51 citations · 52 across the 10 of their papers we have counts for
11 papers
Standard-Compliant Neuromorphic Integrated Sensing and Communications Aided by an Intelligent Reflecting Surface
Jiho Park, Jiechen Chen, Joonhyuk Kang +1
Neuromorphic computing enables event-driven, low-power inference and is therefore an attractive technology for jointly carrying out communication, sensing, and processing at resour…
Test-Time Scalable AI-RAN: Inference Time Allocation for Cell-Free MIMO
Seonghoon Yoo, Sangwoo Park, Seok-Hwan Park +1
Artificial intelligence-enabled radio access networks (AI-RANs) are envisioned to consist of multiple AI-based modules, potentially developed independently by different vendors. In…
Conformal Changepoint Localization and Root Cause Analysis with Corrupted Observations
Seunghun Yu, Meiyi Zhu, Petar Popovski +2
Detecting when the statistical behavior of an engineered system changes, and identifying which component is responsible, are core problems in the monitoring of telecommunication ne…
Robust Beamforming Design for Coherent Distributed ISAC with Statistical RCS and Phase Synchronization Uncertainty
Seonghoon Yoo, Seulhyun Kwon, Kawon Han +3
Distributed integrated sensing and communication (D-ISAC) enables multiple spatially distributed nodes to cooperatively perform sensing and communication. However, achieving cohere…
Reliable Wireless Indoor Localization via Cross-Validated Prediction-Powered Calibration
Seonghoon Yoo, Houssem Sifaou, Sangwoo Park +2
Wireless indoor localization using predictive models with received signal strength information (RSSI) requires proper calibration for reliable position estimates. One remedy is to…
Calibrating Wireless AI via Meta-Learned Context-Dependent Conformal Prediction
Seonghoon Yoo, Sangwoo Park, Petar Popovski +2
Modern software-defined networks, such as Open Radio Access Network (O-RAN) systems, rely on artificial intelligence (AI)-powered applications running on controllers interfaced wit…
Robust Bayesian Optimization via Localized Online Conformal Prediction
Dongwon Kim, Matteo Zecchin, Sangwoo Park +2
Bayesian optimization (BO) is a sequential approach for optimizing black-box objective functions using zeroth-order noisy observations. In BO, Gaussian processes (GPs) are employed…
Reliable Sub-Nyquist Spectrum Sensing via Conformal Risk Control
Hyojin Lee, Sangwoo Park, Osvaldo Simeone +2
Detecting occupied subbands is a key task for wireless applications such as unlicensed spectrum access. Recently, detection methods were proposed that extract per-subband features…
Cloud Radio Access Networks: Uplink Channel Estimation and Downlink Precoding
Osvaldo Simeone, Jinkyu Kang, Joonhyuk Kang +1
The gains afforded by cloud radio access network (C-RAN) in terms of savings in capital and operating expenses, flexibility, interference management and network densification rely…
Fronthaul Compression and Precoding Design for C-RANs over Ergodic Fading Channel
Jinkyu Kang, Osvaldo Simeone, Joonhyuk Kang +1
This work investigates the joint design of fronthaul compression and precoding for the downlink of Cloud Radio Access Networks (C-RANs). In a C-RAN, a central unit (CU) performs th…
Joint Signal and Channel State Information Compression for the Backhaul of Uplink Network MIMO Systems
Jinkyu Kang, Osvaldo Simeone, Joonhyuk Kang +1
In network MIMO cellular systems, subsets of base stations (BSs), or remote radio heads, are connected via backhaul links to central units (CUs) that perform joint encoding in the…