Partitioning the wireless environment for determining radio coverage and traffic distribution with user feedback

To achieve high data rates and seamless coverage, radio access networks continue to increase in complexity, and the expenditure on operational tasks continues to rise to unprecedented levels. The development of Long Term Evolution (LTE) with Self-organizing network (SON) functions is being considered as an effective way to tackle these challenges. The paper describes an approach to model the coverage areas so that resource allocation algorithms can benefit from traffic distribution and coverage information. The main problem considered in this paper is the partitioning of the wireless environment into regions that allow for accurate modelling of the propagation environment and prediction of the traffic distribution. The analysis is based on models constructed from historical data and monitoring of the received signal strengths from the mobile stations (MSs). The mechanism is based on the similarity of perceived signals from MSs. The performance is evaluated using data generated from a network planning tool for a real environment.