<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>AI-Driven Fronthaul Link Compression in Wireless Communication Systems: Review and Method Design · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2509.04805/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:16:22 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/2509.04805/feed.xml" rel="self" type="application/rss+xml" /><item><title>AI-Driven Fronthaul Link Compression in Wireless Communication Systems: Review and Method Design — mentioned by quotemstr</title><link>https://news.ycombinator.com/item?id=45436689</link><guid isPermaLink="false">urn:hackerpapers:mention:2509.04805:45436689</guid><pubDate>Wed, 01 Oct 2025 12:00:56 GMT</pubDate><description>&lt;p&gt;I wonder whether there&amp;#x27;s a role for AI here. (Please don&amp;#x27;t hurt me.) AI turns out to be useful for data compression (https://statusneo.com/creating-lossless-compression-algorith...) and RF modulation optimization (https://www.arxiv.org/abs/2509.04805). Maybe it&amp;#x27;d be useful to train a small model (probably of the SSM variety) to find optimal chunking boundaries.&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2509.04805/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>eess.SP</category></item></channel></rss>
