Numerical Conditional Probability Density Function and Its Application in Jitter Analysis

Chu, Yunhui; Aydiner, Alaeddin; Yan, Jin; Xiao, Kai; Lee, Beomtaek; Oh, Dan; Mikulchenko, Oleg; Norman, Adam; Friar, Rob; Fu, Yan; Phares, Charles

doi:10.1109/temc.2018.2790348

Cited by 6 publications

(2 citation statements)

References 12 publications

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“…According to Chu et al 25 and Simon, 26 the conditional error probability P m ( E / γ ) is given by

P_{m} false(E false/ γ false) = \frac{1}{2} \exp ((), a γ),

where

a = 0.5

for non‐coherent modulation, and hence, Equation (20) becomes

P_{m} false(E false/ γ false) = \frac{1}{2} \exp ((), 0.5 γ) .

…”

Section: Methodsmentioning

confidence: 99%

Hybrid threshold combining and maximum ratio combining model for satellite communication over composite Rayleigh and Rician fading channel

Ahmed

Agbaje

et al. 2021

Satell Commun Network

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Communication through satellite is of great task and importance especially in the world of telecommunication infrastructure. It plays a leading role for future communication systems. However, the performance of the satellite communication system is dominated by the channel conditions overwhelmed by multipath fading and ionospheric scintillation effects. Maximum ratio combining (MRC) previously used to tackle this problem is characterized with hardware complexity resulted in long processing time, while threshold combining (TC) with simple hardware display poor performance. Thus, evaluation of hybrid TC-MRC, with closed-form expression over composite Rayleigh and Rician fading channel is necessary. In this paper, TC and MRC are combined to improve the signal quality and performance. The data are modulated using M-ary quadrature amplitude modulation and transmitted over the combined effects. The received signals at varying paths are scanned to select the best paths. A mathematical expression using the probability density function of composite Rayleigh and Rician fading channel for mean integrated square error (MISE) is derived. The model is efficiently simulated and the performance is estimated. The results show that the hybrid TC-MRC model achieves lower MISE and processing time compared to threshold combiner and even maximum ratio combiner, and thereby enhance the performance of the satellite communication system.

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“…According to Chu et al 25 and Simon, 26 the conditional error probability P m ( E / γ ) is given by

P_{m} false(E false/ γ false) = \frac{1}{2} \exp ((), a γ),

where

a = 0.5

for non‐coherent modulation, and hence, Equation (20) becomes

P_{m} false(E false/ γ false) = \frac{1}{2} \exp ((), 0.5 γ) .

…”

Section: Methodsmentioning

confidence: 99%

Hybrid threshold combining and maximum ratio combining model for satellite communication over composite Rayleigh and Rician fading channel

Ahmed

Agbaje

et al. 2021

Satell Commun Network

View full text Add to dashboard Cite

show abstract

“…Let us assume that there are certain inputs and/or target vectors. The test input will be assigned to one class among the K defined classes and conditional density will also be estimated [19]. To ascertain optimal decision, prior results are combined by the rule of Bayes to obtain A-Posteriori class probabilities.…”

Section: Approach and Mathematical Aspectsmentioning

confidence: 99%

K- Means Based Probabilistic Neural Network (KPNN) For Designing Physical Machine – Classifier

Subramanian*,

Saravanan,

Bhuvaneswari

2019

IJITEE

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Cloud Computing necessitates virtual machines that can deploy users to a machine in a sub-optimal fashion for effective and maximum utilization of resources conserving overall energy within the specified duration. PNN is an effective probabilistic classifier which has been applied for a wide variety of computer application problems. However, for big data applications, we need either pre-processing algorithms for efficient classification with lower computing time or Mathematical tracking operators to speed up a parametric approach. This paper focuses to combine the traditional K means algorithm and a PNN to process the data obtained from Google cluster to classify them into pre-specified groups so as to implement PM classifier design to monitor the Cloud usage pattern. It is found after validation of KPNN with different data sets that KPNN works better than PNN in terms of accuracy even when the number of classes increases and turns out to be a computationally attractive tool.

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Method of Signaling Analysis Including Jitter Effect for Large-Scale Nonlinear Channel and Links

Dou,

Jiao,

Zhu

2023

2023 IEEE MTT-S International Conference on Numerical Electromagnetic and Multiphysics Modeling and Optimization (NEMO)

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Numerical Conditional Probability Density Function and Its Application in Jitter Analysis

Cited by 6 publications

References 12 publications

Hybrid threshold combining and maximum ratio combining model for satellite communication over composite Rayleigh and Rician fading channel

Hybrid threshold combining and maximum ratio combining model for satellite communication over composite Rayleigh and Rician fading channel

K- Means Based Probabilistic Neural Network (KPNN) For Designing Physical Machine – Classifier

Method of Signaling Analysis Including Jitter Effect for Large-Scale Nonlinear Channel and Links

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