Telecom Big Data Based User Offloading Self-Optimisation in Heterogeneous Relay Cellular Systems

• Published in: International journal of distributed systems and technologies Vol. 8; no. 2; pp. 1 - 20
• Main Authors: Xu, Lexi, Luan, Yuting, Cheng, Xinzhou, Fan, Yifeng, Zhang, Haijun, Wang, Weidong, He, Anqi
• Format: Journal Article
• Language: English
• Published: Hershey IGI Global 01.04.2017
• Subjects: Algorithms; Analysis; Big Data; Clustering; Consumption; Customer services; Data management; Design; Failure; Load distribution (forces); Optimization; Personal information; Relay; Telecommunication systems; Telecommunications; Telecommunications industry; Traffic analysis; Traffic engineering; Canada; United Kingdom; China
• ISSN: 1947-3532; 1947-3540; 1947-3540
• DOI: 10.4018/IJDST.2017040103

This paper proposes a telecom big data based user offloading self-optimisation (TBDUOS) scheme. Its aim is to assist telecom operators to effectively balancing the load distribution with achieving good service performance and customer management in heterogeneous relay cellular systems. To achieve these objectives, in the cell-level offloaded traffic analysis stage, the optimal offloaded traffic is calculated to minimise the total blocking probability. In the user-level offloading stage, the user portrait is drawn and the K-MEANS algorithm is employed to manage the users clustering in the heavily loaded cell, and finally shifting users to assistant cells. Simulation results show the TBDUOS scheme can effectively reduce the handover failure and call dropping of specific users, especially voice/stream users, high consumption users, high level users. The TBDUOS scheme can also reduce the blocking probability.