Jingchu Liu

Jingchu Liu
Tsinghua University | TH · Department of Electrical Engineering

BSc

About

13
Publications
3,005
Reads
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362
Citations
Introduction
LIU Jingchu is currently a PhD student at the Department of Electronic Engineering, Tsinghua University. He received his B.S. degree in Electronic Engineering from Tsinghua University, Beijing, China, in 2012. His research interests include cloud-based cellular/wireless networks, cellular big data, and green wireless communications.
Additional affiliations
September 2012 - November 2015
Tsinghua University
Position
  • PhD Student
September 2012 - December 2015
Tsinghua University
Position
  • PhD Student and Visiting Scholar @ USC
September 2008 - present
Tsinghua University
Position
  • PhD Student

Publications

Publications (13)
Conference Paper
Full-text available
Wireless communication networks rely heavily on channel state information (CSI) to make informed decision for signal processing and network operations. However, the traditional CSI acquisition methods is facing many difficulties: pilot-aided channel training consumes a great deal of channel resources and reduces the opportunities for energy saving,...
Conference Paper
Full-text available
User behaviour analysis based on traffic log in wireless networks can be beneficial to many fields in real life: not only for commercial purposes, but also for improving network service quality and social management. We cluster users into groups marked by the most frequently visited websites to find their preferences. In this paper, we propose a us...
Conference Paper
Full-text available
Accurate traffic forecast is important for efficient network planning and operations. However, existing traffic prediction models have high complexity, making the forecasting process slow and costly. In this paper, we propose a Block Regression (BR) model for mobile traffic forecasting. This model employs seasonal differentiation so as to take into...
Article
Full-text available
The fronthaul is an indispensable enabler for 5G networks. However, the classical fronthauling method demands large bandwidth, low latency,and tight synchronization from the transport network, and only allows for point-to-point logical topology. This greatly limits the usage of fronthaul in many 5G scenarios. In this article, we introduce a new per...
Article
Full-text available
Cellular networks are one of the corner stones of our information-driven society. However, existing cellular systems have been seriously challenged by the explosion of mobile data traffic, the emergence of machine-type communications and the flourish of mobile Internet services. In this article, we propose CONCERT (CONvergence of Cloud and cEllulaR...
Article
Full-text available
Base station sleeping is an effective way to reduce the energy consumption of mobile networks. Previous efforts to design sleeping control algorithms mainly rely on stochastic traffic models and analytical derivation. However the tractability of models often conflicts with the complexity of real-world traffic, making it difficult to apply in realit...
Preprint
Full-text available
Tactical driving decision making is crucial for autonomous driving systems and has attracted considerable interest in recent years. In this paper, we propose several practical components that can speed up deep reinforcement learning algorithms towards tactical decision making tasks: 1) non-uniform action skipping as a more stable alternative to act...
Article
Cloud radio access network (C-RAN) is proposed recently to reduce network cost, enable cooperative communications, and increase system flexibility through centralized baseband processing. By pooling multiple virtual base stations (VBSs) and consolidating their stochastic computational tasks, the overall computational resource can be reduced, achiev...
Conference Paper
Full-text available
The baseband-up centralization architecture of radio access networks (C-RAN) has recently been proposed to support efficient cooperative communications and reduce deployment and operational costs. However, the massive fronthaul bandwidth required to aggregate baseband samples from remote radio heads (RRHs) to the central office incurs huge fronthau...
Conference Paper
Full-text available
Facing the explosion of mobile data traffic, cloud radio access network (C-RAN) is proposed recently to overcome the efficiency and flexibility problems with the traditional RAN architecture by centralizing baseband processing. However, there lacks a mathematical model to analyze the statistical multiplexing gain from the pooling of virtual base st...

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Projects

Project (1)
Archived project