scholarly journals VOICE QUALITY IN MOBILE TELECOMMUNICATION SYSTEM / BALSO KOKYBĖ MOBILIOJO RYŠIO SISTEMOSE

2013 ◽  
Vol 5 (2) ◽  
pp. 150-154
Author(s):  
Evaldas Stankevičius
Keyword(s):  
Correlation Coefficient ◽  
Linear Prediction ◽  
Voice Quality ◽  
Quality Measurement ◽  
Prediction Method ◽  
Mobile Network ◽  
Mobile Telecommunication ◽  
Nonlinear Prediction ◽  
Telecommunication System ◽  
Hardware Configuration

The article deals with methods measuring the quality of voice transmitted over the mobile network as well as related problem, algorithms and options. It presents the created voice quality measurement system and discusses its adequacy as well as efficiency. Besides, the author presents the results of system application under the optimal hardware configuration. Under almost ideal conditions, the system evaluates the voice quality with MOS 3.85 average estimate; while the standardized TEMS Investigation 9.0 has 4.05 average MOS estimate. Next, the article presents the discussion of voice quality predictor implementation and investigates the predictor using nonlinear and linear prediction methods of voice quality dependence on the mobile network settings. Nonlinear prediction using artificial neural network resulted in the correlation coefficient of 0.62. While the linear prediction method using the least mean squares resulted in the correlation coefficient of 0.57. The analytical expression of voice quality features from the three network parameters: BER, C / I, RSSI is given as well. Article in Lithuanian. Santrauka Nagrinėjama mobiliuoju tinklu perduoto balso kokybės matavimo metodikos problematika, balso kokybės įvertinimo algoritmų pasirinkimo galimybės. Aptariamas sukurtos balso kokybės matavimo sistemos tinkamumas, efektyvumas. Pateikiami sukurtos sistemos taikymo rezultatai parinkus optimalią įrangos konfigūraciją. Sąlygomis, artimomis idealioms, gauta, kad sukurta sistema balso kokybę įvertina vidutiniu 3,85 MOS įverčiu, o standartizuota TEMS Investigation 9.0 – vidutiniu 4,05 MOS įverčiu. Aptarta balso kokybės prognozatoriaus sukūrimo galimybė. Ištirtas balso kokybės priklausomybės nuo mobiliojo tinklo parametrų prognozatorius, taikantis tiesinės ir netiesinės prognozės būdus. Netiesinė prognozė, taikant dirbtinius neuronų tinklus, teikia 0,62 koreliacijos koeficientą. Tiesinė prognozė mažiausiųjų kvadratų metodu teikia 0,57 koreliacijos koeficientą. Gauta analitinė balso kokybės funkcijos išraiška nuo trijų tinklo parametrų: BER, C/I, RSSI.

scholarly journals A novel method for the codecs’ performance analysis in mobile telephony systems

2020 ◽  
Vol 33 (2) ◽  
pp. 243-259
Author(s):  
Aleksandar Lebl ◽  
Dragan Mitic ◽  
Vladimir Matic ◽  
Mladen Mileusnic ◽  
Zarko Markov
Keyword(s):  
Quality Of Service ◽  
Flow Rate ◽  
Mobile Communications ◽  
Voice Quality ◽  
Mobile Telephony ◽  
Mobile Telecommunication ◽  
Telecommunication System ◽  
Full Rate ◽  
Novel Method

This paper presents a novel method of expressing the quality of service in a mobile telecommunication system when its performance depends on several factors including applied codecs? characteristics (voice quality and data flow rate) and telecommunications traffic service possibilities. The influence of these factors is unified in one variable - quality of service measure. The proposed method is especially applicable in the cases when two-dimensional systems are analyzed - for example when two codecs with different flow rate and different achievable connection quality are used in a system. As an example, we also studied system with full-rate or mixed full-rate and half-rate codec implementation depending on the offered traffic. The system performances - mean dataflow and mean connection quality as a function of offered traffic are presented graphically and also expressed quantitatively by the novel quality of service measure. The systems with different number of available traffic channels may be compared on the base of this novel evaluation value such that the system with the highest value is the most suitable one for the concrete situation. In this way mobile system design is simplified to the great extent. The developed model is applicable generally for mobile telephony systems defining, but in this paper we studied its implementation for Global System for Mobile communications.

scholarly journals Downstream prediction using a nonlinear prediction method

2013 ◽  
Vol 10 (11) ◽  
pp. 14331-14354 ◽  
Author(s):  
N. H. Adenan ◽  
M. S. M. Noorani
Keyword(s):  
Phase Space ◽  
Flood Control ◽  
River Flow ◽  
Linear Prediction ◽  
Prediction Method ◽  
Nonlinear Prediction ◽  
Langat River ◽  
Correlation Dimension Method ◽  
The Impact ◽  
Downstream Area

