Harald Kallin

Neighbor Cell Relation List and Physical Cell Identity Self-Organization in LTE

Automation of radio network management is a key determinant to work reduction for wireless operators. By replacing time consuming and costly tasks with automatic mechanisms, operational expenditure can be reduced. In this paper we present a method for automatic configuration of locally-unique physical cell identities and neighbor cell relation lists in 3G long term evolution (LTE). This method makes use of mobile measurements to update the neighbor cell relation lists in the cells and to detect local cell identity conflicts, report the conflicts to the operation support systems (OSS) and resolve them. The performance of the approach is determined using simulations of realistically deployed macro networks. Conducted simulations illustrate the ability of the method to resolve local cell identity conflicts. In particular, the method is capable of both accommodating new cells and handling a worst case scenario where all cells are initiated with the same local cell identities and where neighbor cell relation lists are empty.

Neighbor cell relation list and measured cell identity management in LTE

Radio network management simplification concerns to some extent the removal, not the simplification, of tasks. In this paper we present an approach for automatic network management in 3G long term evolution (LTE), namely, methods for automatic configuration of locally-unique physical cell identities and neighbor cell relation lists. We show that these issues can be removed from the list of planning tasks and completely replaced by autonomous algorithms. These algorithms make use of mobile measurements to detect local cell identity conflicts, resolve them, and to update the neighbor cell relation lists in the cells. The performance of the approach is determined using simulations of realistically deployed macro networks. The simulations illustrate the ability of the algorithms to resolve local cell identity conflicts. In particular, the algorithms are capable of both accommodating new cells and handling a worst case scenario where all cells are initiated with the same local cell identities and where neighbor cell relation lists are empty. The contributions in this paper are meant to aid operators by allowing them to replace time consuming and costly tasks with automatic mechanisms, thus, reducing operational expenditure.

Energy efficiency in heterogeneous networks

An attractive approach to meet increasing traffic demands is to densify existing cellular networks with low power nodes. This creates a heterogeneous network. In this paper we analyse the impact of such a densification on the network energy consumption and the possibilities it offers to enhance the network energy efficiency. In a heterogeneous network, the user performance can be significantly improved. This performance increase leads to a shorter transmission time of most data packets, creating longer idle time in the network nodes. In this work, we introduce two node sleep modes operating on a fast and intermediate time scale respectively, in order to exploit short and longer idle periods of the nodes. Our results point out that the total energy consumption of the heterogeneous network featuring the node sleep modes can be maintained at a similar level as the one of the reference network, while the user performance remains superior. At very high traffic load we show that the heterogeneous network can even be more energy-efficient. This means that it is actually possible to increase end-user performance and decrease energy consumption at the same time.

Evaluations of LTE Automatic Neighbor Relations

In recent years, there has been a strong focus on network management simplicity under the device self-organizing networks (SON). A number of SON use cases and features have been and are discussed for 3G Long Term Evolution (LTE). The main SON feature in the first LTE release is methods for automatic configuration of neighbor cell relations - Automatic Neighbor Relations (ANR). In this paper, we describe the neighbor relations management and ANR, and evaluate ANR in a pre-launch, commercially deployed network cluster. The results indicate that ANR configures discovered and needed neighbor relations such that handover can be performed in combination with the neighbor relation establishment without dropping the connection.

Visualization of Self-Organizing Networks Operated by the ANR Algorithm

Cellular radio networks are continually growing in both node count and complexity. It therefore becomes more and more difficult to manage the networks and necessary to use time and cost effective automatic computer algorithms to organize the networks neighbor cell relations. Ericsson has developed such an algorithm, called automatic neighbor relations (ANR), which solves a part of this problem by automatically creating and updating neighbor cell relation (NCR) lists, based on measured network data. Network operators need to have an understanding of the algorithm and of its reliability and performance, which is not easily perceived. This paper presents a visualization tool that visualizes the performance of ANR and gives the user a possibility to control it via policies. The tool allows the operators to follow the evolution of the network and to find problems occurring over time. In addition, it also supports finding potential problems that can occur in the future. The tool was evaluated by a group of relevant domain users and the results from the evaluation were highly positive.