5G K-SimSys: Open/Modular/Flexible System Level Simulator for 5G System. - Minsig Han; Jae Won Lee; Chung Gu Kang 001; Minjoong Rim (DySPAN, 2018)

System-level Performance Evaluation with 5G K-SimSys for 5G URLLC System. - Minsig Han; Jae Won Lee; Chung Gu Kang 001; Minjoong Rim (CCNC, 2019)

5G K-SimSys for System-level Evaluation of Massive MIMO. - Jae Won Lee; Minsig Han; Chung Gu Kang 001; Minjoong Rim (CCNC, 2019)

Deep Learning-Based Multi-User Multi-Dimensional Constellation Design in Code Domain Non-Orthogonal Multiple Access. - Minsig Han; Hanchang Seo; Ameha T. Abebe; Chung Gu Kang 001 (ICC Workshops, 2020)

5G K-SimSys for Open/Modular/Flexible System-Level Simulation: Overview and its Application to Evaluation of 5G Massive MIMO. - Jae Won Lee; Minsig Han; Minjoong Rim; Chung Gu Kang 001 (IEEE Access, 2021)

Deep Learning-based Codebook Design for Code-domain Non-Orthogonal Multiple Access Achieving a Single-User Bit Error Rate Performance. - Minsig Han; Hanchang Seo; Ameha Tsegaye Abebe; Chung Gu Kang 001 (CoRR, 2021)

Dynamic Bandwidth Part Allocation in 5G Ultra Reliable Low Latency Communication for Unmanned Aerial Vehicles with High Data Rate Traffic. - Minsig Han; Jae Won Lee; Minjoong Rim; Chung Gu Kang 001 (Sensors, 2021)

On the Performance of Deep Learning-based Data-aided Active User Detection for GF-SCMA System. - Minsig Han; Ameha T. Abebe; Chung Gu Kang 001 (APCC, 2022)

Data-aided Active User Detection with a User Activity Extraction Network for Grant-free SCMA Systems. - Minsig Han; Ameha T. Abebe; Chung Gu Kang 001 (GLOBECOM (Workshops), 2022)

Deep Learning-Based Codebook Design for Code-Domain Non-Orthogonal Multiple Access: Approaching Single-User Bit-Error Rate Performance. - Minsig Han; Hanchang Seo; Ameha Tsegaye Abebe; Chung Gu Kang 001 (IEEE Trans. Cogn. Commun. Netw., 2022)

Deep learning-based Collision-aware Multi-user Detection for Grant-free Sparse Code Multiple Access Systems. - Minsig Han; Metasebia G. Demissu; Ameha T. Abebe; Chung G. Kang 001 (APCC, 2023)

Deep Learning-based Data-aided Activity Detection with Extraction Network in Grant-free Sparse Code Multiple Access Systems. - Minsig Han; Ameha T. Abebe; Chung Gu Kang 001 (CoRR, 2023)

Generalization Performance of Deep Learning-based Multi-User Detection for GF-SCMA Systems. - Metasebia D. Gemeda; Minsig Han; Ameha T. Abebe; Chung G. Kang 001 (APCC, 2024)

Design of Deep Learning-Based 1-bit Transceiver With Oversampling and Faster-Than-Nyquist (FTN) Signaling. - Metasebia D. Gemeda; Minsig Han; Ameha Tsegaye Abebe; Chung Gu Kang 001 (IEEE Access, 2024)

Deep Learning-Based Data-Aided Activity Detection with Extraction Network for Grant-Free Sparse Code Multiple Access. - Minsig Han; Metasebia D. Gemeda; Ameha T. Abebe; Chung G. Kang 001 (WCNC, 2025)

Deep Learning-Based Collision-Aware Multi-User Detection for Channel-Modulated Codebooks in Grant-Free Sparse Code Multiple Access Systems. - Minsig Han; Metasebia D. Gemeda; Ameha T. Abebe; Chung Gu Kang 001 (IEEE Trans. Cogn. Commun. Netw., 2025)