Leveraging Self Organizing Map for 5G Heterogeneous Network Deployment for Enhanced Performance

Fifth Generation mobile Wireless Network practically aims not only to connect everyone but everything as well, such as the IoT devices, self-driven cars etc. virtually on the same platform. An important characteristic of 5G network is the Heterogeneous Networks which include densely deployed femto/small cells under laid traditional macro cell network. This leads to the promising solution of high data rate, more capacity, lower latency etc. of the 5G communication. But small cell deployment is not an easy task. Incorrect deployment can lead to poor data quality and higher interference. Automated approach to small cell activation can resolve the issue and will lead to Rapid-to-Market of 5G services. The Kohonen's Self-Organizing Map (SOM) is an automatic data-analysis method. This unsupervised machine learning technique has been extensively applied to clustering problems and data exploration in industry. This paper aims to model a system where base station deployment is governed by SOM, supporting increasing tele density. The proposed system model serves as an effective solution for efficient small cell deployment leading to enhanced Area Spectral Efficiency targeting for Maximum Coverage and essential traffic offloading from Macro cell network.