no code implementations • 13 Apr 2024 • Zhe Wang, Jiayi Zhang, Hongyang Du, Ruichen Zhang, Dusit Niyato, Bo Ai, Khaled B. Letaief
Next-generation multiple input multiple output (MIMO) is expected to be intelligent and scalable.
no code implementations • 2 Apr 2024 • Yuanming Shi, Li Zeng, Jingyang Zhu, Yong Zhou, Chunxiao Jiang, Khaled B. Letaief
Although promising, the dynamics of LEO networks, characterized by the high mobility of satellites and short ground-to-satellite link (GSL) duration, pose unique challenges for FEEL.
no code implementations • 14 Mar 2024 • Xiang Peng, Zhijin Qin, Xiaoming Tao, Jianhua Lu, Khaled B. Letaief
Semantic communications have gained significant attention as a promising approach to address the transmission bottleneck, especially with the continuous development of 6G techniques.
no code implementations • 16 Feb 2024 • Songjie Xie, Youlong Wu, Jiaxuan Li, Ming Ding, Khaled B. Letaief
Based on the proposed method, we further develop a variational representation encoding approach that simultaneously achieves fairness and LDP.
1 code implementation • 18 Jan 2024 • Qiong Wu, Wenhua Wang, Pingyi Fan, Qiang Fan, Huiling Zhu, Khaled B. Letaief
Finally, we propose a multi-agent deep reinforcement learning (MADRL) based algorithm to decide where the predicted popular contents are collaboratively cached among SBSs.
no code implementations • 15 Jan 2024 • Minrui Xu, Dusit Niyato, Jiawen Kang, Zehui Xiong, Shiwen Mao, Zhu Han, Dong In Kim, Khaled B. Letaief
AI agents based on multimodal large language models (LLMs) are expected to revolutionize human-computer interaction and offer more personalized assistant services across various domains like healthcare, education, manufacturing, and entertainment.
no code implementations • 21 Dec 2023 • Ruoxiao Cao, Hengtao He, Xianghao Yu, Shenghui Song, Kaibin Huang, Jun Zhang, Yi Gong, Khaled B. Letaief
To address the joint channel estimation and cooperative localization problem for near-field UM-MIMO systems, we propose a variational Newtonized near-field channel estimation (VNNCE) algorithm and a Gaussian fusion cooperative localization (GFCL) algorithm.
no code implementations • 16 Dec 2023 • Wentao Yu, Hengtao He, Xianghao Yu, Shenghui Song, Jun Zhang, Ross D. Murch, Khaled B. Letaief
In this paper, we address the fundamental challenge of designing a low-complexity Bayes-optimal channel estimator in near-field HMIMO systems operating in unknown EM environments.
no code implementations • 9 Dec 2023 • Nguyen Van Huynh, Jiacheng Wang, Hongyang Du, Dinh Thai Hoang, Dusit Niyato, Diep N. Nguyen, Dong In Kim, Khaled B. Letaief
The recent evolution of generative artificial intelligence (GAI) leads to the emergence of groundbreaking applications such as ChatGPT, which not only enhances the efficiency of digital content production, such as text, audio, video, or even network traffic data, but also enriches its diversity.
no code implementations • 30 Nov 2023 • Qiong Wu, Wenhua Wang, Pingyi Fan, Qiang Fan, Jiangzhou Wang, Khaled B. Letaief
Vehicular edge computing (VEC) is a promising technology to support real-time vehicular applications, where vehicles offload intensive computation tasks to the nearby VEC server for processing.
no code implementations • 14 Nov 2023 • Wentao Yu, Hengtao He, Xianghao Yu, Shenghui Song, Jun Zhang, Ross D. Murch, Khaled B. Letaief
Holographic MIMO (HMIMO) has recently been recognized as a promising enabler for future 6G systems through the use of an ultra-massive number of antennas in a compact space to exploit the propagation characteristics of the electromagnetic (EM) channel.
no code implementations • 16 Oct 2023 • Jingyang Zhu, Yuanming Shi, Yong Zhou, Chunxiao Jiang, Wei Chen, Khaled B. Letaief
We first provide a comprehensive study on the convergence of AirComp-based FedAvg (AirFedAvg) algorithms under both strongly convex and non-convex settings with constant and diminishing learning rates in the presence of data heterogeneity.
