Rethinking Cellular System Coverage Optimization: A Perspective of Pseudometric Structure of Antenna Azimuth Variable Space

TLDR: The pseudometric structure, as a fundamental topology on the azimuth solution space, provides a new lens to address other CCO issues concerning the antenna azimUTH variables and, thus, provokes rethinking on the coverage optimization of cellular system in general.

Abstract: This article, with the intent of maximizing the cellular system coverage ratio, reveals the pseudometric structure of the solution space for antenna azimuth variables. First, we study the solution space of azimuth variables with equivalent and neighboring characteristics. A generalized improvement to coverage and capacity optimization (CCO) approaches is proposed only in the light of the pseudometric structure of the solution space. Then, we model the optimization problem as an unconstrained one and propose a pseudometric-driven evolutionary algorithm to optimize the coverage ratio. Experiments are carried out both in the ideal and the practical urban scenarios. Simulation results show that the proposed algorithm edges out other baseline algorithms belonging to evolutionary computation and swarm intelligence with respect to the convergence speed and the final coverage result. Furthermore, the pseudometric structure, as a fundamental topology on the azimuth solution space, provides a new lens to address other CCO issues concerning the antenna azimuth variables and, thus, provokes rethinking on the coverage optimization of cellular system in general.