLM-aided framework that translates natural language into structured spatial constraints for wireless communication optimization, achieving significant performance gains."

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BeamAgent: LLM-Aided MIMO Beamforming with Decoupled Intent Parsing and Alternating Optimization for Joint Site Selection and Precoding

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References (40)

Founder's Pitch

"An LLM-aided framework that translates natural language into structured spatial constraints for wireless communication optimization, achieving significant performance gains."

Commercial Viability Breakdown

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