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Paul Rigge

Researcher at University of California, Berkeley

Publications -  17
Citations -  389

Paul Rigge is an academic researcher from University of California, Berkeley. The author has contributed to research in topics: Wireless & Communication channel. The author has an hindex of 7, co-authored 17 publications receiving 256 citations.

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Journal ArticleDOI

Chipyard: Integrated Design, Simulation, and Implementation Framework for Custom SoCs

TL;DR: The Chipyard framework is presented, an integrated SoC design, simulation, and implementation environment for specialized compute systems, that includes configurable, composable, open-source, generator-based IP blocks that can be used across multiple stages of the hardware development flow while maintaining design intent and integration consistency.
Proceedings ArticleDOI

Cooperative communication for high-reliability low-latency wireless control

TL;DR: A novel “diversity meter” designed to measure “effective diversity” in the non-asymptotic regime is developed and can robustly achieve a system probability of error better than 10-9 with nominal SNR below 5 dB.
Journal ArticleDOI

Real-Time Cooperative Communication for Automation Over Wireless

TL;DR: In this article, a wireless communication protocol that capitalizes on multiuser diversity and cooperative communication to achieve the ultra-reliability with a low-latency constraint is proposed.
Posted Content

Real-time Cooperative Communication for Automation over Wireless

TL;DR: A wireless communication protocol that capitalizes on multiuser diversity and cooperative communication to achieve the ultra-reliability with a low-latency constraint is introduced.
Journal ArticleDOI

Wireless Channel Dynamics and Robustness for Ultra-Reliable Low-Latency Communications

TL;DR: A modeling approach from robust control to wireless communication is brought—the wireless channel characteristics are given a nominal model around which to allow for some quantified uncertainty, and certain key URLLC-relevant parameters are proposed along which the model uncertainty is to be bounded.