Master of Science
With increase in the indoor usage of communication, there has been increase in the need for optimal design of mobile coverage for buildings with a lot of users. Cellular service companies had been pushing the limits with their macro-cell approach however, with the advent of 4G LTE and their higher frequency use, the penetration inside the buildings adds to their troubles. A Distributed Antenna System(DAS) extends the mobile coverage from the base station to distributed antennas through a network topology of coaxial cables and power splitters. Though the solution of DAS would solve the problem of mobile coverage but the total cost of ownership is a major obstacle. To reduce the total cost of ownership for enterprises, the need to optimize the design arises. This work researches the use of a popular computational method to optimize the design of in-building passive distributed antenna system with iterative improvements. The application of Particle Swarm Optimization(PSO) to the design problem reduces the cost of the deployment and also provides a quicker solution than brute force search. The model converges on an optimal design solution and stops execution at the stop criteria which has been empirically proven as appropriate. To make the design topology compatible with the particle swarm optimization, tree topology of passive DAS is converted to Prufer code. This allows the PSO algorithm to traverse through different solutions in the Euclidean space. The current optimization methods have only been applied to either optimizing the length of the cable or the equipment selection. This approach provides optimization for the complete deployment of passive DAS. Test results of the model show that we achieve the design way more quickly due to reduction in the complexity and the cost is reduced for the deployment due to optimal design.
Shah, Rohan A., "Economical Approach To Design Of Passive Distributed Antenna System" (2017). Theses and Dissertations. 2991.