12 papers
Fundamental Limits of MIMO-OTFS and MIMO-OFDM in High-Dynamics ISAC: An Antenna Array Architecture Perspective
Po-Chih Chen, Ming-Chun Lee, Yu-Chih Huang
This paper investigates the fundamental limits of MIMO-OTFS and MIMO-OFDM integrated sensing and communications (ISAC) systems in high-mobility environments, specifically comparing…
Design of APSK Constellations Approaching the Communication-Sensing Pareto Boundary for ISAC
Yujie Shao, Min Qiu, Ming-Chun Lee +2
We propose a semi-analytical design framework for amplitude phase shift keying (APSK) signaling for integrated sensing and communication (ISAC), focusing on i.i.d. uniform discrete…
Pairing Regularization for Mitigating Many-to-One Collapse in GANs
Kuan-Yu Lin, Yu-Chih Huang, Tie Liu
Mode collapse remains a fundamental challenge in training generative adversarial networks (GANs). While existing works have primarily focused on inter-mode collapse, such as mode d…
A Modularized Framework for Piecewise-Stationary Restless Bandits
Kuan-Ta Li, Chia-Chun Lin, Ping-Chun Hsieh +1
We study the piecewise-stationary restless multi-armed bandit (PS-RMAB) problem, where each arm evolves as a Markov chain but \emph{mean rewards may change across unknown segments}…
Finite-Blocklength Analysis of Alamouti Codes over Eisenstein Integers
Juliana Souza, Yu-Chih Huang
We study a space--time block code from a maximal order in the definite quaternion algebra $(-1,-3)_{\Q}$. Its embedding into $\C^{2\times 2}$ yields an Alamouti--Eisenstein code ov…
On optimal solutions of classical and sliced Wasserstein GANs with non-Gaussian data
Yu-Jui Huang, Hsin-Hua Shen, Yu-Chih Huang +2
The generative adversarial network (GAN) aims to approximate an unknown distribution via a parameterized neural network (NN). While GANs have been widely applied in reinforcement a…