论文部分内容阅读
Most current Global System for Mobile Communications (GSM) frequency planning methods evaluate the interference and assign frequencies based on measurement reports.Assigning the same or adjacent frequencies to cells close to each other will introduce co-channel and adjacent channel interference which will reduce network performance.Traditionally,man power is used to check and allocate new frequencies which is time consuming and the accuracy is not satisfactory.This paper presents an intelligent analysis method for optimization of co-channel and adjacent channel interference by exploiting cell configuration information.The method defines an interference evaluation model by analyzing various factors such as the base station layer,the azimuth ward relationship,and the cell neighborhood relationships.The interference for each frequency is evaluated and the problem frequencies are optimized.This method is verified by a large number of actual datasets from an in-service GSM network.The results show this method has better intelligence,accuracy,timeliness,and visualization than traditional methods.
Most current Global System for Mobile Communications (GSM) frequency planning methods evaluate the interference and assign frequencies based on measurement reports. Assigning the same or adjacent frequencies to cells close to each other will introduce co-channel and adjacent channel interference which will reduce network performance .Traditionally, man power is used to check and allocate new frequencies which is time consuming and the accuracy is not satisfactory. This paper presents an intelligent analysis method for optimization of co-channel and adjacent channel interference by exploiting cell configuration information. The method defines. an interference evaluation model by analyzing various factors such as the base station layer, the azimuth ward relationship, and the cell neighborhood relationships. interference for each frequency is evaluated and the problem frequencies are optimized. This method is verified by a large number of actual datasets from an in-service GSM network.The resul ts show this method has better intelligence, accuracy, timeliness, and visualization than traditional methods.