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A master's thesis from Aalborg University
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Designing the algorithm for network discovery and selection in heterogeneous radio network environment

Author

Term

4. term

Publication year

2011

Submitted on

Pages

76

Abstract

Når nye radioadgangssystemer som LTE-Advanced og WiMAX rulles ud samtidig med, at ældre systemer stadig er i drift, bliver mobilnettene både tætte og blandede (heterogene). Det gør det vanskeligere for enheder at finde og vælge det bedst egnede netværk. Dette projekt præsenterer en algoritme til netværksopdagelse og -valg i sådanne heterogene miljøer. Algoritmen bruger et udvidet sæt udvælgelsesparametre knyttet til nøgletal for netværkets ydeevne (KPI’er) for at beslutte, hvornår en bruger skal optages, droppes eller overføres (handover) til et andet net. Algoritmen er implementeret i C++ og vurderet ved simuleringer. Ydelsen er evalueret i tre scenarier, blandt andet ved at måle, hvor mange brugere netværket kan betjene. Rapporten sætter løsningen i relation til eksisterende metoder, beskriver udviklingen af algoritmen og valg af softwareværktøjer samt præsenterer implementeringsdetaljer og resultater.

As new radio access systems such as LTE-Advanced and WiMAX are deployed alongside older technologies, mobile networks become dense and heterogeneous. This makes it harder for devices to discover and choose the best network. This project presents an algorithm for network discovery and selection in such mixed environments. The algorithm uses an extended set of selection parameters linked to key performance indicators (KPIs) to decide when to admit a user, drop a connection, or perform a handover (switch a user to another network). It is implemented in C++ and evaluated through simulations. Performance is assessed in three scenarios, including how many users can be served. The report positions the approach relative to state-of-the-art methods, details the algorithm’s development and software tool choices, and presents the implementation and results.

[This abstract was generated with the help of AI]