no code implementations • 18 Sep 2023 • Wentao Yu, Yifan Ma, Hengtao He, Shenghui Song, Jun Zhang, Khaled B. Letaief
Ultra-massive multiple-input multiple-output (UMMIMO) is a cutting-edge technology that promises to revolutionize wireless networks by providing an unprecedentedly high spectral and energy efficiency.
no code implementations • 7 Aug 2023 • Lumin Liu, Jun Zhang, Shenghui Song, Khaled B. Letaief
To improve communication efficiency and achieve a better privacy-utility trade-off, we propose a communication-efficient FL training algorithm with differential privacy guarantee.
no code implementations • 6 Jul 2023 • Yifei Shen, Jiawei Shao, Xinjie Zhang, Zehong Lin, Hao Pan, Dongsheng Li, Jun Zhang, Khaled B. Letaief
The evolution of wireless networks gravitates towards connected intelligence, a concept that envisions seamless interconnectivity among humans, objects, and intelligence in a hyper-connected cyber-physical world.
1 code implementation • 21 May 2023 • Hongru Li, Wentao Yu, Hengtao He, Jiawei Shao, Shenghui Song, Jun Zhang, Khaled B. Letaief
Task-oriented communication is an emerging paradigm for next-generation communication networks, which extracts and transmits task-relevant information, instead of raw data, for downstream applications.
no code implementations • 5 May 2023 • Yuchen Shi, Zheqi Zhu, Pingyi Fan, Khaled B. Letaief, Chenghui Peng
Federated Learning (FL) is a promising distributed learning mechanism which still faces two major challenges, namely privacy breaches and system efficiency.
1 code implementation • 11 Mar 2023 • Zheqi Zhu, Yuchen Shi, Jiajun Luo, Fei Wang, Chenghui Peng, Pingyi Fan, Khaled B. Letaief
By adopting layer-wise pruning in local training and federated updating, we formulate an explicit FL pruning framework, FedLP (Federated Layer-wise Pruning), which is model-agnostic and universal for different types of deep learning models.
1 code implementation • 14 Feb 2023 • Hengtao He, Xianghao Yu, Jun Zhang, Shenghui Song, Khaled B. Letaief
As one of the core technologies for 5G systems, massive multiple-input multiple-output (MIMO) introduces dramatic capacity improvements along with very high beamforming and spatial multiplexing gains.
1 code implementation • 29 Nov 2022 • Wentao Yu, Yifei Shen, Hengtao He, Xianghao Yu, Shenghui Song, Jun Zhang, Khaled B. Letaief
For practical usage, the proposed framework is further extended to wideband THz UM-MIMO systems with beam squint effect.
no code implementations • 28 Nov 2022 • Yifan Ma, Wentao Yu, Xianghao Yu, Jun Zhang, Shenghui Song, Khaled B. Letaief
In this paper, we propose a lightweight and flexible deep learning-based CSI feedback approach by capitalizing on deep equilibrium models.
no code implementations • 15 Nov 2022 • Wentao Yu, Hengtao He, Xianghao Yu, Shenghui Song, Jun Zhang, Khaled B. Letaief
Reliability is of paramount importance for the physical layer of wireless systems due to its decisive impact on end-to-end performance.
no code implementations • 19 Oct 2022 • Zhibin Wang, Yapeng Zhao, Yong Zhou, Yuanming Shi, Chunxiao Jiang, Khaled B. Letaief
The rapid advancement of artificial intelligence technologies has given rise to diversified intelligent services, which place unprecedented demands on massive connectivity and gigantic data aggregation.
no code implementations • 5 Oct 2022 • Zheqi Zhu, Pingyi Fan, Chenghui Peng, Khaled B. Letaief
Then, we formulate the problem of selecting optimal IS weights and obtain the theoretical solutions.
no code implementations • 3 Sep 2022 • Yifan Ma, Xianghao Yu, Jun Zhang, S. H. Song, Khaled B. Letaief
In limited feedback multi-user multiple-input multiple-output (MU-MIMO) cellular networks, users send quantized information about the channel conditions to the associated base station (BS) for downlink beamforming.
1 code implementation • 10 May 2022 • Wentao Yu, Yifei Shen, Hengtao He, Xianghao Yu, Jun Zhang, Khaled B. Letaief
We draw inspirations from fixed point theory to develop an efficient deep learning based channel estimator with adaptive complexity and linear convergence guarantee.
