Research on PCI Sequence Optimization in Large-scale Mobile Communication Networks based on Genetic Algorithm

Abstract

This study focuses on the importance of physical cell identifier (PCI) planning in large-scale mobile communication networks to reduce inter-cell conflicts, confusion and interference. Genetic algorithms are used to solve the PCI sequence optimization problem in wireless communication systems with the goal of reducing mobile reselection events caused by PCI conflicts, confusions and mode 3 interference. Iterative population selection, crossover and mutation operations are used to search and optimize PCI sequence configurations through a genetic optimization framework. Design PCI reallocation schemes for 2067 cells to minimize the sum of MR data points due to inter-cell conflicts, confusions and interference. Construct conflict matrix A, confusion matrix B, and interference matrix C. Determine inter-cell relationships and intensity metrics based on MR data to ensure that the total number of three MR data points is minimized under the new PCI plan. Conflict MR, confusion MR and mode 3 interference MR are optimized as decision variables, and the objective function is constructed to minimize the sum of interference MR, confusion MR and interference MR by adding them together, and solved by using the genetic optimization algorithm to ensure that the total number of MRs in 2067 cells is minimized. The optimal solution 55989824 is finally obtained through data processing, establishment of connectivity relationship network, integer planning model and genetic algorithm solution. This research result provides a strong support for optimizing network performance and improving user experience.