scholarly journals An Improved Iterative Nonlinear Least Square Approximation Method for the Design of SISO Wideband Mobile Radio Channel Simulators

2012 ◽  
Vol 2 (1-2) ◽  
Author(s):  
Akmal Fayziyev ◽  
Matthias Pätzold
Keyword(s):  
Simulation Model ◽  
Communication Systems ◽  
Goodness Of Fit ◽  
Radio Channel ◽  
Least Square ◽  
Model Parameters ◽  
Frobenius Norm ◽  
Single Input Single Output ◽  
Time Frequency ◽  
Wideband Channel

In this paper, we present an improved version of the iterative nonlinear least square approximation (INLSA) method for designing measurement-based single-input single-output (SISO) wideband channel simulators. The proposed method aims to fit the time-frequency correlation function (TFCF) of the simulation model to that of a measured channel. The parameters of the simulation model are determined iteratively by minimizing the Frobenius norm, which serves as a measure for the fitting error. In contrast to the original INLSA method, the proposed approach provides a unique optimized set of model parameters, which guarantees a quasi-perfect fitting with respect to the TFCF. We analyze the performance of the proposed method in terms of the goodness of fit to the measured data. The investigations will be carried out with respect to the TFCF and the scattering function. We demonstrate that the proposed approach is a powerful tool for the design of measurement-based wideband channel simulators, which are important for the performance evaluation of mobile communication systems under real-world propagation conditions.

scholarly journals Design and Simulation of Measurement-Based Correlation Models for Shadow Fading

2011 ◽  
Vol 1 (2) ◽  
Author(s):  
Matthias Pätzold ◽  
Nurilla Avazov ◽  
Van Duc Nguyen
Keyword(s):  
Simulation Model ◽  
Real World ◽  
Communication Systems ◽  
Goodness Of Fit ◽  
Model Parameters ◽  
Shadow Fading ◽  
Correlation Model ◽  
Lp Norm ◽  
Correlation Models ◽  
Average Duration Of Fades

This paper deals with the design of measurement-based correlation models for shadow fading. Based on the correlation model, we design a simulation model using the sum-of-sinusoids (SOS) method to enable the simulation of spatial lognormal processes characterizing real-world shadow fading scenarios. The model parameters of the simulation model are computed by applying the Lp-norm method (LPNM). This method facilitates an excellent fitting of the simulation model’s autocorrelation function (ACF) to that of measured channels. Our study includes an evaluation of all important statistical quantities of the proposed measurement-based simulation model, such as the probability density function (PDF), spatial ACF, decorrelation and coherence distance, as well as the level-crossing rate (LCR) and the average duration of fades (ADF). A comparison with the Gudmundson correlation model shows that the developed measurement-based correlation model outperforms the former one by far in terms of the goodness of fit to the measured data. The proposed measurement-based simulation model allows to study the effects of long-term fading on the performance of mobile communication systems under real-world shadow fading conditions.

Stochastic Approach to a Rain Attenuation Time Series Synthesizer for Heavy Rain Regions

2016 ◽  
Vol 6 (5) ◽  
pp. 2379
Author(s):  
Masoud Mohebbi Nia ◽  
Jafri Din ◽  
Hong Yin Lam ◽  
Athanasios D. Panagopoulos
Keyword(s):  
Time Series ◽  
Communication Systems ◽  
Measurement Data ◽  
Likelihood Estimation ◽  
Heavy Rain ◽  
Stochastic Approach ◽  
Rain Attenuation ◽  
Least Square ◽  
Model Parameters ◽  
Cir Model

<p>In this work, a new rain attenuation time series synthesizer based on the stochastic approach is presented. The model combines a well-known interest-rate prediction model in finance namely the Cox-Ingersoll-Ross (CIR) model, and a stochastic differential equation approach to generate a long-term gamma distributed rain attenuation time series, particularly appropriate for heavy rain regions. The model parameters were derived from maximum-likelihood estimation (MLE) and Ordinary Least Square (OLS) methods. The predicted statistics from the CIR model with the OLS method are in good agreement with the measurement data collected in equatorial Malaysia while the MLE method overestimated the result. The proposed stochastic model could provide radio engineers an alternative solution for the design of propagation impairment mitigation techniques (PIMTs) to improve the Quality of Service (QoS) of wireless communication systems such as 5G propagation channel, in particular in heavy rain regions.</p>

scholarly journals Stochastic Approach to a Rain Attenuation Time Series Synthesizer for Heavy Rain Regions

2016 ◽  
Vol 6 (5) ◽  
pp. 2379
Author(s):  
Masoud Mohebbi Nia ◽  
Jafri Din ◽  
Hong Yin Lam ◽  
Athanasios D. Panagopoulos
Keyword(s):  
Time Series ◽  
Communication Systems ◽  
Measurement Data ◽  
Likelihood Estimation ◽  
Heavy Rain ◽  
Stochastic Approach ◽  
Rain Attenuation ◽  
Least Square ◽  
Model Parameters ◽  
Cir Model