1 code implementation • 30 Apr 2022 • Hongwei Zhang, Shuo Shao, Meixia Tao, Xiaoyan Bi, Khaled B. Letaief
In practice, the semantic information is defined by the pragmatic task of the receiver and cannot be known to the transmitter.
1 code implementation • 21 Mar 2022 • Yifei Shen, Jun Zhang, S. H. Song, Khaled B. Letaief
For design guidelines, we propose a unified framework that is applicable to general design problems in wireless networks, which includes graph modeling, neural architecture design, and theory-guided performance enhancement.
no code implementations • 14 Mar 2022 • Lumin Liu, Jun Zhang, S. H. Song, Khaled B. Letaief
Federated Distillation (FD) is a recently proposed alternative to enable communication-efficient and robust FL, which achieves orders of magnitude reduction of the communication overhead compared with FedAvg and is flexible to handle heterogeneous models at the clients.
no code implementations • 19 Dec 2021 • Huiqiang Xie, Zhijin Qin, Xiaoming Tao, Khaled B. Letaief
For the single-modal multi-user system, we will propose two Transformer based models, named, DeepSC-IR and DeepSC-MT, to perform image retrieval and machine translation, respectively.
no code implementations • 2 Dec 2021 • Shuo Wan, Jiaxun Lu, Pingyi Fan, Yunfeng Shao, Chenghui Peng, Khaled B. Letaief
In this paper, we develop a vertical-horizontal federated learning (VHFL) process, where the global feature is shared with the agents in a procedure similar to that of vertical FL without any extra communication rounds.
no code implementations • 24 Nov 2021 • Khaled B. Letaief, Yuanming Shi, Jianmin Lu, Jianhua Lu
The thriving of artificial intelligence (AI) applications is driving the further evolution of wireless networks.
no code implementations • 1 Oct 2021 • Yifan Ma, Yifei Shen, Xianghao Yu, Jun Zhang, S. H. Song, Khaled B. Letaief
Furthermore, such networks will vary dynamically in a significant way, which makes it intractable to develop comprehensive analytical models.
1 code implementation • 17 Aug 2021 • Yifei Shen, Yongji Wu, Yao Zhang, Caihua Shan, Jun Zhang, Khaled B. Letaief, Dongsheng Li
In this paper, we endeavor to obtain a better understanding of GCN-based CF methods via the lens of graph signal processing.
Ranked #5 on Collaborative Filtering on Gowalla
no code implementations • 3 Aug 2021 • Yifan Ma, Yifei Shen, Xianghao Yu, Jun Zhang, S. H. Song, Khaled B. Letaief
Channel estimation and beamforming play critical roles in frequency-division duplexing (FDD) massive multiple-input multiple-output (MIMO) systems.
no code implementations • 11 May 2021 • Wenzhi Fang, Yuning Jiang, Yuanming Shi, Yong Zhou, Wei Chen, Khaled B. Letaief
Over-the-air computation (AirComp) is a disruptive technique for fast wireless data aggregation in Internet of Things (IoT) networks via exploiting the waveform superposition property of multiple-access channels.
no code implementations • 30 Apr 2021 • Shuo Wan, Jiaxun Lu, Pingyi Fan, Yunfeng Shao, Chenghui Peng, Khaled B. Letaief
Federated learning (FL) has recently emerged as an important and promising learning scheme in IoT, enabling devices to jointly learn a model without sharing their raw data sets.
no code implementations • 26 Apr 2021 • Zhefeng Qiao, Xianghao Yu, Jun Zhang, Khaled B. Letaief
Federated learning (FL) is a promising and powerful approach for training deep learning models without sharing the raw data of clients.
1 code implementation • 4 Apr 2021 • He Wang, Yifei Shen, Ziyuan Wang, Dongsheng Li, Jun Zhang, Khaled B. Letaief, Jie Lu
In this paper, we investigate the decentralized statistical inference problem, where a network of agents cooperatively recover a (structured) vector from private noisy samples without centralized coordination.
no code implementations • 31 Mar 2021 • Lintao Li, Longwei Yang, Xin Guo, Yuanming Shi, Haiming Wang, Wei Chen, Khaled B. Letaief
Federated learning (FL) is a collaborative machine learning paradigm, which enables deep learning model training over a large volume of decentralized data residing in mobile devices without accessing clients' private data.
no code implementations • 26 Mar 2021 • Lumin Liu, Jun Zhang, Shenghui Song, Khaled B. Letaief
Hierarchical FL, with a client-edge-cloud aggregation hierarchy, can effectively leverage both the cloud server's access to many clients' data and the edge servers' closeness to the clients to achieve a high communication efficiency.
no code implementations • 28 Dec 2020 • Zheqi Zhu, Shuo Wan, Pingyi Fan, Khaled B. Letaief
To the best of our knowledge, it's the first joint MEC collaboration algorithm that combines the edge federated mode with the multi-agent actor-critic reinforcement learning.
