Co-channel interference in heterogeneous networks: Rician/Rayleigh scenario
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Elektroniikan, tietoliikenteen ja automaation tiedekunta |
Master's thesis
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Authors
Date
2010
Department
Major/Subject
Tietoliikennetekniikka
Mcode
S-72
Degree programme
Language
en
Pages
68
Series
Abstract
The purpose of this study is to analyze interference for a macro cellular network h which embeds femtocells and/or relay nodes. Femtocells and relay nodes are being introduced to improve coverage and capacity of conventional cellular networks. However, their introduction comes with additional interference between the uacrocell and femtocell/relay node, and between individual femtocells/relay nodes. Hence, there is a need for analytical expressions for the performance measures such that outage probability and average capacity so that the effect of co-channe1 interference is understood thoroughly. In this thesis, analytical and numerical results are presented for outage probability and average capacity in a Rician/Rayleigh Scenario. In this scenario, the desired signal experiences Rician fading channel and the interfering signals experience Rayleigh fading channels. Closed-form and infinite series expressions are found for the outage probability and an infinite sum expression is found for the average capacity. The analysis approximates SINR by its tight upper bound SIR; therefore, the outage probability result is a tight lower bound and the average capacity result is a tight upper bound of their corresponding results without the approximation. Moreover, the thesis, as a background work, includes detailed studies of the relevant probability distributions used to model fading channels and radio link performance metrics in the absence of interference.Description
Supervisor
Hämäläinen, JyriThesis advisor
Riihonen, TaneliKeywords
probability distributions, channel modeling, co-channel interference, Rayleigh fading, Rician fading, Nakagami fading, Weibull fading, lognormal fading, outage probability, outage capacity, average capacity, heterogeneous networks