<p>In this work, a new rain attenuation time series synthesizer based on the stochastic approach is presented. The model combines a well-known interest-rate prediction model in finance namely the Cox-Ingersoll-Ross (CIR) model, and a stochastic differential equation approach to generate a long-term gamma distributed rain attenuation time series, particularly appropriate for heavy rain regions. The model parameters were derived from maximum-likelihood estimation (MLE) and Ordinary Least Square (OLS) methods. The predicted statistics from the CIR model with the OLS method are in good agreement with the measurement data collected in equatorial Malaysia while the MLE method overestimated the result. The proposed stochastic model could provide radio engineers an alternative solution for the design of propagation impairment mitigation techniques (PIMTs) to improve the Quality of Service (QoS) of wireless communication systems such as 5G propagation channel, in particular in heavy rain regions.</p>

scholarly journals A Three-parameter New Exponentiated Distribution for Life-time Data

2020 ◽  
pp. 194-203
Author(s):  
Arun Kumar Chaudhary ◽  
Vijay Kumar
Keyword(s):  
Goodness Of Fit ◽  
Survival Function ◽  
Continuous Distribution ◽  
Life Time ◽  
Least Square ◽  
Cumulative Distribution ◽  
Model Parameters ◽  
Time Data ◽  
Data Set ◽  
Exponentiated Distribution

In the presented work, a continuous distribution consisting of three-parameters is proposed for life-time data called new exponentiated distribution. The discussion of some of the distribution’s statistical as well as mathematical properties, including the Cumulative Distribution Function (CDF), Probability Density function (PDF), quantile function, survival function, hazard rate function, kurtosis measures and skewness, is conducted. The estimation of the presented distribution’s model parameters is performed using the techniques of Cramer-Von-Mises estimation (CVME), least-square estimation (LSE), and maximum likelihood estimation (MLE). The evaluation of the proposed distribution’s goodness of fit is performed through its fitting in comparison with some of the other existing life-time models with the help of a real data set.

scholarly journals THE LOGISTIC INVERSE LOMAX DISTRIBUTION WITH PROPERTIES AND APPLICATIONS

2021 ◽  
Vol 09 (01) ◽  
Author(s):  
Ramesh Kumar Joshi ◽  
Keyword(s):  
Goodness Of Fit ◽  
Survival Function ◽  
Continuous Distribution ◽  
Least Square ◽  
Cumulative Distribution ◽  
Estimation Methods ◽  
Model Parameters ◽  
Data Set ◽  
Lomax Distribution ◽  
Inverse Lomax Distribution

In this article, a three-parameter continuous distribution is introduced called Logistic inverse Lomax distribution. We have discussed some mathematical and statistical properties of the distribution such as the probability density function, cumulative distribution function and hazard rate function, survival function, quantile function, the skewness, and kurtosis measures. The model parameters of the proposed distribution are estimated using three well-known estimation methods namely maximum likelihood estimation (MLE), least-square estimation (LSE), and Cramer-Von-Mises estimation (CVME) methods. The goodness of fit of the proposed distribution is also evaluated by fitting it in comparison with some other existing distributions using a real data set.

Improving Space-Time-Frequency MIMO-OFDM with ICI Self-Cancellation Scheme using Least Square Error Estimator

2015 ◽  
Vol 12 (1) ◽  
pp. 25
Author(s):  
Nur Farahiah Ibrahim ◽  
Zahari Abu Bakar ◽  
Azlina Idris
Keyword(s):  
Channel Estimation ◽  
Orthogonal Frequency Division Multiplexing ◽  
Symbol Error Rate ◽  
Space Time ◽  
Least Square ◽  
Error Estimator ◽  
Frequency Diversity ◽  
Time Frequency ◽  
Mimo Ofdm ◽  
Subcarrier Mapping

Channel estimation techniques for Multiple-input Multiple-output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) based on comb type pilot arrangement with least-square error (LSE) estimator was investigated with space-time-frequency (STF) diversity implementation. The frequency offset in OFDM effected its performance. This was mitigated with the implementation of the presented inter-carrier interference self-cancellation (ICI-SC) techniques and different space-time subcarrier mapping. STF block coding in the system exploits the spatial, temporal and frequency diversity to improve performance. Estimated channel was fed into a decoder which combined the STF decoding together with the estimated channel coefficients using LSE estimator for equalization. The performance of the system was compared by measuring the symbol error rate with a PSK-16 and PSK-32. The results show that subcarrier mapping together with ICI-SC were able to increase the system performance. Introduction of channel estimation was also able to estimate the channel coefficient at only 5dB difference with a perfectly known channel.

