Modelling and Optimisation of GSM and UMTS Radio Access Networks

The size and complexity of mobile communication networks have increased in the last years making network management a very complicated task. GSM/EDGE Radio Access Network (GERAN) systems are in a mature state now. Thus, non-optimal performance does not come from typical network start-up problems, but, more likely, from the mismatching between traffic, network or propagation models used for network planning, and their real counterparts. Such differences cause network congestion problems both in signalling and data channels. With the aim of maximising the financial benefits on their mature networks, operators do not solve anymore congestion problems by adding new radio resources, as they usually did. Alternatively, two main strategies can be adopted, a) a better assignment of radio resources through a re-planning approach, and/or b) the automatic configuration (optimisation, in a wide sense) of network parameters. Both techniques aim to adapt the network to the actual traffic and propagation conditions. Moreover, a new heterogenous scenario, where several services and Radio Access Technologies (RATs) coexist in the same area, is now common, causing new unbalanced traffic scenarios and congestion problems. In this thesis, several optimisation and modelling methods are proposed to solve congestion problems in data and signalling channels for single- and multi-RAT scenarios

A data-driven user steering algorithm for optimizing user experience in multi-tier LTE networks

Multi-tier cellular networks are a cost-effective solution for capacity enhancement in urban scenarios. In these networks, effective handover schemes are required to assign users to the most adequate layer. In this paper, a data-driven self-tuning algorithm for user steering is proposed to improve the overall Quality of Experience (QoE) in multi-carrier Long Term Evolution (TE) networks. Unlike classical approaches, user steering is achieved by changing Reference Signal Received Quality (RSRQ) based inter-frequency handover margins. To drive the tuning process, a novel indicator showing throughput changes in the vicinity of handovers is derived from connection traces. Method assessment is carried out in a dynamic system-level LTE simulator implementing a real multi-carrier scenario. Results show that the proposed algorithm significantly improves QoE figures obtained with a classical inter-frequency handover scheme based on Reference Signal Received Power (RSRP) measurements.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Un nuevo criterio basado en calidad de experiencia para el balance de carga en redes LTE

The increase in traffic and services in mobile networks has made network management a very complex task. This fact has motivated the development of many algorithms in a Self-Organized Network (SON) framework, such as Mobility Load Balancing (MLB). MLB achieves to solve congestion problems by sharing traffic demand among neighbour cells through the modification of handover parameters. However, it presents some limitations in current LTE networks. These limitations have a negative impact on end-user throughput and thus in Quality of Experience (QoE) perceived by end-users. In this paper, a sensitivity analysis of throughput according to Handover (HO) margins is presented and an alternative indicator for tuning HO margins is introduced, focusing on end-user throughput. The assessment is carried out in a trial LTE network. Results show that the proposed indicator improves network performance in terms of end-user throughput from that obtained with classical MLB algorithms.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Modelling Slice Performance in Radio Access Networks through Supervised Learning

In 5G systems, the Network Slicing (NS) feature allows to deploy several logical networks customized for specific verticals over a common physical infrastructure. To make the most of this feature, cellular operators need models reflecting performance at slice level for re-dimensioning the Radio Access Network (RAN). Throughput is often regarded as a key perfor- mance metric due its strong impact on users demanding enhanced mobility broadband services. In this work, we present the first comprehensive analysis tackling slice throughput estimation in the down link of RAN-sliced networks through Supervised Learning (SL), based on information collected in the operations support system. The considered SL algorithms include support vector regression, k-nearest neighbors, ensemble methods based on decision trees and neural networks. All these algorithms are tested in two NS scenarios with single-service and multi-service slices. To this end, synthetic datasets with performance indicators and connection traces are generated with a system-level simulator emulating the activity of a live cellular network. Results show that the best model (i.e., combination of SL algorithm and input features) to estimate slice throughput may vary depending on the NS scenario. In all cases, the best models have shown adequate accuracy(i.e., error below 10%).Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Limitaciones del equilibrio de carga para la mejora de la calidad de experiencia en redes LTE

Due to the huge increase in traffic and services in mobile networks, network management has changed its main focus from Quality of Service (QoS) to Quality of Experience (QoE). In addition, SON (Self Organizing Networks) techniques have been developed to automate network management, being load balancing a key use case. Load balancing aims to balance the traffic among adjacent cells in the hope that this balance will decrease the overall blocking ratio, thus increasing the total carried traffic in the network. Nevertheless, this technique may fail when QoE perspective is considered. In this work, a QoE network sensitivity analysis is performed in a LTE network with different services and traffic conditions. Different traffic sharing techniques are tested and limitations of classical cell load balancing algorithm are shown when a QoE performance perspective is considered.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

