Abstract
Recent years have seen the proliferation of different techniques for outdoor and, especially, indoor positioning. Still being a field in development, localization is expected to be fully pervasive in the next few years. Although the development of such techniques is driven by the commercialization of location-based services (e.g., navigation), its application to support cellular management is considered to be a key approach for improving its resilience and performance. When different approaches have been defined for integrating location information into the failure management activities, they commonly ignore the increase in the dimensionality of the data as well as their integration into the complete flow of networks failure management. Taking this into account, the present work proposes a complete integrated approach for location-aware failure management, covering the gathering of network and positioning data, the generation of metrics, the reduction in the dimensionality of such data, and the application of inference mechanisms. The proposed scheme is then evaluated by system-level simulation in ultra-dense scenarios, showing the capabilities of the approach to increase the reliability of the supported diagnosis process as well as reducing its computational cost.
Highlights
IntroductionMechanisms that are applied to implement performance analysis and failure management activities in cellular networks have been typically based on the analysis of alarms, radio measurements, and network performance indicators (e.g., throughput) [1]
Until recently, mechanisms that are applied to implement performance analysis and failure management activities in cellular networks have been typically based on the analysis of alarms, radio measurements, and network performance indicators [1].this approach has become very limited due to the complexity of the new mobile scenarios and, in particular, for ultra-dense cellular environments
These systems typically rely on geolocated User Equipment (UE) traces obtained via drive tests, Global Navigation Satellite System (GNSS)-based third-party apps measurements, as well as UE traces provided by the network itself, typically known as Minimization of Drive Tests (MDT) or UE network-based traces [9]
Summary
Mechanisms that are applied to implement performance analysis and failure management activities in cellular networks have been typically based on the analysis of alarms, radio measurements, and network performance indicators (e.g., throughput) [1]. This approach has become very limited due to the complexity of the new mobile scenarios and, in particular, for ultra-dense cellular environments. Different works and tools have been developed for location-aware failure management mechanisms These approaches are only typically employed for very specific applications that are not integrated into a general failure management architecture and in macrocell scenarios. These systems typically rely on geolocated UE traces obtained via drive tests, Global Navigation Satellite System (GNSS)-based third-party apps measurements, as well as UE traces provided by the network itself (and typically positioned by cellular signals localization techniques), typically known as Minimization of Drive Tests (MDT) or UE network-based traces [9]
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