Nhan Thanh Nguyen — accepted AI-conference papers

2025

Low-Complexity Cramér-Rao Lower Bound and Sum Rate Optimization in ISAC Systems

Tianyu Fang, Nhan Thanh Nguyen, Markku J. Juntti

ICASSP 2025accepted

While Cramér-Rao lower bound is an important metric in sensing functions in integrated sensing and communications (ISAC) designs, its optimization usually involves a computationally expensive solution such as semidefinite relaxation. In this paper, we aim to develop a low-complexity yet efficient al…

Cited by 12 Source ↗Scholar ↗

2023

Deep Unfolding-Enabled Hybrid Beamforming Design for mmWave Massive MIMO Systems

Nhan Thanh Nguyen, Mengyuan Ma, Nir Shlezinger, Yonina C. Eldar, A. Lee Swindlehurst, Markku J. Juntti

ICASSP 2023accepted

Hybrid beamforming (HBF) is a key enabler for millimeter-wave (mmWave) communications systems, but HBF optimizations are often non-convex and of large dimension. In this paper, we propose an efficient deep unfolding-based HBF scheme, referred to as ManNet-HBF, that approximately maximizes the system…

Cited by 0 Source ↗Scholar ↗