Cognitive radio (CR) is the enabling technology for supporting dynamic spectrum access:
the policy that addresses the spectrum scarcity problem that is encountered in many …

With the growth of network applications such as 5G and artificial intelligence, network
security techniques, ie, the techniques that detect various attacks (eg, well-known denial-of …

Intelligent Transportation Systems (ITSs) are vital for alleviating traffic congestion and
improving traffic efficiency. Due to the delay of network transmission and failure of detectors …

When network is undergoing problems such as congestion, scan attack, DDoS attack, etc.,
measurements are much more important than usual. In this case, traffic characteristics …

Time series prediction problems are becoming increasingly high-dimensional in modern
applications, such as climatology and demand forecasting. For example, in the latter …

In this paper, we propose to leverage the emerging deep learning techniques for
spatiotemporal modeling and prediction in cellular networks, based on big system data …

Traffic prediction of wireless networks attracted many researchers and practitioners during
the past decades. However, wireless traffic frequently exhibits strong nonlinearities and …

Network measurement remains a missing piece in today's software packet processing
platforms. Sketches provide a promising building block for filling this void by monitoring …

Sparsity and missing data problems are very common in spatiotemporal traffic data collected
from various sensing systems. Making accurate imputation is critical to many applications in …

Compressive sensing (CS) is a novel sampling paradigm that samples signals in a much
more efficient way than the established Nyquist sampling theorem. CS has recently gained a …