Abstract. The estimation of river flow is significantly related to the impact of urban hydrology, as this could provide information to solve important problems, such as flooding downstream. The nonlinear prediction method has been employed for analysis of four years of daily river flow data for the Langat River at Kajang, Malaysia, which is located in a downstream area. The nonlinear prediction method involves two steps; namely, the reconstruction of phase space and prediction. The reconstruction of phase space involves reconstruction from a single variable to the m-dimensional phase space in which the dimension m is based on optimal values from two methods: the correlation dimension method (Model I) and false nearest neighbour(s) (Model II). The selection of an appropriate method for selecting a combination of preliminary parameters, such as m, is important to provide an accurate prediction. From our investigation, we gather that via manipulation of the appropriate parameters for the reconstruction of the phase space, Model II provides better prediction results. In particular, we have used Model II together with the local linear prediction method to achieve the prediction results for the downstream area with a high correlation coefficient. In summary, the results show that Langat River in Kajang is chaotic, and, therefore, predictable using the nonlinear prediction method. Thus, the analysis and prediction of river flow in this area can provide river flow information to the proper authorities for the construction of flood control, particularly for the downstream area.

UMTS

2011 ◽  
pp. 134-154
Author(s):  
Péter Fazekas
Keyword(s):  
Access Network ◽  
Mobile Network ◽  
Transport Network ◽  
Universal Mobile Telecommunication System ◽  
Basic Operation ◽  
Mobile Telecommunication ◽  
Telecommunication System ◽  
Comprehensive Overview ◽  
Radio Interface

The aim of this chapter is to provide a brief yet comprehensive overview of the 3rd generation UMTS (Universal Mobile Telecommunication System) mobile network, with emphasis on its specific protocols. Therefore, in this chapter, the basic operation and protocol structure of UMTS network is described. The main architectural changes compared to GSM are shown, as well as the principles of the physical radio interface. The details of other relevant UMTS specific interfaces in the access network and their protocols are provided as well, along with the description of transport network solutions. The most relevant part of UMTS specifications, the radio interface protocols, are also presented.

scholarly journals Multivariate Nonlinear Analysis and Prediction of Shanghai Stock Market

2008 ◽  
Vol 2008 ◽  
pp. 1-8 ◽  
Author(s):  
Junhai Ma ◽  
Lixia Liu
Keyword(s):  
Time Series ◽  
Prediction Model ◽  
Stock Returns ◽  
Stock Price ◽  
Linear Prediction ◽  
Stock Exchange ◽  
Multivariate Time Series ◽  
Prediction Method ◽  
Nonlinear Prediction ◽  
Stock Price Prediction

This study attempts to characterize and predict stock returns series in Shanghai stock exchange using the concepts of nonlinear dynamical theory. Surrogate data method of multivariate time series shows that all the stock returns time series exhibit nonlinearity. Multivariate nonlinear prediction methods and univariate nonlinear prediction method, all of which use the concept of phase space reconstruction, are considered. The results indicate that multivariate nonlinear prediction model outperforms univariate nonlinear prediction model, local linear prediction method of multivariate time series outperforms local polynomial prediction method, and BP neural network method. Multivariate nonlinear prediction model is a useful tool for stock price prediction in emerging markets.

scholarly journals Robust Weighted l1,2 Norm Filtering in Passive Radar Systems

Sensors ◽  
2020 ◽  
Vol 20 (11) ◽  
pp. 3270 ◽  
Author(s):  
Baris Satar ◽  
Gokhan Soysal ◽  
Xue Jiang ◽  
Murat Efe ◽  
Thiagalingam Kirubarajan
Keyword(s):  
Target Detection ◽  
Impulsive Noise ◽  
Simulated Data ◽  
Real Data ◽  
Detection Performance ◽  
Passive Radar ◽  
Mobile Telecommunication ◽  
Telecommunication System ◽  
Conventional Methods ◽  
Non Gaussian

Conventional methods such as matched filtering, fractional lower order statistics cross ambiguity function, and recent methods such as compressed sensing and track-before-detect are used for target detection by passive radars. Target detection using these algorithms usually assumes that the background noise is Gaussian. However, non-Gaussian impulsive noise is inherent in real world radar problems. In this paper, a new optimization based algorithm that uses weighted l 1 and l 2 norms is proposed as an alternative to the existing algorithms whose performance degrades in the presence of impulsive noise. To determine the weights of these norms, the parameter that quantifies the impulsiveness level of the noise is estimated. In the proposed algorithm, the aim is to increase the target detection performance of a universal mobile telecommunication system (UMTS) based passive radars by facilitating higher resolution with better suppression of the sidelobes in both range and Doppler. The results obtained from both simulated data with α stable distribution, and real data recorded by a UMTS based passive radar platform are presented to demonstrate the superiority of the proposed algorithm. The results show that the proposed algorithm provides more robust and accurate detection performance for noise models with different impulsiveness levels compared to the conventional methods.

Voice Quality Measurement in perfSONAR

2010 ◽  
Vol 30 (0) ◽  
pp. 104
Author(s):  
Pin-Hsuan Chen ◽  
Che-Nan Yang
Keyword(s):  
Voice Quality ◽  
Quality Measurement
Sign in / Sign up

Export Citation Format

Share Document