Page 51 - Proceedings of the 2018 ITU Kaleidoscope

SELF-HEALING AND RESILIENCE IN FUTURE 5G COGNITIVE AUTONOMOUS
NETWORKS

2
1
2
Janne Ali-Tolppa ; Szilard Kocsis ; Benedek Schultz ; Levente Bodrog ; Marton Kajo 3
2
1 Nokia Bell Labs, Munich, Germany
2 Nokia Bell Labs, Budapest, Hungary
3 Technische Universität München, Munich, Germany

Mobility Load Balancing (MLB) -- optimize the network
ABSTRACT function configuration so that specified objectives are
fulfilled. [2]
In the Self-Organizing Networks (SON) concept, self-healing
functions are used to detect, diagnose and correct degraded While self-optimization functions optimize a set of
states in the managed network functions or other resources. configuration parameters to improve the network
Such methods are increasingly important in future network performance from a given network state, the self-healing
deployments, since ultra-high reliability is one of the key functions focus on ensuring that the system can fulfill its
requirements for the future 5G mobile networks, e.g. in purpose and serve its customers even in case of unexpected
critical machine-type communication. In this paper, we changes or events that risk a degradation in the network
discuss the considerations for improving the resiliency of performance. In other words, their objective is to make the
future cognitive autonomous mobile networks. In particular, network more resilient [3, 4, 5].
we present an automated anomaly detection and diagnosis
function for SON self-healing based on multi-dimensional In this paper, we discuss the methods for improving
statistical methods, case-based reasoning and active resiliency in future 5G mobile networks and present a SON
learning techniques. Insights from both the human expert self-healing function applying automatic anomaly detection
and sophisticated machine learning methods are combined and diagnosis that enables detection of unexpected changes
in an iterative way. Additionally, we present how a more and events and allows fast reaction to them. Unlike in
holistic view on mobile network self-healing can improve its optimization, the self-healing functions can typically only
performance. monitor the symptoms of a fault and the causes are not a
priori known. Due to this and the less-constrained problem
Keywords – SON, cognitive network management, self- space, the self-healing process is often more complex than
healing, anomaly detection, machine learning the optimization control loops. This complexity is
accentuated by the distributed and heterogenous nature of
1 INTRODUCTION mobile networks. Finally, diverse fault states often occur
only in very rare cases, which makes it impossible to collect
Mobile networks are becoming ever more complex, while statistically meaningful data for each case. The lack of
the pressure for reducing the operational expenses and cost statistical samples makes the reliable root-cause analysis
per bit is increasing. Network management automation is a extremely difficult. Therefore, mobile network self-healing
key enabler for the increased dynamicity of the future 5G functions typically require more sophisticated machine
networks. Furthermore, the dynamic and complex future learning and augmented intelligence methods, as well as
networks require automation that can autonomously adapt to knowledge-sharing between domains. In our concept we’ve
changes in the context and in the environment, which applied a holistic view on the network to detect the diverse
necessitates the use of machine learning, analytics and problem states that may occur, as well as considered active
artificial intelligence. [1] and transfer learning methods.
Traditionally, the Self-Organizing Networks (SON) use The rest of the paper is structured as follows. In section 2,
cases are divided into three categories: self-configuration, we present the main principles of resilient systems and how
self-optimization and self-healing. Self-configuration refers they map to the future cognitive mobile networks. Section 3
to automated, “plug and play” deployment of new network focuses on SON self-healing as an enabler for resiliency and
functions, which are implemented by SON functions such as gives an overview of the self-healing process. In sections 4
the Automatic Neighbor Relationship (ANR) detection and and 5, we look more closely to the most important phases of
Physical Cell Identifier (PCI) allocation. Self-optimization the self-healing process, namely the anomaly detection and
functions -- for example Mobility Robustness Optimization diagnosis, respectively. Section 6 outlines how a more
(MRO), Capacity and Coverage Optimization (CCO) and holistic view on the complete network, over several

‎ 978-92-61-26921-0/CFP1868P-ART‎ – 35 – Kaleidoscope