<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Open RAN |</title><link>https://doost.rice.edu/tags/open-ran/</link><atom:link href="https://doost.rice.edu/tags/open-ran/index.xml" rel="self" type="application/rss+xml"/><description>Open RAN</description><generator>HugoBlox Kit (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Tue, 04 Nov 2025 00:00:00 +0000</lastBuildDate><image><url>https://doost.rice.edu/media/icon_hu_702a800cd775dbac.png</url><title>Open RAN</title><link>https://doost.rice.edu/tags/open-ran/</link></image><item><title>ETHOS: Demystifying Performance, Energy, and Computational Efficiency in Virtualized 5G O-RAN Networks</title><link>https://doost.rice.edu/publications/wu2025ethos/</link><pubDate>Tue, 04 Nov 2025 00:00:00 +0000</pubDate><guid>https://doost.rice.edu/publications/wu2025ethos/</guid><description/></item><item><title>Helix: A RAN Slicing Based Scheduling Framework for Massive MIMO Networks</title><link>https://doost.rice.edu/publications/an2024helix/</link><pubDate>Mon, 25 Nov 2024 00:00:00 +0000</pubDate><guid>https://doost.rice.edu/publications/an2024helix/</guid><description/></item><item><title>ETHOS project launches with NTIA Public Wireless Supply Chain Innovation Fund award</title><link>https://doost.rice.edu/blog/2024-ethos-launch/</link><pubDate>Mon, 15 Jan 2024 00:00:00 +0000</pubDate><guid>https://doost.rice.edu/blog/2024-ethos-launch/</guid><description>&lt;p&gt;We are excited to launch
— &lt;em&gt;A
Multi-dimensional Approach to ML-Enabled RAN Software Testing&lt;/em&gt; — a new
5-year project funded by the NTIA Public Wireless Supply Chain
Innovation Fund. ETHOS will build a comprehensive testing framework for
machine-learning components in Open RAN software, helping to accelerate
the deployment of trustworthy, interoperable 5G/6G networks.&lt;/p&gt;</description></item><item><title>ETHOS</title><link>https://doost.rice.edu/projects/ethos/</link><pubDate>Mon, 01 Jan 2024 00:00:00 +0000</pubDate><guid>https://doost.rice.edu/projects/ethos/</guid><description>&lt;p&gt;&lt;strong&gt;ETHOS&lt;/strong&gt; develops a comprehensive, multi-dimensional testing framework
for machine-learning components in Open RAN software, with the goal of
accelerating the deployment of trustworthy, interoperable 5G/6G
networks. Funded by the NTIA Public Wireless Supply Chain Innovation
Fund, January 2024 – December 2028.&lt;/p&gt;</description></item></channel></rss>