Radiomap Inpainting for Restricted Areas based on Propagation Priority and Depth Map

no code implementations • 24 May 2023 • Songyang Zhang, Tianhang Yu, Brian Choi, Feng Ouyang, Zhi Ding

Providing rich and useful information regarding spectrum activities and propagation channels, radiomaps characterize the detailed distribution of power spectral density (PSD) and are important tools for network planning in modern wireless systems.

Exemplar-Based Radio Map Reconstruction of Missing Areas Using Propagation Priority

no code implementations • 10 Sep 2022 • Songyang Zhang, Tianhang Yu, Jonathan Tivald, Brian Choi, Feng Ouyang, Zhi Ding

Radio map describes network coverage and is a practically important tool for network planning in modern wireless systems.

INT8 Winograd Acceleration for Conv1D Equipped ASR Models Deployed on Mobile Devices

no code implementations • 28 Oct 2020 • Yiwu Yao, Yuchao Li, Chengyu Wang, Tianhang Yu, Houjiang Chen, Xiaotang Jiang, Jun Yang, Jun Huang, Wei Lin, Hui Shu, Chengfei Lv

The intensive computation of Automatic Speech Recognition (ASR) models obstructs them from being deployed on mobile devices.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +2

MNN: A Universal and Efficient Inference Engine

1 code implementation • 27 Feb 2020 • Xiaotang Jiang, Huan Wang, Yiliu Chen, Ziqi Wu, Lichuan Wang, Bin Zou, Yafeng Yang, Zongyang Cui, Yu Cai, Tianhang Yu, Chengfei Lv, Zhihua Wu

Deploying deep learning models on mobile devices draws more and more attention recently.

Scheduling

Buffer-aware Wireless Scheduling based on Deep Reinforcement Learning

no code implementations • 13 Nov 2019 • Chen Xu, Jian Wang, Tianhang Yu, Chuili Kong, Yourui Huangfu, Rong Li, Yiqun Ge, Jun Wang

In this paper, the downlink packet scheduling problem for cellular networks is modeled, which jointly optimizes throughput, fairness and packet drop rate.

Fairness reinforcement-learning +2