MLICOM

Along with the fast developing of mobile communications technologies, the amount of high quality wireless services is required and increasing exponentially. According to the prediction of Cisco VNI Mobile Forecast 2016, Global mobile data traffic will increase nearly eightfold between 2015 and 2020, and mobile network connection speeds will increase more than threefold by 2020. Hence, there are still big gap between the future requirements and current communications technologies, even using 4G/5G. How to integrate the limited wireless resources with some intelligent algorithms/schemes and boost potential benefits are the interests of the conference. As an emerging discipline, machine learning is a subfield of computer science that evolved from the study of pattern recognition and computational learning theory in artificial intelligence, and explores the study and construction of algorithms that can learn from and make predictions on complicated scenarios. In communication systems, the previous/current radio situations and communication paradigms should be well considered to obtain a high quality of service (QoS), such us available spectrum, limited energy, antenna configurations, and heterogeneous properties. Machine learning algorithms facilitate complicated scenarios analysis and prediction, and thus to make an optimal actions in OSI seven layers.