Optimization of Transmitter Azimuths for a 4th Generation Mobile Telecommunications Network Using Artificial Intelligence Techniques and Wave Propagation Simulation with Atoll Software

The orientation of transmitters (azimuths) plays a crucial role in determining the quality of a mobile network. As a result, selecting these angles accurately is of paramount importance. However, this process is challenging because the supervisor must establish the azimuths for numerous sites across a given area. While wave propagation simulation software can aid in this task, it often involves running simulations for hundreds of different scenarios, which can be time-consuming and complex. In this work, we propose an azimuth optimization method that automates the generation of possible transmitter orientation scenarios and evaluates the quality of each scenario using wave propagation simulations. This method consists of two complementary parts: the first is a genetic algorithm, an artificial intelligence tool, which generates solutions based on the results of previous solutions; this choice is justified by its effectiveness in the field of optimization. The second part involves evaluating the solutions through simulations with ATOLL software. Although these two parts operate independently, they communicate through intermediate files. Our method was evaluated in an area with four 4 G sites, each equipped with three transmitters spaced 120° apart. The azimuths optimized by our method resulted in a 3.8 % improvement in network coverage, increasing it from 93.2 % to 97 %. This significant enhancement demonstrates the effectiveness of the proposed method