no code implementations • 20 Apr 2024 • Feibo Jiang, Li Dong, Siwei Tu, Yubo Peng, Kezhi Wang, Kun Yang, Cunhua Pan, Dusit Niyato
Large Language Models (LLMs) have revolutionized natural language processing tasks.
no code implementations • 9 Mar 2024 • Feibo Jiang, Yubo Peng, Li Dong, Kezhi Wang, Kun Yang, Cunhua Pan, Xiaohu You
Semantic Communication (SC) is a novel paradigm for data transmission in 6G.
no code implementations • 13 Dec 2023 • Feibo Jiang, Li Dong, Yubo Peng, Kezhi Wang, Kun Yang, Cunhua Pan, Dusit Niyato, Octavia A. Dobre
The rapid development of the Large Language Model (LLM) presents huge opportunities for 6G communications, e. g., network optimization and management by allowing users to input task requirements to LLMs by nature language.
no code implementations • 3 Sep 2023 • Feibo Jiang, Yubo Peng, Li Dong, Kezhi Wang, Kun Yang, Cunhua Pan, Xiaohu You
To this end, we propose a Large AI Model-based Multimodal SC (LAM-MSC) framework, in which we first present the MLM-based Multimodal Alignment (MMA) that utilizes the MLM to enable the transformation between multimodal and unimodal data while preserving semantic consistency.
no code implementations • 29 Aug 2023 • Li Dong, Feibo Jiang, Yubo Peng, Kezhi Wang, Kun Yang, Cunhua Pan, Robert Schober
Next-generation edge intelligence is anticipated to bring huge benefits to various applications, e. g., offloading systems.
no code implementations • 21 Jul 2023 • Yao Wen, Guopeng Zhang, Kezhi Wang, Kun Yang
To alleviate the shortage of computing power faced by clients in training deep neural networks (DNNs) using federated learning (FL), we leverage the edge computing and split learning to propose a model-splitting allowed FL (SFL) framework, with the aim to minimize the training latency without loss of test accuracy.
no code implementations • 7 Jul 2023 • Feibo Jiang, Yubo Peng, Li Dong, Kezhi Wang, Kun Yang, Cunhua Pan, Xiaohu You
Semantic communication (SC) is an emerging intelligent paradigm, offering solutions for various future applications like metaverse, mixed-reality, and the Internet of everything.
no code implementations • 5 May 2023 • Na Yan, Kezhi Wang, Cunhua Pan, Kok Keong Chai, Feng Shu, Jiangzhou Wang
We aim to improve the learning performance by jointly designing the device scheduling, alignment coefficient, and the number of aggregation rounds of federated averaging (FedAvg) subject to sum power and privacy constraints.
no code implementations • 26 Dec 2022 • Musbahu Mohammed Adam, Liqiang Zhao, Kezhi Wang, Zhu Han
In recent years, the exponential proliferation of smart devices with their intelligent applications poses severe challenges on conventional cellular networks.
no code implementations • 31 Oct 2022 • Na Yan, Kezhi Wang, Cunhua Pan, Kok Keong Chai
The scheme schedules the devices with better channel conditions in the training to avoid the problem that the alignment coefficient is limited by the device with the worst channel condition in the system.
no code implementations • 27 Oct 2022 • Li Dong, Zhibin Liu, Feibo Jiang, Kezhi Wang
To address this issue, we propose a joint optimization framework of deployment and trajectory (JOLT), where an adaptive whale optimization algorithm (AWOA) is applied to optimize the deployment of the UAV, and an elastic ring self-organizing map (ERSOM) is introduced to optimize the trajectory of the UAV.
no code implementations • 14 Oct 2022 • Na Yan, Kezhi Wang, Kangda Zhi, Cunhua Pan, Kok Keong Chai, H. Vincent Poor
In this paper, a novel secure and private over-the-air federated learning (SP-OTA-FL) framework is studied where noise is employed to protect data privacy and system security.
no code implementations • 23 Sep 2021 • Muhammad Khalid, Liang Wang, Kezhi Wang, Cunhua Pan, Nauman Aslam, Yue Cao
In this paper, to reduce the congestion rate at the city center and increase the quality of experience (QoE) of each user, the framework of long-range autonomous valet parking (LAVP) is presented, where an Autonomous Vehicle (AV) is deployed in the city, which can pick up, drop off users at their required spots, and then drive to the car park out of city center autonomously.
no code implementations • 26 Feb 2021 • Jeyamohan Neera, Xiaomin Chen, Nauman Aslam, Kezhi Wang, Zhan Shu
At the SP, The MoG model estimates the noise added to perturbed ratings and the MF algorithm predicts missing ratings.
