As a key technique for enabling artificial intelligence, machine learning (ML) is capable of
solving complex problems without explicit programming. Motivated by its successful …

In this paper, a survey of the literature of the past 15 years involving machine learning (ML)
algorithms applied to self-organizing cellular networks is performed. In order for future …

In this paper, a novel framework is proposed to enable a predictive deployment of
unmanned aerial vehicles (UAVs) as temporary base stations (BSs) to complement ground …

Predictive models for human mobility have important applications in many fields including
traffic control, ubiquitous computing, and contextual advertisement. The predictive …

Wireless data traffic is growing unprecedentedly and it may impede network performance by
consuming an ever-greater amount of bandwidth. With the advancement in technology there …

Future 6G wireless communication systems are expected to feature intelligence and
automation. Knowledge-defined networking (KDN) is an evolutionary step toward …

The context of this study examines the requirements of Future Intelligent Networks (FIN),
solutions, and current research directions through a survey technique. The background of …

The method to estimate the predictability of human mobility was proposed in Song et
al.(2010), which is extensively followed in exploring the predictability of disparate time …

WiFi fingerprint-based indoor localization has been a popular research topic recently. In this
work, we propose two novel deep learning-based models, the convolutional mixture density …

A major limiting factor for prediction algorithms is the forecast of new or never before-visited
locations. Conventional personal models utterly relying on personal location data perform …