3GPP TR 36.902 PDF

Mobility Robustness Optimisation (MRO). ○. Mobility Load Balancing optimisation (MLB). ▫. Q4, additional use cases to TR ○. Support for SON based automatic RACH optimization is introduced in 3GPP Release 9 specifications TS. and TS and is discussed in TR [1] 3GPP “E-UTRA Radio Resource Control (RRC) Protocol specification ( Release [2] 3GPP TR V, “Evolved Universal Terrestrial Radio Access.

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This approach has been successfully applied to networks of limited scale but it is foreseen to be insufficient in the management of future complex networks. In order to maintain a massive multivendor and multi-RAN infrastructure in a cost-efficient manner, operators have to employ automated solutions to optimize the most difficult and time-consuming network operation procedures.

Introduction Modern radio access networks RAN are complex infrastructures consisting of several overlaying and cooperating networks such as next-generation high-speed-packet-access HSPA and long-term evolution LTE networks and as such are prone to the impacts of uncertainty on system management and stability.


An Approach for Network Outage Detection from Drive-Testing Databases

The presented method is designed to detect sleeping base stations, network outage, and change of the dominance areas in a cognitive 36.920 self-organizing manner. Motivation of classifying MDT measurement reports to periodical, handover, and outage categories is to detect areas where periodical reports start to become similar to the outage samples.

A data-mining framework for analyzing a cellular network drive testing database is described in 36.092 paper. Self-organizing network concept [1] has emerged in the last years, with the goal to foster automation and to reduce human involvement in management tasks. Classical network management is based on a design principle which requires knowledge of the state of all existing entities within the network at all times.

In addition, the method is 3gpp because it uses minimization of drive testing MDT functionality to gather the training and testing data.

Journal of Computer Networks and Communications

Moreover, these areas are associated with estimated dominance areas to detected sleeping base stations. It implies autonomous configuration, optimization, and healing actions which would result in a reduced operational burden and improve the experienced end user quality-of-service QoS. The essence of the method is to find similarities between periodical network measurements and previously known outage data.


The method is cognitive because it requires training data for the outage detection.

In the studied verification case, measurement classification results in an increase of the amount of samples which can be used for detection of performance degradations, 63.902 consequently, makes the outage detection faster and more reliable. One of the downsides of the SON concept is the necessity to gather larger amounts of operational data from user equipment UE. For this purpose, diffusion maps dimensionality reduction and nearest neighbor data classification methods are utilized.