Toward cell outage detection with composite hypothesis testing

This paper presents a novel cell outage detection algorithm based on statistics and performance metrics, which enables a base station (BS) to detect a failure/outage of a neighbor cell. The algorithm is a weighted combination of three hypothesis tests based on: 1) the distribution of the channel quality indicator (CQI), 2) the time correlation of the CQI differential, and 3) the registration request (RRQ) frequency. The weights of the combined test are functions of the predicted traffic load in neighboring cells, which is motivated by the fact that the reliability of a individual test depends on the load state. To detect the change-point in the CQI distribution, we use an efficient discriminant function related to the ""universal code"" proposed by [1], which can be shown to be asymptotically optimal in the sense of the modified Neyman-Pearson criterion. The simulation results indicate that the proposed algorithm can detect the outage problem in a real-time and reliable manner.