no code implementations • 15 Dec 2023 • Fan Zhang, Jining Chen, Kunlun Wang, Wen Chen
we formulate a joint device scheduling, and power allocation problem to maximize the number of scheduled devices.
no code implementations • 4 May 2023 • Ziwei Liu, Wen Chen, Zhendong Li, Jinhong Yuan, Qingqing Wu, Kunlun Wang
In this paper, we investigated the downlink transmission problem of a cognitive radio network (CRN) equipped with a novel transmissive reconfigurable intelligent surface (TRIS) transmitter.
no code implementations • 9 Apr 2023 • Shunfeng Chu, Jun Li, Kang Wei, Yuwen Qian, Kunlun Wang, Feng Shu, Wen Chen
In this paper, we design two-level incentive mechanisms for the HFL with a two-tiered computing structure to encourage the participation of entities in each tier in the HFL training.
no code implementations • 11 Sep 2021 • Asim Ihsan, Wen Chen, Wali Ullah Khan, Qingqing Wu, Kunlun Wang
In the second stage, AOBWS uses a non-iterative algorithm that provides a closed-form expression for the computation of optimal reflection coefficient for roadside sensors under their quality of service (QoS) and a circuit power constraint.
no code implementations • 23 Jul 2021 • Zhendong Li, Wen Chen, Huanqing Cao, Hongying Tang, Kunlun Wang, Jun Li
Aiming at the limited battery capacity of widely deployed low-power smart devices in the Internet-of-things (IoT), this paper proposes a novel intelligent reflecting surface (IRS) empowered unmanned aerial vehicle (UAV) simultaneous wireless information and power transfer (SWIPT) network framework, in which IRS is used to reconstruct the wireless channel to enhance the wireless energy transmission efficiency and coverage area of the UAV SWIPT networks.
no code implementations • 21 Apr 2020 • Samira Jaber, Wen Chen, Kunlun Wang, Qingqing Wu
Moreover, the proposed method is compared with orthogonal frequency devision multiple access (OFDMA) and code devision multiple access (CDMA) in terms of spectral efficiency (SE) and energy efficiency (EE) respectively.
no code implementations • Conference 2018 • Zening Liu, Xiumei Yang, Yang Yang, Kunlun Wang, and Guoqiang Mao, Fellow, IEEE
Abstract—Fog computing has risen as a promising architecture for future Internet of Things (IoT), 5G and embedded artificial intelligence (AI) applications with stringent service delay requirements along the cloud to things continuum.