<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>S. Chen | NIULAB</title><link>https://souig.github.io/authors/s.-chen/</link><atom:link href="https://souig.github.io/authors/s.-chen/index.xml" rel="self" type="application/rss+xml"/><description>S. Chen</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en</language><lastBuildDate>Thu, 01 Aug 2024 00:00:00 +0000</lastBuildDate><image><url>https://souig.github.io/media/icon_hu_7d2a9e6dbe042ff1.png</url><title>S. Chen</title><link>https://souig.github.io/authors/s.-chen/</link></image><item><title>Learning-Assisted User Scheduling and Beamforming for mmWave Vehicular Networks</title><link>https://souig.github.io/publication/learning-assisted-019/</link><pubDate>Thu, 01 Aug 2024 00:00:00 +0000</pubDate><guid>https://souig.github.io/publication/learning-assisted-019/</guid><description/></item><item><title>, Learning-Based Remote Channel Inference: Feasibility Analysisand Case Study</title><link>https://souig.github.io/publication/learning-based-068/</link><pubDate>Mon, 01 Jan 2024 00:00:00 +0000</pubDate><guid>https://souig.github.io/publication/learning-based-068/</guid><description/></item><item><title>Channel Fingerprint Based Beam Tracking for Millimeter Wave Communications</title><link>https://souig.github.io/publication/channel-fingerprint-061/</link><pubDate>Mon, 01 Jan 2024 00:00:00 +0000</pubDate><guid>https://souig.github.io/publication/channel-fingerprint-061/</guid><description/></item><item><title>Exploitingwirelesschannel stateinformationstructuresbeyondlinearcorrelations: Adeeplearningapproach</title><link>https://souig.github.io/publication/exploitingwirelesschannel-stateinformationstructuresbeyondlinearcorrelations-077/</link><pubDate>Mon, 01 Jan 2024 00:00:00 +0000</pubDate><guid>https://souig.github.io/publication/exploitingwirelesschannel-stateinformationstructuresbeyondlinearcorrelations-077/</guid><description/></item><item><title>Jointuserschedulingandbeamselectionoptimizationforbeam- basedmassiveMIMOdownlinks</title><link>https://souig.github.io/publication/jointuserschedulingandbeamselectionoptimizationforbeam-basedmassivemimodownlinks-086/</link><pubDate>Mon, 01 Jan 2024 00:00:00 +0000</pubDate><guid>https://souig.github.io/publication/jointuserschedulingandbeamselectionoptimizationforbeam-basedmassivemimodownlinks-086/</guid><description/></item><item><title>ADeep Reinforcement Learning Frame- workto Combat Dynamic Blockageinmm WaveV2XNetworks</title><link>https://souig.github.io/publication/adeep-reinforcement-181/</link><pubDate>Wed, 01 Jan 2020 00:00:00 +0000</pubDate><guid>https://souig.github.io/publication/adeep-reinforcement-181/</guid><description/></item><item><title>Inferring Remote Channel State Infor- mation: Cramer-Rao Lower Boundand Deep Learning Implementation</title><link>https://souig.github.io/publication/inferring-remote-198/</link><pubDate>Mon, 01 Jan 2018 00:00:00 +0000</pubDate><guid>https://souig.github.io/publication/inferring-remote-198/</guid><description/></item><item><title>Time-sequence channel inference for beam alignment in vehicularnetworks</title><link>https://souig.github.io/publication/time-sequence-200/</link><pubDate>Mon, 01 Jan 2018 00:00:00 +0000</pubDate><guid>https://souig.github.io/publication/time-sequence-200/</guid><description/></item></channel></rss>