Loading

Base Station Allocation using SVM for Load Balancing in Heterogeneous Mobile Cellular Network
Tincy Thomas1, Aby Abahai T2

1Tincy Thomas, Department of Computer Science and Engineering, Mar Athanasius College of Engineering Kothamangalam, APJ Abdul Kalam Technological University, (Kerala), India.
2Aby Abahai T, Department of Computer Science and Engineering, Mar Athanasius College of Engineering Kothamangalam (Kerala), India.
Manuscript received on 07 March 2019 | Revised Manuscript received on 20 March 2019 | Manuscript published on 30 March 2019 | PP: 864-869 | Volume-8 Issue-5, March 2019 | Retrieval Number: E3038038519/19©BEIESP
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: The dramatic increase in mobile network subscribers demands high data traffic. This huge data demand is becoming one of the challenges for mobile operators. In cellular communication network, the whole coverage area is divided into cells. The network traffic is not uniformly distributed across base stations in mobile cellular network. This leads to difficulties in network management and load balancing issues arise. To address these challenges small base stations are deployed in network to cope with the explosion in mobile traffic. Cells having large coverage area and transmission power are called macro cells. Small cells contain base stations with small transmission range. If more user equipment are connected to macro cell, it may become heavily loaded and they cannot serve all devices connected to it. In such cases the traffic can be shifted to small cells that are lightly loaded. Support vector machines are used for determining the offloading process. Based on the historic data and the movement of users, resource allocation can be estimated. Base stations are allocated to the users based on several factors like load value, resource utilization, traffic type, cell tower position etc. The main objective of the paper is to balance cellular network traffic by optimizing resource utilization and increase the network throughput.
Keyword: Quality of Service (Qos), User Equipment (UE), Self-Organizing Network (SON), Support Vector Machine (SVM).
Scope of the Article: High Speed Networks