Indoor Distributed Antenna System Planning with Optimized Antenna Power Using Genetic Algorithm

Abstract

Distributed Antenna System (DAS) promises an attractive solution to cope with the increasing demand for high data rate services inside building. DAS divides the indoor Base Station power among a group of spatially separated antennas that are connected to the BS. The power sharing makes the planning of (DAS) more challenging compared to other wireless networks. The previous To simplify the problem DAS planning approaches divided power equally among the antennas and focused on finding the optimal number and locations of antennas. This paper optimizes the transmitted power of the DAS antennas along with their location and shows that this will enhance the performance compared to the equal power structure. The paper formulates the DAS planning problem as an optimization problem that considers the power division among antennas. The optimization aims to minimize the deployment cost and the power leakage outside the building while the maximizing the average data rate and the indoor coverage. To deal with these conflicting objectives and with the non-convexity of the formulated function, the paper develops meta-heuristic genetic algorithm with novel mutation and crossover methods that are customized to this problem.