1 citations · 2 across the 4 of their papers we have counts for
6 papers
UL-Assisted Parametric CSI Feedback and Prediction for FDD Systems
Hao Chang, Mingcheng Nie, Shuangyang Li +4
In frequency-division duplex (FDD) systems, the uplink (UL) and downlink (DL) channels are not fully reciprocal. Therefore, DL channel state information (CSI) estimated by each use…
Channel Estimation for OFDM via Delay-Doppler Refinement
Mingcheng Nie, Hao Chang, Xiaoqi Zhang +4
In this paper, we propose a novel channel estimation (CE) algorithm for orthogonal frequency division multiplexing (OFDM) systems that exploits the unique characteristics of the de…
Neural Network-Based Delay-Doppler-Assisted Channel Estimation for OFDM
Mingcheng Nie, Hao Chang, Shuangyang Li +3
Conventional orthogonal frequency division multiplexing (OFDM) channel estimation relies on single-tap estimation and time-frequency (TF) interpolation, which becomes unreliable in…
Short Wins Long: Short Codes with Language Model Semantic Correction Outperform Long Codes
Jiafu Hao, Chentao Yue, Hao Chang +2
This paper presents a novel semantic-enhanced decoding scheme for transmitting natural language sentences with multiple short block codes over noisy wireless channels. After ASCII…
Graph Neural Network-based End-to-End Learning for Multi-User MIMO Systems
Hao Chang, Hoang Triet Vo, Alva Kosasih +2
End-to-end (E2E) learning has recently been proposed to jointly design the modulator and symbol detector by using deep neural networks (DNNs). However, existing schemes lack suffic…
Graph-based Untrained Neural Network Detector for OTFS Systems
Hao Chang, Branka Vucetic, Wibowo Hardjawana
Inter-carrier interference (ICI) caused by mobile reflectors significantly degrades the conventional orthogonal frequency division multiplexing (OFDM) performance in high-mobility…