A GA based network optimization tool for passive in-building distributed antenna systems

With an explosive increase in data traffic over recent years, it has become increasingly difficult to rely on outdoor base stations to support the traffic generated indoors mainly due to the penetration issue of wireless signals. Mobile operators have investigated different options to provide adequate capacity and good in-building coverage such as by deploying femtocells, Wi-Fi off-load or in-building distributed antenna systems (IB-DAS). A passive IB-DAS extends indoor coverage by connecting antennas to a base station through coaxial cables and passive components. This paper focuses on automated design of IB-DAS based on the real world requirements of a telecom service provider. A Genetic Algorithm (GA) is derived for this purpose, giving consideration to different factors, such as minimizing cabling and passive splitter costs, reducing power spillage and power deviation between the required and supplied power for antennas. The solution representation of the problem and the customized genetic operators to assist the evolution are described. The experimental results showing the effectiveness of the GA model on a number of different scenarios are also presented. The built model is incorporated into a software tool, which is being trialled by our industrial partner, delivering encouraging results, saving cost and design time.