Detecting and reducing interference in 3G and beyond wireless access networks

As wireless access networks evolve, addressing the growing subscribers demand, their complexity has been increasing too. To manage it, Mobile Network Operator (MNO)s rely more often on automatic methods, such as network planning, optimization and maintenance. In this regard, this study focuses on the development of a intra-Radio Access Technology (RAT) coverage optimization and interference reduction algorithm, applying Self-Organizing Networks (SON) concepts. A Genetic Algorithm (GA) was used to optimize multiple antenna tilt parameters, based on Drive Test (DT) measurements and network configuration. This study was applied to the 3
^rd
Generation (3G) technology, nonetheless, it can be adapted to other RAT. It was tested, with both single and multiple cells optimization, resulting in a Radio Frequency (RF) condition improvement. In an urban scenario, the simultaneous optimization of several cells, resulted in a 50
^th
percentile Received Signal Code Power (RSCP) and Energy per Chip on Spectral Noise Density (Ec/No) distributions improvement of 7 dB and 3 dB, respectively. Moreover, the joint optimization of the Electrical Downtilt (EDT) and Mechanical Downtilt (MDT) proved insignificant advantages over just the EDT optimization.