Search results for "self-organizing network"
showing 10 items of 10 documents
Reinforcement Learning Based Mobility Load Balancing with the Cell Individual Offset
2021
In this study, we focus on the cell individual offset (CIO) parameter in the handover process, which represents the willingness of a cell to admit the incoming handovers. However, it is challenging to tune the CIO parameter, as any poor implementation can lead to undesired outcomes, such as making the neighboring cells over-loaded while decreasing the traffic load of the cell. In this work, a reinforcement learning-based approach for parameter selection is introduced, since it is quite convenient for dynamically changing environments. In that regard, two different techniques, namely Q-learning and SARSA, are proposed, as they are known for their multi-objective optimization capabilities. Mo…
Anomaly Detection Algorithms for the Sleeping Cell Detection in LTE Networks
2015
The Sleeping Cell problem is a particular type of cell degradation in Long-Term Evolution (LTE) networks. In practice such cell outage leads to the lack of network service and sometimes it can be revealed only after multiple user complains by an operator. In this study a cell becomes sleeping because of a Random Access Channel (RACH) failure, which may happen due to software or hardware problems. For the detection of malfunctioning cells, we introduce a data mining based framework. In its core is the analysis of event sequences reported by a User Equipment (UE) to a serving Base Station (BS). The crucial element of the developed framework is an anomaly detection algorithm. We compare perfor…
Cell degradation detection based on an inter-cell approach
2017
Fault management is a crucial part of cellular network management systems. The status of the base stations is usually monitored by well-defined key performance indicators (KPIs). The approaches for cell degradation detection are based on either intra-cell or inter-cell analysis of the KPIs. In intra-cell analysis, KPI profiles are built based on their local history data whereas in inter-cell analysis, KPIs of one cell are compared with the corresponding KPIs of the other cells. In this work, we argue in favor of the inter-cell approach and apply a degradation detection method that is able to detect a sleeping cell that could be difficult to observe using traditional intra-cell methods. We d…
Detecting cellular network anomalies using the knowledge discovery process
2015
Analytical companies unanimously forecast the exponential growth of mobile traffic consumption over the next five years. The densification of a network structure with small cells is regarded as a key solution to meet growing capacity demands. The manual management of a multi-layer network is a very expensive, error prone, and sluggish process. Hence, the automation of the whole life cycle of network operation is highly anticipated. To this aim 3GPP introduces a self-management concept referred to as SON. It is envisioned that SON updates information concerning the latest network conditions through the MDT mecha- nism. MDT enables a network operator to collect radio and service quality measurem…
Towards proactive context-aware self-healing for 5G networks
2017
In this paper, we suggest a new research direction and a future vision for Self-Healing (SH) in Self-Organizing Networks (SONs). The problem we wish to solve is that traditional SH solutions may not be sufficient for the future needs of cellular network management because of their reactive nature, i.e., they start recovering after detecting already occurred faults instead of preparing for possible future faults in a pre-emptive manner. The detection delays are especially problematic with regard to the zero latency requirements of 5G networks. To address this problem, existing SONs need to be upgraded from reactive to proactive response. One of the dimensions in SH research is to employ more…
Design and evaluation of self-healing solutions for future wireless networks
2016
This doctoral dissertation is aimed at the creation of comprehensive and innovative Self-Organizing Networks (SON) solutions for the Network Management of future wireless networks. More specifically, the thesis focuses on the Self-Healing (SH) part of SON. Faults can appear at several functional areas of a complex cellular network. However, the most critical domain from a fault management viewpoint is the Radio Access Network (RAN). The fault management of network elements is not only difficult but also imposes high costs both in capital investment (CAPEX) and operational expenditures (OPEX). The SON concept has emerged with the goal to foster automation and to reduce human involvement in man…
Network of Concepts and Ideas
2010
We present the results of an experiment designed to investigate the way information is organized and stored in the human brain. In particular, we are using controlled stimuli to reverse engineer the networks of ideas and concepts in order to answer the following questions. (1) Are the networks of ideas and concepts in the human brain invoked by verbal and visual stimuli distinct from each other? The answer appears to be no for the network of ideas and inconclusive for the network of concepts. (2) What is the topology of these networks? Our experimental results show that both are small-world networks, with the network of ideas being random and the network of concepts scale-free.
Assessment of Deep Learning Methodology for Self-Organizing 5G Networks
2019
In this paper, we present an auto-encoder-based machine learning framework for self organizing networks (SON). Traditional machine learning approaches, for example, K Nearest Neighbor, lack the ability to be precisely predictive. Therefore, they can not be extended for sequential data in the true sense because they require a batch of data to be trained on. In this work, we explore artificial neural network-based approaches like the autoencoders (AE) and propose a framework. The proposed framework provides an advantage over traditional machine learning approaches in terms of accuracy and the capability to be extended with other methods. The paper provides an assessment of the application of …
Between Self-Organizing and Accelerating Networks: Untangling the multilevel of strategic networks
2010
This paper aims to detect the crucial determinants and processes that shape the emergence and evolution of interfirm network cognitive morphology. We pinpoint three relatively distinct but coexistent levels which define the fundamental structure of the network: the microsystemic (or the single firm) level; the mesosystemic (or the groups of firms within the network) level; and the macrosystemic (or the overarching network) level. Then, we integrate the complex system perspective (Morin, 1977; Prigogine and Stengers, 1984; Anderson, 1999) applied to networks with studies regarding theoretical models that elucidate network structuring and dynamics cultivated in the new “science of networks” (…
Advanced performance monitoring for self-healing cellular mobile networks
2015
This dissertation is devoted to development and validation of advanced per- formance monitoring system for existing and future cellular mobile networks. Knowledge mining techniques are employed for analysis of user specific logs, collected with Minimization of Drive Tests (MDT) functionality. Ever increas- ing quality requirements, expansion of the mobile networks and their extend- ing heterogeneity, call for effective automatic means of performance monitoring. Nowadays, network operation is mostly controlled manually through aggregated key performance indicators and statistical profiles. These methods are are not able to fully address the dynamism and complexity of modern mobile networks. Se…