Modeling of UE-UE interference at 2.5 GHz WCDMA

Heiska, Kari; Rikkinen, Kari; Muszynski, Peter; Schwarz, Uwe

doi:10.1109/pimrc.2003.1264234

Cited by 2 publications

(2 citation statements)

References 2 publications

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“…Instead, users in the radio cell locate inside clusters. In [ 2 ], researchers derive the capacity reduction of a WCDMA downlink due to mobile-to-mobile interference, considering nonuniform user distribution. In [ 3 ], the author evaluates the impact of user equipment to user equipment interference between LTE systems operated by different operators at adjacent frequency bands, and real user distribution is also taken into account.…”

Section: Introductionmentioning

confidence: 99%

Derivation of Probability Density Function of Signal-to-Interference-Plus-Noise Ratio for the MS-to-MS Interference Analysis

Son

Kim

2013

The Scientific World Journal

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This paper provides an analytical derivation of the probability density function of signal-to-interference-plus-noise ratio in the scenario where mobile stations interfere with each other. This analysis considers cochannel interference and adjacent channel interference. This could also remove the need for Monte Carlo simulations when evaluating the interference effect between mobile stations. Numerical verification shows that the analytical result agrees well with a Monte Carlo simulation. Also, we applied analytical methods for evaluating the interference effect between mobile stations using adjacent frequency bands. The analytical derivation of the probability density function can be used to provide the technical criteria for sharing a frequency band.

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Section: Introductionmentioning

confidence: 99%

Derivation of Probability Density Function of Signal-to-Interference-Plus-Noise Ratio for the MS-to-MS Interference Analysis

Son

Kim

2013

The Scientific World Journal

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“…Although [2], [3], [4] derive the PDF of the SINR or the ACI to analyze the effect of interference between different cells, they belong to interference analysis for a intra-system. In [5], although the ACI between TSs for different systems is analyzed it is suggested by simulations not by analytic methods.…”

Section: Introductionmentioning

confidence: 99%

Derivation of the closed-form PDF of the downlink SIR for coexisting LTE systems

Kim

Son

Lee

2012

2012 IEEE 23rd International Symposium on Personal, Indoor and Mobile Radio Communications - (PIMRC)

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Recently, as a variety of cellular systems are coexisted and the use of mobiles in a confined space increases, interference problems between terminals become more important. In this paper, we derive the closed-form probability density function (PDF) of the downlink signal-to-interference ratio (SIR) due to uplink transmission of the adjacent terminal station of the other system for the coexistence environment of two cellular systems. And it is shown that the formula of the PDF is exactly the same with Monte-Carlo simulation. This probability distribution model of the SIR is useful in that it is very simple and can be applicable to general propagation models including shadow fading. With this model, interference analysis for coexisting LTE systems in 900 MHz band of South Korea is suggested.

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Modeling of UE-UE interference at 2.5 GHz WCDMA

Cited by 2 publications

References 2 publications

Derivation of Probability Density Function of Signal-to-Interference-Plus-Noise Ratio for the MS-to-MS Interference Analysis

Derivation of Probability Density Function of Signal-to-Interference-Plus-Noise Ratio for the MS-to-MS Interference Analysis

Derivation of the closed-form PDF of the downlink SIR for coexisting LTE systems

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