2 citations · 4 across the 8 of their papers we have counts for
9 papers
Soft Graph Diffusion Transformer for MIMO Detection
Nan Jiang, Jiadong Hong, Lei Liu +3
Learning-based MIMO detection has shown strong empirical performance, yet existing methods typically rely on fixed-depth architectures without explicitly modeling the progressive r…
Prediction--Loss Alignment for Sampler--Robust Flow Matching Training
Jiadong Hong, Lei Liu, Xinyu Bian +2
Recent work has popularized a practical recipe in diffusion and flow matching: predict the clean signal , convert it to a velocity, and train through a velocity-space loss. The…
Soft Graph Transformer for MIMO Detection
Jiadong Hong, Lei Liu, Xinyu Bian +2
We propose the Soft Graph Transformer (SGT), a soft-input-soft-output neural architecture designed for MIMO detection. While Maximum Likelihood (ML) detection achieves optimal accu…
Decentralizing Coherent Joint Transmission Precoding via Fast ADMM with Deterministic Equivalents
Xinyu Bian, Yuhao Liu, Yizhou Xu +4
Inter-cell interference (ICI) suppression is critical for multi-cell multi-user networks. In this paper, we investigate advanced precoding techniques for coordinated multi-point (C…
Decentralizing Coherent Joint Transmission Precoding via Deterministic Equivalents
Yuhao Liu, Xinyu Bian, Yizhou Xu +4
In order to control the inter-cell interference for a multi-cell multi-user multiple-input multiple-output network, we consider the precoder design for coordinated multi-point with…
Joint Activity-Delay Detection and Channel Estimation for Asynchronous Massive Random Access: A Free Probability Theory Approach
Xinyu Bian, Yuyi Mao, Jun Zhang
Grant-free random access (RA) has been recognized as a promising solution to support massive connectivity due to the removal of the uplink grant request procedures. While most ende…
Joint Activity Detection, Channel Estimation, and Data Decoding for Grant-free Massive Random Access
Xinyu Bian, Yuyi Mao, Jun Zhang
In the massive machine-type communication (mMTC) scenario, a large number of devices with sporadic traffic need to access the network on limited radio resources. While grant-free r…
Joint Activity Detection and Data Decoding in Massive Random Access via a Turbo Receiver
Xinyu Bian, Yuyi Mao, Jun Zhang
In this paper, we propose a turbo receiver for joint activity detection and data decoding in grant-free massive random access, which iterates between a detector and a belief propag…
Supporting More Active Users for Massive Access via Data-assisted Activity Detection
Xinyu Bian, Yuyi Mao, Jun Zhang
Massive machine-type communication (mMTC) has been regarded as one of the most important use scenarios in the fifth generation (5G) and beyond wireless networks, which demands scal…