Radio network planning and optimisation for WCDMA

The present thesis introduces the radio network planning process and optimisation for WCDMA (FDD mode), as defined by 3GPP. This thesis consists of three parts: modelling and tools for radio network planning, process for pre-operational network control and optimisation for the operational network. General challenges to face in 3G network control are based on the fact that many issues are interconnected and should be simultaneously considered, such as Planning means not only to meet current status and demands, but the solution should also comply with the future requirements by providing an acceptable development path. Traffic modelling is not only the question about the total amount of traffic growth, but also the question about the future service distribution and performance demands. All CDMA systems have a relation between capacity and coverage. Consequently, the network planning itself is not only based on propagation estimation but also on the interference situation in the network. Ideally, site selection consideration will be done based on the network analysis with planned load and traffic/service portfolio, taking possible co-siting constraints into account. Provision of multiple services and seamless management of at least two multiple access systems require rapid evolution of the management tools and processes. The network performance in terms of capacity, quality, and implementation and operational costs forms a multidimensional space. Operators' task will be to convert the business strategy to an operating point in the performance space in a cost efficient manner. The contribution of this thesis in terms of modelling and tools is as follows: Improvement of the accuracy of radio link budget by introducing power control headroom (also called fast fading margin). Improvement of loading equation by introducing a transmit power increase term. Development of theory and modelling for a planning tool capable of multi-service and multi-carrier interference, capacity and coverage analysis. Development and implementation an interface taking into account the true traffic distribution (not uniform) and terminal speed. In the area of pre-operational planning process the contribution of this thesis is as follows: Development of dimensioning methodology for multi-service network site density estimation, utilising the modelling of power control headroom, transmit power increase, soft handover and Eb/N0. Development of radio network planning process for multi-service environment including capacity and coverage evaluation for a given traffic mixture, quality and area requirements. Analysis of means to improve radio network performance with Mast Head Amplifier (MHA), diversity reception, sectorisation and proper antenna selection. In the area of optimisation of the operational network the contribution of this thesis is as follows: Definition for optimisation target in the case of 3G. The optimisation will be capacity-quality trade-off management instead of plain quality improvement process. Introduction of Self Organizing Map (SOM) in the analysis of cellular networks. Analysis of the applicability of SOM in WCDMA cellular network optimisation. Introduction of SOM based applications to support network capacity-quality trade-off management. It is worth noting that process and methods described in this work are not limited to 3G systems with WCDMA radio access technology, but they are applicable to other CDMA standards as well.reviewe

Computer usage and internet access on agricultural and horticultural farms in Finland

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Neural Analysis of Mobile Radio Access Network

The Self-Organizing Map (SOM) is an efficient tool for visualization and clustering of multidimensional data. It transforms the input vectors on two-dimensional grid of prototype vectors and orders them. The ordered prototype vectors are easier to visualize and explore than the original data. Mobile networks produce a huge amount of spatiotemporal data. The data consists of parameters of base stations (BS) and quality information of calls. There are two alternatives in starting the data analysis. We can build either a general one-cell-model trained using state vectors from all cells, or a model of the network using state vectors with parameters from all mobile cells. In both methods, further analysis is needed to understand the reasons for various operational states of the entire network

Advanced analysis methods for 3G cellular networks

Abstract — The operation and maintenance of the 3G mobile networks will be challenging. These networks will be strongly service driven, and this approach differs significantly from the traditional speech dominated 2G approach. Compared to 2G, in 3G the mobile cells interact and interfere with each other more, they have hundreds of adjustable parameters, and they monitor and record data related to several hundreds of different variables in each cell. This paper shows that a neural network algorithm called the Self-Organizing Map (SOM) together with a conventional clustering method like the k-means can effectively be used to simplify and focus network analysis. It is shown that these algorithms help in visualizing and grouping similarly behaving cells. Thus, it is easier for a human expert to discern different states of the network. This makes it possible to perform faster and more efficient trouble shooting and optimization of the parameters of the cells. The presented methods are applicable for different radio access network technologies