Investigating binary EAs for Passive In-Building Distributed Antenna Systems

A passive in-building distributed antenna system (IB-DAS) is often used to enhance indoor mobile data coverage by introducing indoor antennas inside buildings. Such systems are created to ensure that traffic generated indoors does not heavily depend on base stations installed outdoor, as penetration issues of wireless signals can affect the quality of connection. The focus of this paper is on the automation of IB-DAS design. Particularly, it provides an extensive analysis of the performance of four binary Evolutionary Algorithms (EAs) for this problem and shows that the two tested Estimation of Distribution Algorithms (EDAs) performs well on this problem. Furthermore, it investigates the effect of different genetic operators on the performance of the considered EAs. The practice outcome of this is to select the best algorithm among others to be implemented in a DAS network planning tool and to help our industrial partner reduce both the design time and deployment cost.