Clustering Nature of Base Station and Traffic Demand in Cellular Networks and the Corresponding Caching and Multicast Strategies

Clustering Nature of Base Station and Traffic Demand in Cellular Networks and the Corresponding Caching and Multicast Strategies

Yifan Zhou (1, 2)

1 SCEE - Signal, Communication et Electronique Embarquée
2 IETR - Institut d'Électronique et des Technologies du numéRique

Traditional cellular networks have evolved from the first generation of analog communications to the current fourth generation of digital communications where iteratively enhanced physical layer technologies have greatly increased the network capacity. According to Shannon’s theory, the technical gains brought by physical layer has gradually become saturated, which cannot match the rapid increase of user traffic demand in current mobile internet era, thus calls for another path of evolution, i.e., digging into the traffic demand of mobile users. In recent years, the academic communities have begun to use the real data to analyze the infrastructure deployment of wireless networks and the traffic demand of mobile users, in order to make benefits from the underlying statistical patterns. At the same time, along with the recent rise of machine learning technics, data-driven service is considered as the next economic growth point. Thus the industry is putting more and more attention on data accumulation and knowledge mining related services and telecommunication operators are coming to realize the increasing importance of the recorded data from their own networks. Therefore, the real-data-driven technology advancement is considered as a promising direction for the next evolution of cellular networks.

Traditional cellular networks have evolved from the first generation of analog communications to the current fourth generation of digital communications where iteratively enhanced physical layer technologies have greatly increased the network capacity. According to Shannon’s theory, the technical gains brought by physical layer has gradually become saturated, which cannot match the rapid increase of user traffic demand in current mobile internet era, thus calls for another path of evolution, i.e., digging into the traffic demand of mobile users. In recent years, the academic communities have begun to use the real data to analyze the infrastructure deployment of wireless networks and the traffic demand of mobile users, in order to make benefits from the underlying statistical patterns. At the same time, along with the recent rise of machine learning technics, data-driven service is considered as the next economic growth point. Thus the industry is putting more and more attention on data accumulation and knowledge mining related services and telecommunication operators are coming to realize the increasing importance of the recorded data from their own networks. Therefore, the real-data-driven technology advancement is considered as a promising direction for the next evolution of cellular networks.

Mots clés: clustering; base stations; caching; multicast

Mots clés: clustering; base stations; caching; multicast

Domaines: Traitement du signal et de l'image [eess.SP]

Yifan Zhou. Clustering Nature of Base Station and Traffic Demand in Cellular Networks and the Corresponding Caching and Multicast Strategies. Signal and Image processing. Centrale Supélec, 2018. English. ⟨NNT : ⟩. ⟨tel-02434146⟩