no code implementations • 8 Feb 2021 • Yijin Pan, Kezhi Wang, Cunhua Pan, Huiling Zhu, Jiangzhou Wang
This paper proposes a new simultaneous terahertz (THz) information and power transfer (STIPT) system, which is assisted by reconfigurable intelligent surface (RIS) for both the information data and power transmission.
no code implementations • 23 Dec 2020 • Gui Zhou, Cunhua Pan, Hong Ren, Kezhi Wang, Zhangjie Peng
In this paper, we study the robust transmission design for a reconfigurable intelligent surface (RIS)-aided secure communication system in the presence of transceiver hardware impairments.
Information Theory Signal Processing Information Theory
no code implementations • 19 Nov 2020 • Sheng Hong, Cunhua Pan, Gui Zhou, Hong Ren, Kezhi Wang
In this paper, we investigate the robust outage constrained transmission design for an intelligent reflecting surface (IRS) aided secure communication system.
no code implementations • 9 Nov 2020 • Cunhua Pan, Hong Ren, Kezhi Wang, Jonas Florentin Kolb, Maged Elkashlan, Ming Chen, Marco Di Renzo, Yang Hao, Jiangzhou Wang, A. Lee Swindlehurst, Xiaohu You, Lajos Hanzo
Reconfigurable intelligent surfaces (RISs) or intelligent reflecting surfaces (IRSs), are regarded as one of the most promising and revolutionizing techniques for enhancing the spectrum and/or energy efficiency of wireless systems.
no code implementations • 27 Oct 2020 • Yijin Pan, Kezhi Wang, Cunhua Pan, Huiling Zhu, Jiangzhou Wang
In this paper, unmanned aerial vehicles (UAVs) and intelligent reflective surface (IRS) are utilized to support terahertz (THz) communications.
no code implementations • 26 Oct 2020 • Kangda Zhi, Cunhua Pan, Hong Ren, Kezhi Wang
We consider the Rician channel model and exploit the long-time statistical CSI to design the phase shifts of the RIS, while the maximum ratio combination (MRC) technique is applied for the active beamforming at the base station (BS) relying on the instantaneous CSI.
no code implementations • 18 Oct 2020 • Yifan Luo, Jindan Xu, Wei Xu, Kezhi Wang
Federated learning (FL) in a bandwidth-limited network with energy-limited user equipments (UEs) is under-explored.
no code implementations • 23 Sep 2020 • Liang Wang, Kezhi Wang, Cunhua Pan, Wei Xu, Nauman Aslam, Lajos Hanzo
An unmanned aerial vehicle (UAV)-aided mobile edge computing (MEC) framework is proposed, where several UAVs having different trajectories fly over the target area and support the user equipments (UEs) on the ground.
no code implementations • 21 Sep 2020 • Gui Zhou, Cunhua Pan, Hong Ren, Kezhi Wang, Maged Elkashlan, Marco Di Renzo
To enhance the robustness of hybrid analog-digital beamforming in the presence of random blockages, we formulate a stochastic optimization problem based on the minimization of the sum outage probability.
no code implementations • 2 Aug 2020 • Kangda Zhi, Cunhua Pan, Hong Ren, Kezhi Wang
In this paper, we derive the uplink achievable rate expression of intelligent reflecting surface (IRS)-aided millimeter-wave (mmWave) systems, taking into account the phase noise at IRS and the quantization error at base stations (BSs).
no code implementations • 27 Jul 2020 • Muhammad Asim, Yong Wang, Kezhi Wang, Pei-Qiu Huang
These optimization problems usually have complex properties, such as non-convexity and NP-hardness, which may not be addressed by the traditional convex optimization-based solutions.
no code implementations • 20 Jul 2020 • Hong Ren, Cunhua Pan, Kezhi Wang, Wei Xu, Maged Elkashlan, Arumugam Nallanathan
This letter considers an unmanned aerial vehicle (UAV)-enabled relay communication system for delivering latency-critical messages with ultra-high reliability, where the relay is operating under amplifier-and-forward (AF) mode.
