no code implementations • 31 May 2024 • Wenchao Liu, Xuhui Zhang, Huijun Xing, Jinke Ren, Yanyan Shen, Shuguang Cui
Recently, movable antenna (MA) array becomes a promising technology for improving the communication quality in wireless communication systems.
no code implementations • 29 Apr 2024 • Huijun Xing, Xuhui Zhang, Shuo Chang, Jinke Ren, Zixun Zhang, Jie Xu, Shuguang Cui
Different from prior works that investigate them independently, this paper studies the joint signal detection and automatic modulation classification (AMC) by considering a realistic and complex scenario, in which multiple signals with different modulation schemes coexist at different carrier frequencies.
no code implementations • 27 Apr 2024 • Lichao Wang, Zhihao Yuan, Jinke Ren, Shuguang Cui, Zhen Li
In this paper, we address two key limitations of existing approaches: 1) their reliance on ground-truth instances as input; and 2) their neglect of the relative positions among potential instances.
no code implementations • 29 Jan 2024 • Yijing Lin, Zhipeng Gao, Hongyang Du, Jinke Ren, Zhiqiang Xie, Dusit Niyato
However, existing works require central servers to retain the historical model parameters from distributed clients, such that allows the central server to utilize these parameters for further training even, after the clients exit the training process.
no code implementations • 29 Jan 2024 • Yijing Lin, Zhipeng Gao, Hongyang Du, Dusit Niyato, Gui Gui, Shuguang Cui, Jinke Ren
Federated unlearning has emerged as a promising paradigm to erase the client-level data effect without affecting the performance of collaborative learning models.
no code implementations • 26 Nov 2023 • Zhihao Yuan, Jinke Ren, Chun-Mei Feng, Hengshuang Zhao, Shuguang Cui, Zhen Li
Building on this, we design a visual program that consists of three types of modules, i. e., view-independent, view-dependent, and functional modules.
no code implementations • 21 Nov 2023 • Jinke Ren, Zezhong Zhang, Jie Xu, GuanYing Chen, Yaping Sun, Ping Zhang, Shuguang Cui
Semantic communication is widely touted as a key technology for propelling the sixth-generation (6G) wireless networks.
no code implementations • 26 May 2023 • Rui Sun, Andi Zhang, Haiming Zhang, Jinke Ren, Yao Zhu, Ruimao Zhang, Shuguang Cui, Zhen Li
Specifically, our framework consists of two components: a sample repairing module and a detection module.
Generative Adversarial Network Out-of-Distribution Detection +1
no code implementations • 19 Jul 2021 • Jinke Ren, Chonghe Liu, Guanding Yu, Dongning Guo
This paper proposes a new framework for training GANs in a distributed fashion: Each device computes a local discriminator using local data; a single server aggregates their results and computes a global GAN.
no code implementations • 1 Apr 2020 • Jinke Ren, Yinghui He, Dingzhu Wen, Guanding Yu, Kaibin Huang, Dongning Guo
In this paper, a novel scheduling policy is proposed to exploit both diversity in multiuser channels and diversity in the "importance" of the edge devices' learning updates.
no code implementations • 10 Nov 2019 • Dingzhu Wen, Xiaoyang Li, Qunsong Zeng, Jinke Ren, Kaibin Huang
Specifically, the metrics that measure data importance in active learning (e. g., classification uncertainty and data diversity) are applied to RRM for efficient acquisition of distributed data in wireless networks to train AI models at servers.
no code implementations • 23 May 2019 • Jinke Ren, Guanding Yu, Guangyao Ding
The optimal solution in this scenario is manifested to have the similar structure as that of the CPU scenario, recommending that our proposed algorithm is applicable in more general systems.