Research Areas
WIIL works across the full stack of communication and information systems — from information-theoretic foundations to machine-learning-driven wireless systems. Our thrusts are deeply interconnected: coding theory informs distributed computing, signal processing enables satellite links, and machine learning ties them together.
📶 Wireless Communications
6G, interference management, massive MIMO, beamforming, NOMA, limited-feedback systems, channel quantization, and device-to-device communication.
🛰️ LEO Satellite Communications
Beam-squint mitigation, tensor-based & decentralized channel estimation, and random-beam NOMA for massive-MIMO LEO satellite networks. (Joint flagship area of both PIs.)
🧮 Coding & Information Theory
Index coding, coded caching, coded/distributed computing, coded matrix computation, straggler mitigation, and numerically stable sparse computation via combinatorial designs (Steiner systems).
📊 Signal Processing & Machine Learning
ML-based beamforming and power allocation, ISAC (integrated sensing and communication), waveform design, LLM compression & mixed-precision quantization (MPQ), and RAG-based semantic error correction.
🔐 Physical-Layer Security & Covert Communications
Opportunistic jammer/relay selection, secrecy degrees of freedom, covert communication with active wardens, and full-duplex user relaying.
🔢 Discrete Mathematics & Abstract Algebra for Information Systems
Group algebra, graph theory, frame quantization, and combinatorial design (Steiner systems, resolvable designs, Latin squares) applied to communication and computing.
Where the Two Groups Meet
The PIs share a KAIST communication-theory lineage and co-author actively. Their overlap is strongest in LEO satellite communications (beam-squint mitigation, tensor channel estimation), index coding & coded transmission, and coded matrix computation for reliable edge AI — see the Publications page for joint works.