Szymon Stefanski

Load Balancing in Downlink LTE Self-Optimizing Networks

In this paper we present system level simulation results of a self-optimizing load balancing algorithm in a long-term-evolution (LTE) mobile communication system. Based on previous work, we evaluate the network performance of this algorithm that requires the load of a cell as input and controls the handover parameters. We compare the results for different simulation setups: for a basic, regular network setup, a non-regular grid with different cell sizes and also for a realistic scenario based on measurements and realistic traffic setup.

Coordinating Handover Parameter Optimization and Load Balancing in LTE Self-Optimizing Networks

In this paper we present simulation results of a self-optimizing network in a long-term-evolution (LTE) mobile communication system that uses two optimizing algorithms at the same time: load balancing and handover parameter optimization. Based on previous work, we extend the optimization by a combined use case. We present the interactions of the two SON algorithms and show an example of a coordination system. The coordination system for self optimization observes system performance and controls the SON algorithms. As both SON algorithms deal with the handover decision itself, not only interactions, but also conflicts in the observation and control of the system are to be expected and are observed. The example of a coordination system here is not the optimal solution covering all aspects, but rather a working solution that shows equal performance to the individual algorithms or in the best case combining the strengths of the algorithms and achieving even better performance; although as localized gain, in time and area.

Weighted Performance Based Handover Parameter Optimization in LTE

Handover parameter optimization is a selfoptimizing network (SON) use case that promises significant performance improvement of the radio network. The basic idea is to adapt the handover control parameters, hysteresis and time-to-trigger, to the individual cell situation, in terms of e.g. the building density, cell environment and degree of user mobility. The aim is to reduce the number of handover failures, ping-pong handovers and radio link failures. We propose an handover parameter optimization algorithm that tunes the hysteresis and time-to-trigger in iterative steps and show the system performance improvement with it in both a realistic and a hexagonal simulation scenario.

Efficient uplink modeling for dynamic system-level simulations of cellular and mobile networks

A novel theoretical framework for uplink simulations is proposed. It allows investigations which have to cover a very long (real-) time and which at the same time require a certain level of accuracy in terms of radio resource management, quality of service, and mobility. This is of particular importance for simulations of self-organizing networks. For this purpose, conventional system level simulators are not suitable due to slow simulation speeds far beyond real-time. Simpler, snapshot-based tools are lacking the aforementioned accuracy. The runtime improvements are achieved by deriving abstract theoretical models for the MAC layer behavior. The focus in this work is long term evolution, and the most important uplink effects such as fluctuating interference, power control, power limitation, adaptive transmission bandwidth, and control channel limitations are considered. Limitations of the abstract models will be discussed as well. Exemplary results are given at the end to demonstrate the capability of the derived framework.