Big Spectrum Data: The New Resource for Cognitive Wireless Networking

The era of Big Data is here now, which has brought both unprecedented opportunities and critical challenges. In this article, from a perspective of cognitive wireless networking, we start with a definition of Big Spectrum Data by analyzing its characteristics in terms of six V’s, i.e., volume, variety, velocity, veracity, viability, and value. We then present a high-level tutorial on research frontiers in Big Spectrum Data analytics to guide the development of practical algorithms. We also highlight Big Spectrum Data as the new resource for cognitive wireless networking by presenting the emerging use cases. We now live in an era of data deluge. We live in a world that has more than a billion transistors per human; a world with more than 4 billion mobile phone subscribers and about 30 billion radio frequency identification tags produced globally within the last two years [1]. All these sensors generate data. Sadly, much of this data is simply thrown away, because of the lack of efficient mechanisms to derive value from it. This fact motivates the worldwide increasing interests in Big Data. Although there are still debates on whether Big Data is a big opportunity or a big bubble, Big Data is here now and is going to transform how we gain insights and how we make decisions in the future [2]. To leverage the Big Data opportunities and challenges, many governments, organizations and academic institutions come forward to take initiates. For example, the US This work is supported by the National Natural Science Foundation of China (Grant No. 61172062 and No. 61301160), Jiangsu Province Natural Science Foundation (Grant No. BK2011116), and in part by the National Basic Research Program of China (Grant No. 2009CB320400). DRAFT ar X iv :1 40 4. 65 08 v1 [ cs .O H ] 2 3 A pr 2 01 4