activity
20192022
most citedBackscatter Data Collection with Unmanned Ground Vehicle: Mobility Management and Power Allocation

22 citations · 34 across the 10 of their papers we have counts for

collaborators

11 papers

eess.SP20211 cited

Unit-Modulus Wireless Federated Learning Via Penalty Alternating Minimization

Shuai Wang, Dachuan Li, Rui Wang +3

Wireless federated learning (FL) is an emerging machine learning paradigm that trains a global parametric model from distributed datasets via wireless communications. This paper pr…

cs.IT20215 cited

Space Shift Keying with Reconfigurable Intelligent Surfaces: Phase Configuration Designs and Performance Analysis

Qiang Li, Miaowen Wen, Shuai Wang +2

Reconfigurable intelligent surface (RIS)-assisted transmission and space shift keying (SSK) appear as promising candidates for future energy-efficient wireless systems. In this pap…

cs.IT20204 cited

Reconfigurable Intelligent Surface Assisted Mobile Edge Computing with Heterogeneous Learning Tasks

Shanfeng Huang, Shuai Wang, Rui Wang +2

The ever-growing popularity and rapid improving of artificial intelligence (AI) have raised rethinking on the evolution of wireless networks. Mobile edge computing (MEC) provides a…

cs.IT2020

Learning Centric Wireless Resource Allocation for Edge Computing: Algorithm and Experiment

Liangkai Zhou, Yuncong Hong, Shuai Wang +4

Edge intelligence is an emerging network architecture that integrates sensing, communication, computing components, and supports various machine learning applications, where a fund…

eess.SP20201 cited

Edge Learning with Unmanned Ground Vehicle: Joint Path, Energy and Sample Size Planning

Dan Liu, Shuai Wang, Zhigang Wen +3

Edge learning (EL), which uses edge computing as a platform to execute machine learning algorithms, is able to fully exploit the massive sensing data generated by Internet of Thing…

cs.IT20201 cited

Learning Centric Power Allocation for Edge Intelligence

Shuai Wang, Rui Wang, Qi Hao +2

While machine-type communication (MTC) devices generate massive data, they often cannot process this data due to limited energy and computation power. To this end, edge intelligenc…