activity
20172022
most citedStochastic Joint Radio and Computational Resource Management for Multi-User Mobile-Edge Computing Systems

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.IT2022

Error Rate Analysis for Grant-free Massive Random Access with Short-Packet Transmission

Xinyu Bian, Yuyi Mao, Jun Zhang

Grant-free massive random access (RA) is a promising protocol to support the massive machine-type communications (mMTC) scenario in 5G and beyond networks. In this paper, we focus…

cs.LG2021

Communication-Computation Efficient Device-Edge Co-Inference via AutoML

Xinjie Zhang, Jiawei Shao, Yuyi Mao +1

Device-edge co-inference, which partitions a deep neural network between a resource-constrained mobile device and an edge server, recently emerges as a promising paradigm to suppor…

eess.SP2021

Joint Activity Detection and Data Decoding in Massive Random Access via a Turbo Receiver

Xinyu Bian, Yuyi Mao, Jun Zhang

In this paper, we propose a turbo receiver for joint activity detection and data decoding in grant-free massive random access, which iterates between a detector and a belief propag…

eess.SP2021

Supporting More Active Users for Massive Access via Data-assisted Activity Detection

Xinyu Bian, Yuyi Mao, Jun Zhang

Massive machine-type communication (mMTC) has been regarded as one of the most important use scenarios in the fifth generation (5G) and beyond wireless networks, which demands scal…

cs.IT20171 cited

Stochastic Joint Radio and Computational Resource Management for Multi-User Mobile-Edge Computing Systems

Yuyi Mao, Jun Zhang, S. H. Song +1

Mobile-edge computing (MEC) has recently emerged as a prominent technology to liberate mobile devices from computationally intensive workloads, by offloading them to the proximate…