1. Officers:

Chair: Yang Yang, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, China, Email: yang.yang@mail.sim.ac.cn

Vice-Chair: Shuguang Cui, The Chinese University of Hong Kong Shenzhen, China, Email: shuguangcui@cuhk.edu.cn

Vice-Chair: Olav Tirkkonen, Department of Communications and Networking, Aalto University, Electrical Engineering Building, Otakaari 5, 02150 Espoo, Finland. Email: olav.tirkkonen@aalto.fi

Vice-Chair: Cheng-Xiang Wang, Southeast University China , Email: chxwang@seu.edu.cn

  1. Scope and Objectives:

The popularity of smart devices and multimedia applications contribute to the surge of mobile data traffic. Besides, in order to pursuit higher performance, modern wireless communication systems generally employ advanced signal processing techniques which can alleviate the system’s pressure from vast data traffic, such as MIMO antenna system. On the one hand, the big data poses challenges to all aspects of the wireless system design. On the other hand, we can also create and utilize modern big data technology to analyze networks and patterns of user’ behavior to construct a data-aware wireless communication system with better service quality.

This SIG will focus on issues related to how to construct a scalable wireless network architecture to deal with vast data traffic efficiently, and how to improve the wireless system’s performance by using big data innovations.

Due to the huge volume of data, neither BS-centric network nor cloud-centric network is favorable. A new hybrid network structure must be proposed. Furthermore, efficient signal processing techniques, along with traffic management techniques and resource allocation strategy also constitute such an architecture.

       To utilize big data, we first need to understand what data can be regarded as big data. We think that wireless big data could be classified as: wireless channel data, network data and user data. Thanks to the development of measuring techniques, abundant wireless channel data could be measured to construct channel model. So is network data which could be applied to optimize network. User data means data generated at user side, such as social network data.

Next, data-analytical methods could be applied to extract the characteristics of wireless big data. Once identified, data characteristics could be used to improve wireless service quality. For a mature data-aware wireless system, it should be more intelligent and cooperative. Some functionalities, we think the data-aware wireless system should have, include crowd computing, context/social-aware processing and so forth need to be considered. Besides, we also look forward to more concrete applications in wireless communication with respect to big data.

In summary, this SIG will focus on techniques to handle and utilize big data in wireless systems. The main sub-areas of interest include, but not limited to,

  • Network architecture
  • Signal processing techniques
  • Traffic management techniques
  • Resource allocation strategy
  • Data-aware cache management
  • Crowd computing
  • Wireless cloudlet
  • Context/social-aware processing
  • Software-defined networking
  • Wireless sensor network/IOT
  • Social network
  • Big data analysis tools for Wireless Communication
  • Big data applications in Wireless Communication
  • Mobile data security and privacy
  • Network function virtualization