Neural Networks Based Physical Cell Identity Assignment for Self Organized 3GPP Long Term Evolution

This paper proposes neural networks based graph coloring technique to assign Physical Cell Identities throughout the self-organized 3GPP Long Term Evolution Networks. PCIs are allocated such that no two cells in the vicinity of each other or with a common neighbor get the same identity. Efficiency of proposed methodology resides in the fact that minimum number of identities is utilized in the network wise assignment. Simulations are performed on a very large scale network, where initially all the cells are without any PCIs assigned. Results of simulations are demonstrated to analyze the performance of the proposed technique. Discussions about the presence of femto cells and PCI assignment in them are also presented at the end

Identification of femtocells in mobile networks

The evolving mobile networks are requested to convey increasing data traffic as popularity of online services together with affordability of mobile devices is growing. One solution to mobile carriers, which can help them quickly deploy small base stations (BS) ensuring great indoor coverage with minimum costs, and high data rate capability, is femtocell technology. However, standard deployment techniques are unsatisfactory for these type of BSs. There are two main reasons for that. Firstly, femtocells will be deployed in great numbers. Secondly, they are deployed by users and are portable. It means their position is not known in advance, and can vary in time. Therefore, femtocells have to implement self-configuration principles. Physical Cell Identity is one of the most important parameters to be chosen automatically under defined conditions. It is crucial parameter, which allows them to convey a communication between a user equipment and a core network. A study on Physical Cell Identity issues in mobile networks with femtocells is presented in my thesis. For this purpose, I created two different models of femtocells deployment and deal with a collision and a confusion. They are two main problems, which threaten proper Physical Cell Identity assignment in mobile networks. Outputs of the thesis serves for better understanding of interrelations between differently placed femtocells in term of collision and confusion issue and as the basis to design the framework handling Physical Cell Identity allocation. The simulations conducted on proposed models were utilized to obtain probability characteristics and indicators based on graph theory. In the evaluation section, I appoint several characteristics as probability of collision, probability of confusion and maximal number of neighbourhood cells and some others to support solution of collision and confusion issue. I use results of evaluation and layout the framework for automated Physical Cell Identity assignment with two different approaches, the distributed one, and the centralized one. Since, femtocells are subcategory of small cells so findings, mentioned in this thesis, can also be used for other types of small cells.Katedra telekomunikační technik