COMPARATIVE STUDY OF CLUSTERING TECHNIQUES TO ACHIEVE IMPROVED CAPACITY IN DENSE NETWORKS

Abstract

The objective ofthis project is to achieve improved capacity in dense networks. This report explores different techniques used for improving capacity in dense networks. We are using more than one Algorithm for comparing them to achieve capacity in terms of more users. The outputs of both the techniques are shown through simulations, by comparing them. Matlab Tool is used for Implementation different Algorithms. Research carried out on Long Term Evolution (LTE) and LTE-Advanced (LTE-A) networks, mainly focuses on the method to achieve improved network capacity and decrease the interference. As in the current time WSN can be the mainstream technology for wireless networks but in future the WSN will be replaced by HetNet. HetNet is the future of technology which guarantee user seamless availability of network with maximum bandwidth with minimum interference. In the current networks to improve quality, coverage and service, small cells offers an economically interesting way to achieve the above mentioned goals. Currently for improved indoor coverage to facilitate indoor users, femto cell usage also aid for consumers in cost reduction as a result of capacity offload. Femtocell can be a successful choice to manage and carry out a large part of the cellular network traffic from the Macro Base Station to Small cell Base stations. The purpose ofthis report is to provide an overview of one ofthe crucial challenges that emerge from the deployment ofHetNets i.e. Capacity management and highlight its importance. Subsequently, we present a comparison between two clustering techniques to increase network capacity by minimizing interference and adding small cells in network.