1 code implementation • 15 Jul 2020 • Yifei Shen, Yuanming Shi, Jun Zhang, Khaled B. Letaief
In this paper, we propose to apply graph neural networks (GNNs) to solve large-scale radio resource management problems, supported by effective neural network architecture design and theoretical analysis.
no code implementations • 26 Apr 2020 • Ye Xue, Yifei Shen, Vincent Lau, Jun Zhang, Khaled B. Letaief
Specifically, we propose a novel $\ell_3$-norm-based formulation to recover the data without channel estimation.
1 code implementation • 24 Feb 2020 • Yifei Shen, Ye Xue, Jun Zhang, Khaled B. Letaief, Vincent Lau
Dictionary learning is a classic representation learning method that has been widely applied in signal processing and data analytics.
no code implementations • 24 Feb 2020 • Xiangyu Yang, Sheng Hua, Yuanming Shi, Hao Wang, Jun Zhang, Khaled B. Letaief
By exploiting the inherent connections between the set of task selection and group sparsity structural transmit beamforming vector, we reformulate the optimization as a group sparse beamforming problem.
no code implementations • 22 Feb 2020 • Yuanming Shi, Kai Yang, Tao Jiang, Jun Zhang, Khaled B. Letaief
By pushing inference and training processes of AI models to edge nodes, edge AI has emerged as a promising alternative.
2 code implementations • 19 Jul 2019 • Yifei Shen, Yuanming Shi, Jun Zhang, Khaled B. Letaief
Specifically, a $K$-user interference channel is first modeled as a complete graph, where the quantitative information of wireless channels is incorporated as the features of the graph.
no code implementations • 2 Jun 2019 • Jun Zhang, Khaled B. Letaief
The Internet of Vehicles (IoV) is an emerging paradigm, driven by recent advancements in vehicular communications and networking.
Networking and Internet Architecture Signal Processing
1 code implementation • 16 May 2019 • Lumin Liu, Jun Zhang, S. H. Song, Khaled B. Letaief
To combine their advantages, we propose a client-edge-cloud hierarchical Federated Learning system, supported with a HierFAVG algorithm that allows multiple edge servers to perform partial model aggregation.
no code implementations • 5 May 2019 • Shuo Wan, Jiaxun Lu, Pingyi Fan, Khaled B. Letaief
In this paper, a MEC-based big data analysis network is discussed.
no code implementations • 26 Apr 2019 • Khaled B. Letaief, Wei Chen, Yuanming Shi, Jun Zhang, Ying-Jun Angela Zhang
The recent upsurge of diversified mobile applications, especially those supported by Artificial Intelligence (AI), is spurring heated discussions on the future evolution of wireless communications.
2 code implementations • 22 Feb 2019 • Tian Lin, Jiaqi Cong, Yu Zhu, Jun Zhang, Khaled B. Letaief
A particular innovation in our proposed alternating minimization algorithms is a carefully designed initialization method, which leads to faster convergence.
Information Theory Information Theory
no code implementations • 18 Dec 2018 • Yifei Shen, Yuanming Shi, Jun Zhang, Khaled B. Letaief
To further address the task mismatch problem, we develop a transfer learning method via self-imitation in LORM, named LORM-TL, which can quickly adapt a pre-trained machine learning model to the new task with only a few additional unlabeled training samples.
no code implementations • 17 Nov 2018 • Yifei Shen, Yuanming Shi, Jun Zhang, Khaled B. Letaief
A unique advantage of the proposed method is that it can tackle the task mismatch issue with a few additional unlabeled training samples, which is especially important when transferring to large-size problems.
no code implementations • 18 May 2016 • Yuyi Mao, Jun Zhang, Khaled B. Letaief
Sample simulation results shall be presented to verify the theoretical analysis as well as validate the effectiveness of the proposed algorithm.
Information Theory Information Theory