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

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

Lexi Xu (China Unicom Network Technology Research Institute, Beijing, China & Queen Mary University of London, London, United Kingdom), Yuting Luan (The Third Railway Survey and Design Institute Group Corporation, Shenyang, China), Xinzhou Cheng (China Unicom Network Technology Research Institute, Beijing, China), Yifeng Fan (Southeast University, Nanjing, China & Queen Mary University of London, London, United Kingdom), Haijun Zhang (University of Science and Technology Beijing, Beijing, China), Weidong Wang (Beijing University of Posts and Telecommunications, Beijing, China) and Anqi He (Queen Mary University of London, London, United Kingdom)
Copyright: © 2017 |Pages: 20
DOI: 10.4018/IJDST.2017040103
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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.
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In order to meet the explosive demands on cellular systems coverage by emerging smart terminals and mobile phones, the relay technique is employed (3GPP, 2010). The relay station (RS) can be deployed in wireless-hungry areas to extend the wireless coverage, whilst the base station (BS) focuses on the large coverage in LTE-Advanced heterogeneous relay cellular systems (Zheng, 2011). Due to the service diversity and the user mobility, cellular systems also face the challenge of uneven traffic distribution (Cao, 2015). Load balancing is widely used to deal with the uneven load distribution (SOCRATES, 2010; Cao, 2011).

Generally, load balancing can be implemented via two methods. The first method is based on channel borrowing. Under the non-full frequency reuse cellular systems (e.g., GSM), a heavily loaded cell borrows idle spectrum resources from neighbouring cells. Typical channel borrowing schemes includes simple borrowing scheme (Engel, 1973), hybrid assignment scheme (Zhang, 1989), channel borrowing without locking scheme (Jiang, 1994). However, the limitation is that these channel borrowing schemes only suit for cellular systems without employing full frequency reuse. Therefore, this method does not suit the LTE/LTE-Advanced cellular systems (Zheng, 2011; Han, 2012). The second method is via offloading traffic from the heavily loaded cell to less-loaded neighbouring cells.

Many traffic offloading schemes are designed from both academics and industry. In (Nasri, 2007), a heavily loaded cell chooses neighbouring cells, which have lower load, as assistant cells. Then, the heavily loaded cell adjusts handover offset (HOoff) to trigger handover between two cells. This work becomes the milestone of mobility load balancing (MLB). In (Zhang, 2010), cell state is categorized into ‘light load’, ‘high load’ and ‘normal load’. Then the traffic offloading is between the ‘high load’ and ‘light load’ cells, according to their load differences. Kwan (2010) studies the precise HOoff based MLB mechanism, in which a heavily loaded cell selects all less-loaded neighbouring cells as assistant cells, and then this heavily loaded cell gradually regulates HOoff with a fixed step-size to offload serving users. In (Yang, 2012; Yang, 2014), the authors design the cell load based utility function to adjust HOoff, in order to offload edge users efficiently. In (Wang, 2010), the neighbouring cell with the lowest load is chosen as the assistant cell in sequence, then the heavily loaded cell shifts users to RSs in assistant cells, thus balancing the traffic distribution evenly. In (Fan, 2011), the load balancing objective is to avoid a cell serving too many users via broadcasting and considering the number of users served by each cell's RS. In (Wu, 2005), the integrated cellular and Ad-hoc relay (iCAR) scheme is designed, in which the mobile ad-hoc relay station (ARS) is employed to relay the traffic from a heavily loaded cell to less-loaded neighbouring cells.

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