no code implementations • 28 Mar 2024 • Zirui Chen, Zhaoyang Zhang, Zhaohui Yang, Chongwen Huang, Merouane Debbah
How to reduce the pilot overhead required for channel estimation?
no code implementations • 7 Jan 2024 • Zirui Chen, Zhaoyang Zhang, Zhaohui Yang, Lei Liu
For such a channel mapping task, inspired by the intrinsic coupling across the space and frequency domains, this letter proposes to use interleaved learning with partial antenna and subcarrier characteristics to represent the whole MIMO-OFDM channel.
no code implementations • 11 Dec 2023 • Wenbin Guo, Zhao Li, Xin Wang, Zirui Chen
In this paper, we propose a novel dynamic convolutional embedding model ConvD for knowledge graph completion, which directly reshapes the relation embeddings into multiple internal convolution kernels to improve the external convolution kernels of the traditional convolutional embedding model.
no code implementations • 14 Aug 2023 • Zirui Chen, Zongyu Zuo
This paper presents a novel frequency-domain approach for path following problem, specifically designed to handle paths described by discrete data.
no code implementations • 14 Aug 2023 • Zirui Chen, Zongyu Zuo
The present article advances the concept of a non-singular cooperative guiding vector field under a homotopy equivalence transformation.
no code implementations • 9 Apr 2023 • Zhuoran Xiao, Zhaoyang Zhang, Zirui Chen, Zhaohui Yang, Chongwen Huang, Xiaoming Chen
Then, we design a novel physics-inspired spatial channel gradient network (SCGnet), which represents the derivative process of channel varying as a special neural network and can obtain the gradients at any relative displacement needed for the ODE solving.
no code implementations • 8 Jul 2022 • Zhuoran Xiao, Zhaoyang Zhang, Zirui Chen, Zhaohui Yang, Richeng Jin
Through exploring the intrinsic correlation among a set of historical CSI instances randomly obtained in a certain communication environment, channel prediction can significantly increase CSI accuracy and save signaling overhead.