A QoE-driven traffic steering algorithm for LTE Networks

Due to the huge increase in traffic and services in mobile networks, network management has changed its main focus from Quality of Service (QoS) to a Quality of Experience (QoE) perspective. In addition, SON (Self Organizing Networks) techniques have been developed to automate network management, being load balancing a key use case. Load balancing aim is to balance the traffic among adjacent cells. This balance is expected to decrease the overall blocking ratio, thus increasing the total carried traffic in the network. Nevertheless, these techniques may fail when QoE perspective is considered. In this work, a novel QoE balancing algorithm is proposed to reach QoE equilibrium in a realistic LTE network with different services. The proposed balancing approach is tested and compared with classical techniques by means of simulations.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Coordination and load analysis of C-RAN in HetNets by graph-partitioning

In 5G systems, ultra-dense networks are a promising technique to cope strong increase of traffic data in mobile communications. In addition, the deployment of indoor small cells offloads the wireless system from macrocells at the cost of increasing network complexity. In this work, a method for capacity analysis of Centralized Radio Access Networks (C-RANs) comprising macrocells and small cells is proposed. Radio remote heads~(RRH) are grouped to a Base Band Unit~(BBU) pools using graph theory techniques. For this purpose, the impact of Inter-Cell Interference Coordination (ICIC) and Coordinated Multi-Point Transmission/Reception (CoMP) techniques on the network is assessed under different load levels and coordination restrictions. Assessment is carried out by using a radio planning tool that allows to characterize spectral efficiency and allocation of shared resources per cell over a realistic Long-Term Evolution (LTE) heterogeneous network. Results show that load and coordination conditions between cells are key to improve system capacity.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

A data-driven scheduler model for QoE assessment in a LTE radio network planning tool

The use of static system-level simulators is common practice for estimating the impact of re-planning actions in cellular networks. In this paper, a modification of a classical static Long Term Evolution (LTE) simulator is proposed to estimate the Quality of Experience (QoE) provided in each location on a per-service basis. The core of the simulator is the estimation of radio connection throughput on a location and service basis. For this purpose, a new analytical performance model for the packet scheduling process in a multi-service scenario is developed. Model parameters can easily be adjusted with information from radio connection traces available in the network management system. The simulation tool is validated with a large trace dataset taken from a live LTE network

A quality of experience evaluation method for an UAV first person view system

Unmanned Aerial Vehicles (UAV) communication systems are an increasingly widespread and emerging technology due to their flexibility, low cost and usability properties. Hence, the demand for Beyond Visual Line of Sight (BVLOS) cases that require large data transmission and low latency in cellular networks are increasingly. In this work, the assembly, integration and networking of a UAV quadrotor for First Person View (FPV) system connected by LTE is presented. Different configurations of the link between the UAV and the Ground Control Station (GCS) are proposed, such as connection by LTE cloud-based server, direct LTE connection and direct WiFi connection. With these configurations, experiments are carried out to characterise the network metrics that model this service according to the telemetry, control and video traffic. The main contribution is the definition of a closed mathematical expression provided to define the Quality of Experience (QoE) for FPV use cases considering the video quality in terms of Video Multimethod Assessment Fusion (VMAF), network latency and video resolution as inputs. This expression will be applied to lab experiments taking into account link performance, in which network changes based in packet loss and latency alterations will be introduced to measure the QoE of the UAV system.Campus de Excelencia Internacional Andalucía Tech

Traffic Steering in B5G Sliced Radio Access Networks.

In 5G and beyond wireless systems, Network Slicing (NS) feature will enable the coexistence of extremely different services by splitting the physical infrastructure into several logical slices tailored for a specific tenant or application. In sliced Radio Access Networks (RANs), an optimal traffic sharing among cells is key to guarantee Service Level Agreement (SLA) compliance while minimizing operation costs. The configuration of network functions leading to that optimal point may depend on the slice, claiming for slice-aware traffic steering strategies. This work presents the first data-driven algorithm for sliceaware traffic steering by tuning handover margins (a.k.a. mobility load balancing). The tuning process is driven by a novel indicator, derived from connection traces, showing the imbalance of SLA compliance among neighbor cells per slice. Performance assessment is carried out with a system-level simulator implementing a realistic sliced RAN offering services with different throughput, latency and reliability requirements. Results show that the proposed algorithm improves the overall SLA compliance by 9% in only 15 minutes of network activity compared to the case of not steering traffic, outperforming two legacy mobility load balancing approaches not driven by SLA