Matías Toril

Optimization of a Fuzzy Logic Controller for Handover-Based Load Balancing

In Self-Organizing Networks (SON), load balancing has been recognized as an effective means to increase network performance. In cellular networks, cell load balancing can be achieved by tuning handover parameters, for which a Fuzzy Logic Controller (FLC) usually provides good performance and usability. Operator experience can be used to define the behavior of the FLCs. However, such a knowledge is not always available and hence optimization techniques must be applied in the controller design. In this work, a fuzzy

Learning of model parameters for fault diagnosis in wireless networks

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Automatic Replanning of Tracking Areas in Cellular Networks

-Learning algorithm is proposed to find the optimal set of fuzzy rules in an FLC for traffic balancing in GSM-EDGE Radio Access Network (GERAN). Load balancing is performed by modifying handover margins. Simulation results show that the optimized FLC provides a significant reduction in call blocking.

Optimization of Handover Parameters for Traffic Sharing in GERAN

Self-management is essential for Beyond 3G (B3G) systems, where the existence of multiple access technologies (GSM, GPRS, UMTS, WLAN, etc.) will complicate network operation. Diagnosis, that is, fault identification, is the most difficult task in automatic fault management. This paper presents a probabilistic system for auto-diagnosis in the radio access part of wireless networks, which comprises a model and a method. The parameters of the model are thresholds for the discretization of Key Performance Indicators (KPIs) and probabilities. In this paper, some techniques are proposed for the automatic learning of those model parameters. In order to support the theoretical concepts, experimental results are examined, based on data from a live network. It has been proven that calculating parameters from network statistics, instead of being defined by diagnosis experts, highly increases the performance of the diagnosis system. In addition, the proposed techniques enhance the results obtained with continuous diagnosis models previously exposed in the literature.

Traffic steering by self-tuning controllers in enterprise LTE femtocells

In future cellular networks, tracking areas (TAs) that are defined for location management purposes will be frequently updated to cope with changes in user trends. In this paper, an automatic method for defining when and how to change an existing TA plan to minimize network signaling is presented. The method first detects periods of similar user trends that could share the same TA plan. For this purpose, a series of graphs showing the evolution of user mobility and traffic is built from handover and paging statistics in the network management system (NMS). Then, a clustering algorithm is used to identify periods of similar user trends based on graph correlation. Thus, a TA replan is performed at the end of each period. To build the new TA plan, the TA replanning problem is formulated as a classical graph partitioning problem, which is then solved by a sophisticated graph partitioning algorithm combining multilevel and evolutionary techniques. Assessment is based on graphs taken from a live cellular network. Results show that the proposed method can significantly decrease the total number of location update (LU) and paging requests in the network by only changing the TA plan twice a week.

Design of a Computationally Efficient Dynamic System-Level Simulator for Enterprise LTE Femtocell Scenarios

Cellular network traffic is unevenly distributed both in time and space, which greatly complicates network dimensioning. As a result, some cells in the network are permanently congested, while others are underutilized. In a previous paper, the authors showed that this problem can be effectively solved in GSM/EDGE Radio Access Networks (GERAN) by modifying handover boundaries. However, several drawbacks prevent operators from fully exploiting the potential of this technique. This paper investigates the limitations of current traffic-sharing approaches with tight frequency reuses in GERAN. To deal with such limitations, an algorithm is proposed to jointly optimize handover margins and signal-level constraints based on network statistics for traffic sharing in GERAN. A complementary algorithm is proposed to adjust cell (re)selection offsets to minimize the number of handovers. Simulation results show that the proposed method achieves a significant reduction in call blocking without excessive call quality impairment or increase of network signaling load when compared to the current approaches. More traffic can thus be handled without the need for any hardware upgrades, providing a cost-effective means to increase network capacity.

Impact of antenna downtilting on network performance in GERAN systems

Femtocells have been suggested as a promising solution for the provision of indoor coverage and capacity. This article investigates the problem of re-distributing traffic demand between long-term evolution (LTE) femtocells with open access in an enterprise scenario. Several traffic sharing algorithms based on automatic tuning of femtocell parameters are considered. The proposed algorithms are implemented by fuzzy logic controllers. Performance assessment is carried out in a dynamic system-level simulator. Results show that localized congestion problems in these scenarios can be solved without impairing connection quality by jointly tuning handover margins and cell transmit power.

Analysis of Throughput Performance Statistics for Benchmarking LTE Networks

In the context of Long-Term Evolution (LTE), the next generation mobile telecommunication network, femtocells are low-power base stations that efficiently provide coverage and capacity indoors. This paper presents a computationally efficient dynamic system-level LTE simulator for enterprise femtocell scenarios. The simulator includes specific mobility and traffic and propagation models for indoor environments. A physical layer abstraction is performed to predict link-layer performance with low computational cost. At link layer, two important functions are included to increase network capacity: Link Adaptation and Dynamic Scheduling. At network layer, other Radio Resource Management functionalities, such as Admission Control and Mobility Management, are also included. The resulting tool can be used to test and validate optimization algorithms in the context of Self-Organizing Networks (SON).

Adjustment of a Fuzzy Logic Controller for IS-HO parameters in a heterogeneous scenario

Antenna downtilting is often mentioned in the literature as a powerful method for improving network performance in cellular systems. The antenna elevation angle on a number of GSM EDGE radio access network (GERAN) cells has been modified to quantify the impact of this method in a real network. In addition, a novel approach to prioritizing the cells to be tilted, which uses network statistics only, has been tested. Trial results indicate that downtilting can improve certain performance aspects, especially those related to signal quality, but not all of them on every cell.

Optimization of the Assignment of Base Stations to Base Station Controllers in GERAN

In this letter, a comprehensive analysis of throughput performance statistics in a live LTE network is presented. The analysis shows the relationship between several widely accepted throughput performance indicators, i.e., the user throughput, the cell throughput, and the radio link throughput, and how these indicators are related to signal quality statistics. The analysis is performed on a per-cell and per-connection basis. For this purpose, throughput and signal quality statistics are collected from network performance counters and call traces in cells of a live LTE system. Results show that all throughput measures are strongly affected by chatty applications dominating current LTE networks due to the last transmission time interval transmissions and the outer loop link adaptation mechanism.