1 code implementation • 16 Jul 2020 • Liang Wang, Kezhi Wang, Cunhua Pan, Nauman Aslam
In this paper, the intelligent reflecting surface (IRS)-aided unmanned aerial vehicle (UAV) communication system is studied, where the UAV is deployed to serve the user equipment (UE) with the assistance of multiple IRSs mounted on several buildings to enhance the communication quality between UAV and UE.
no code implementations • 9 Jun 2020 • Gui Zhou, Cunhua Pan, Hong Ren, Kezhi Wang, Kok Keong Chai, Kai-Kit Wong
In this paper, intelligent reflecting surface (IRS) is proposed to enhance the physical layer security in the Rician fading channel where the angular direction of the eavesdropper is aligned with a legitimate user.
no code implementations • 21 May 2020 • Feibo Jiang, Li Dong, Kezhi Wang, Kun Yang, Cunhua Pan
We consider the optimization of distributed resource scheduling to minimize the sum of task latency and energy consumption for all the Internet of things devices (IoTDs) in a large-scale mobile edge computing (MEC) system.
no code implementations • 24 Apr 2020 • Sheng Hong, Cunhua Pan, Hong Ren, Kezhi Wang, Kok Keong Chai, Arumugam Nallanathan
To minimize the transmit power, the beamforming vector at the transmitter, the AN covariance matrix, and the IRS phase shifts are jointly optimized subject to the outage rate probability constraints under the statistical cascaded channel state information (CSI) error model that usually models the channel estimation error.
no code implementations • 9 Apr 2020 • Lei Zhang, Cunhua Pan, Yu Wang, Hong Ren, Kezhi Wang
Simulation results verify the efficiency of the proposed algorithms and reveal the impacts of CSI uncertainties on ST's minimum transmit power and feasibility rate of the optimization problems.
no code implementations • 17 Feb 2020 • Sheng Hong, Cunhua Pan, Hong Ren, Kezhi Wang, Arumugam Nallanathan
To tackle it, we propose to utilize the block coordinate descent (BCD) algorithm to alternately update the TPC matrix, AN covariance matrix, and phase shifts while keeping SR non-decreasing.
no code implementations • 11 Feb 2020 • Feibo Jiang, Kezhi Wang, Li Dong, Cunhua Pan, Wei Xu, Kun Yang
By taking full advantage of Computing, Communication and Caching (3C) resources at the network edge, Mobile Edge Computing (MEC) is envisioned as one of the key enablers for the next generation networks.
no code implementations • 24 Jan 2020 • Feibo Jiang, Kezhi Wang, Li Dong, Cunhua Pan, Kun Yang
An online resource scheduling framework is proposed for minimizing the sum of weighted task latency for all the Internet of things (IoT) users, by optimizing offloading decision, transmission power and resource allocation in the large-scale mobile edge computing (MEC) system.
no code implementations • 20 Jan 2020 • Gui Zhou, Cunhua Pan, Hong Ren, Kezhi Wang, Arumugam Nallanathan
Specifically, the transmit power minimization problems are formulated subject to the worst-case rate constraints under the bounded CSI error model and the rate outage probability constraints under the statistical CSI error model, respectively.
no code implementations • 14 Nov 2019 • Gui Zhou, Cunhua Pan, Hong Ren, Kezhi Wang, Marco Di Renzo, Arumugam Nallanathan
In this paper, we study the worst-case robust beamforming design for an IRS-aided multiuser multiple-input single-output (MU-MISO) system under the assumption of imperfect CSI.
no code implementations • 10 Nov 2019 • Liang Wang, Kezhi Wang, Cunhua Pan, Wei Xu, Nauman Aslam, Arumugam Nallanathan
In this paper, we consider a platform of flying mobile edge computing (F-MEC), where unmanned aerial vehicles (UAVs) serve as equipment providing computation resource, and they enable task offloading from user equipment (UE).
no code implementations • 24 Sep 2019 • Chao Lu, Wei Xu, Shi Jin, Kezhi Wang
Quantized channel state information (CSI) plays a critical role in precoding design which helps reap the merits of multiple-input multiple-output (MIMO) technology.
Information Theory Signal Processing Information Theory
no code implementations • 10 Sep 2019 • Gui Zhou, Cunhua Pan, Hong Ren, Kezhi Wang, Arumugam Nallanathan
We aim for maximizing the sum rate of all the multicasting groups by the joint optimization of the precoding matrix at the base station (BS) and the reflection coefficients at the IRS under both the power and unit-modulus constraint.
no code implementations • 8 Apr 2019 • Liang Wang, Peiqiu Huang, Kezhi Wang, Guopeng Zhang, Lei Zhang, Nauman Aslam, Kun Yang
In this paper, multi-unmanned aerial vehicle (UAV) enabled mobile edge computing (MEC), i. e., UAVE is studied, where several UAVs are deployed as flying MEC platform to provide computing resource to ground user equipments (UEs).