3 citations · 10 across the 11 of their papers we have counts for
11 papers
Fully-Passive versus Semi-Passive IRS-Enabled Sensing: SNR Analysis
Xianxin Song, Xinmin Li, Xiaoqi Qin +1
This paper compares the signal-to-noise ratio (SNR) performance between the fully-passive intelligent reflecting surface (IRS)-enabled non-line-of-sight (NLoS) sensing versus its s…
Cramér-Rao Bound Minimization for IRS-Enabled Multiuser Integrated Sensing and Communications
Xianxin Song, Xiaoqi Qin, Jie Xu +1
This paper investigates an intelligent reflecting surface (IRS) enabled multiuser integrated sensing and communications (ISAC) system, which consists of one multi-antenna base stat…
AoI-Delay Tradeoff in Mobile Edge Caching: A Mixed-Order Drift-Plus-Penalty Algorithm
Ran Li, Chuan Huang, Xiaoqi Qin +1
Mobile edge caching (MEC) is a promising technique to improve the quality of service (QoS) for mobile users (MU) by bringing data to the network edge. However, optimizing the cruci…
Efficient Sensor Scheduling Strategy Based on Spatio-temporal Scope Information Model
Yang Liu, Chen Dong, Xiaoqi Qin +1
In this paper, based on the spatio-temporal correlation of sensor nodes in the Internet of Things (IoT), a Spatio-temporal Scope information model (SSIM) is proposed to quantify th…
Service Delay Minimization for Federated Learning over Mobile Devices
Rui Chen, Dian Shi, Xiaoqi Qin +3
Federated learning (FL) over mobile devices has fostered numerous intriguing applications/services, many of which are delay-sensitive. In this paper, we propose a service delay eff…
Coexistence between Task- and Data-Oriented Communications: A Whittle's Index Guided Multi-Agent Reinforcement Learning Approach
Ran Li, Chuan Huang, Xiaoqi Qin +3
We investigate the coexistence of task-oriented and data-oriented communications in a IoT system that shares a group of channels, and study the scheduling problem to jointly optimi…
Dynamic Clustering and Power Control for Two-Tier Wireless Federated Learning
Wei Guo, Chuan Huang, Xiaoqi Qin +2
Federated learning (FL) has been recognized as a promising distributed learning paradigm to support intelligent applications at the wireless edge, where a global model is trained i…
Joint Device Selection and Power Control for Wireless Federated Learning
Wei Guo, Ran Li, Chuan Huang +3
This paper studies the joint device selection and power control scheme for wireless federated learning (FL), considering both the downlink and uplink communications between the par…
Multicast Scheduling over Multiple Channels: A Distribution-Embedding Deep Reinforcement Learning Method
Ran Li, Chuan Huang, Xiaoqi Qin +1
Multicasting is an efficient technique for simultaneously transmitting common messages from the base station (BS) to multiple mobile users (MUs). Multicast scheduling over multiple…
Age Based Task Scheduling and Computation Offloading in Mobile-Edge Computing Systems
Xianxin Song, Xiaoqi Qin, Yunzheng Tao +2
To support emerging real-time monitoring and control applications, the timeliness of computation results is of critical importance to mobile-edge computing (MEC) systems. We propos…
Distributed Layered Grant-Free Non-Orthogonal Multiple Access for Massive MTC
Hui Jiang, Qimei Cui, Yu Gu +3
Grant-free transmission is considered as a promising technology to support sporadic data transmission in massive machine-type communications (mMTC). Due to the distributed manner,…