Lutz Ewe

Base station distributed handover optimization in LTE self-organizing networks

Methods of self-organizing networks (SON) are an essential part of the latest 3rd Generation Partnership Project (3GPP) technology Long Term Evolution (LTE). Among the different identified use cases in standard self-organized handover optimization plays an important role concerning the overall radio network performance. In this paper, we present results as obtained from simulations on a handover optimization procedure performed distributed to base stations of the radio network. Based on a simulation scenario which is characterized by heterogeneous radio conditions between neighboring cells we show the procedures capability of an efficient and stable modification from initial suboptimal parameter settings towards optimum values of the handover key performance indicators (KPIs).

ICIC in DL and UL with network distributed and self-organized resource assignment algorithms in LTE

Inter-cell Interference coordination (ICIC) has gained much interest in the 3rd Generation Partnership Projects (3GPPs) Long Term Evolution (LTE) standardization of a new air interface. Due to the new physical layer, interference can now be predicted and avoided on a frequency basis. Such schemes are based on cell wise usage restrictions or resource preferences. After explaining the general degrees of freedom, we present an “inverted” reuse scheme for downlink and uplink and explain its advantages. This is supported by 3GPP-compliant system simulations. The question of assignment of restrictions or preferences naturally leads to a need for self-organization. For that, the concept of semi-static ICIC based on a request-grant mechanism applicable to load balancing is explained. For the static ICIC case with frequency planning, a novel and fully distributed algorithm provides optimized assignment of resource restrictions to the cells in a self-organizing way. It is capable of resolving sub-optimal aspects and comprises methods to detect and prevent possible system instabilities. The algorithms presented lead to an integrated ICIC-self-organizing network (SON) concept that can be realized in a multi-cell network solution.

Evaluation of the Automatic Neighbor Relation Function in a Dense Urban Scenario

Self-organizing network (SON) capabilities are an important feature of coming LTE networks. An automated configuration of neighbor cell lists, the so-called Automatic Neighbor Relation (ANR) function, is one of the first SON features being deployed in commercial networks. In this paper, we present simulation results of the convergence time of the ANR function in a dense urban scenario. We model the corresponding cell identifier measurements and the X2 setup in a detailed way. Our results show that even for sparse user densities, the network achieves good handover performance within the first two hours. We further propose a blacklist method which can significantly reduce measurement overhead in the mobile terminals during the network auto-configuration period.

Autonomous neighbor relation detection and handover optimization in LTE

Handovers require serving cells to have knowledge about the existence of neighboring cells. This information is stored in neighbor relation tables (NRTs), which can be automatically generated during a procedure called automatic neighbor relation (ANR) by leveraging measurements carried out by terminals. We show, using simulations, how fast the NRT converges with respect to the number of terminals and their speeds, as well as how incomplete NRTs influence the handover drop rate. By means of a field trial, we demonstrate that ANR works successfully in a real-life environment. In addition, we investigate solutions for problematic handover scenarios and self-optimization of relevant handover parameters based on decentralized approaches. We show that some handover parameters have more impact on network performance than others. Two promising self-optimization methods are discussed, based on either a cost function or a genetic programming technique which searches for a suitable algorithm that determines the parameters.