Estimation of signal to noise ratio value based on Autoregressive Integrated Moving Average model in Intelligent Satellite System

Author

Almuhtadi, Wahab ; Cheng, Brian ; Aristama, Aswin ; Olafimihan, Omotayo

Author_Institution

Algonquin Coll., Ottawa, ON

fYear

2008

fDate

4-7 May 2008

Abstract

For intelligent satellite system (ISS) to accomplish its missions, it has to adjust dynamically its operation according to future signal to noise ratio (SNR) value which can be estimated by using autoregressive integrated moving average (ARIMA) models. The ARIMA module takes the forecasted signal attenuation and real-time SNR values as the inputs and estimates the SNR values as the output. The ARIMA module will be updating the database with future SNR values in real-time for every one minute. This database will then be used by the ISS to achieve the most efficient operation mechanism.

Keywords

autoregressive moving average processes; satellite communication; signal processing; autoregressive integrated moving average model; intelligent satellite system; real-time SNR value; signal attenuation; signal-to-noise ratio estimation; Attenuation; Databases; Educational institutions; Equations; Intelligent systems; Predictive models; Satellite broadcasting; Signal to noise ratio; Testing; Throughput; ARIMA; ISS; SNR; attenuation; forecast; satellite;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical and Computer Engineering, 2008. CCECE 2008. Canadian Conference on

Conference_Location

Niagara Falls, ON

ISSN

0840-7789

Print_ISBN

978-1-4244-1642-4

Electronic_ISBN

0840-7789

Type

conf

DOI

10.1109/CCECE.2008.4564674

Filename

4564674