ANALISIS ADVERSITY QUOTIENT DAN KOMUNIKASI INTERPERSONAL DENGAN KOMITMEN ORGANISASI SEBAGAI INTERVENING TERHADAP PRODUKTIVITAS KARYAWAN

2020 ◽  
Vol 7 (2) ◽  
pp. 125-139
Author(s):  
Abd. Rasyid Syamsuri ◽  
Abd. Halim ◽  
Dilla Darvita
Keyword(s):  
Goodness Of Fit ◽  
Equation Model ◽  
Partial Least Square ◽  
Least Square ◽  
Inner Model

Tujuan penelitian ini untuk menganalisis pengaruh adversity quotient dan komunikasi interpersonal dengan komitmen organisasi sebagai Intervening terhadap produktvitas karyawan. Penelitian ini kami lakukan di PT. Gloria Jaya Sejahtera Medan-Indonesia dengan pengumpulan data melalui pendekatan survei yang menyebar kuesioner kepada 40 karyawan. Teknik pengumpulan data dilakukan dengan wawancara, kuesioner dan observasi. Alat analisis yang digunakan pada penelitian ini menggunakan software Statistical Product and Service Solutions (SPSS) dan Stuctural Equation Model (SEM) dengan SmartPLS (Partial Least Square). Pengujian dengan model struktural (inner model) dapat diperoleh bahwa nilai R square untuk variabel komitmen organisasi (Z) dan produktivitas karyawan (Y) dapat dijelaskan oleh variabel adverstiy quotient (X1), dan komunikasi interpersonal (X2), sebesar 75,3%, dan 83,3 % sedangkan sisanya dijelaskan oleh varibel lain. Untuk uji kesesuain model (uji goodness of fit) dapat diketahui bahwa nilai Q2 = 0,958 > 0 yang berarti model penelitian adversity quotient (X1), komunikasi interpersonal (X2), komitmen organisasi (Z), dan produktivitas karyawan (Y) di PT. Gloria Jaya Sejahtera Medan memiliki kesesuaian. Hasil penelitian dengan uji-t dapat diketahui bahwa adversity quotient berpengaruh positif dan tidak signifikan terhadap komitmen organisasi dengan nilai t satistik sebesar 1,069 lebih kecil dari t-tabel 1,96, komunikasi interpersonal berpengaruh positif dan signifikan terhadap komitmen organisasi dengan nilai t satistik sebesar 4,259 lebih besar dari t-tabel 1,96, adversity quotient berpengaruh negatif dan signifikan terhadap produktvitas karyawan dengan nilai t satistik sebesar 2,632 lebih besar dari t-tabel 1,96, komunikasi interpersonal berpengaruh positif dan signifikan terhadap produktvitas kerja karyawan dengan nilai t satistik sebesar 2,900 lebih besar dari t-tabel 1,96, komitmen organisasi berpengaruh positif dan signifikan terhadap produktvitas karyawan dengan nilai t satistik sebesar 4,399 lebih besar dari t-tabel 1,96.

INNOVATIVE METHOD OF SATELLITE COMMUNICATION

2019 ◽  
Author(s):  
Teodor Narytnik ◽  
Vladimir Saiko
Keyword(s):  
Communication Systems ◽  
High Speed ◽  
Satellite Communication ◽  
Radio Channel ◽  
Satellite Communications ◽  
Service Area ◽  
Satellite Systems ◽  
Orbit Satellite ◽  
Geometric Size ◽  
Distributed Satellite

The technical aspects of the main promising projects in the segments of medium and low-orbit satellite communication systems are considered, as well as the project of the domestic low-orbit information and telecommunications system using the terahertz range, which is based on the use of satellite platforms of the micro- and nanosatellite class and the distribution of functional blocks of complex satellite payloads more high-end on multiple functionally related satellites. The proposed system of low-orbit satellite communications represents the groupings of low-orbit spacecraft (LEO-system) with the architecture of a "distributed satellite", which include the groupings of the root (leading) satellites and satellite repeaters (slaves). Root satellites are interconnected in a ring network by high-speed links between the satellites. The geometric size of the “distributed satellite” is the area around the root satellite with a radius of about 1 km. The combination of beams, which are formed by the repeater satellites, make up the service area of the LEO system. The requirements for the integrated service area of the LEO system (geographical service area) determine the requirements for the number of distributed satellites in the system as a whole. In the proposed system to reduce mutual interference between the grouping of the root (leading) satellites and repeater satellites (slaves) and, accordingly, minimizing distortions of the information signal when implementing inter-satellite communication, this line (radio channel) was created in an unlicensed frequency (e.g., in the terahertz 140 GHz) range. In addition, it additionally allows you to minimize the size of the antennas of such a broadband channel and simplify the operation of these satellite systems.

scholarly journals Time–Frequency-Analysis-Based Blind Modulation Classification for Multiple-Antenna Systems

Sensors ◽  
2021 ◽  
Vol 21 (1) ◽  
pp. 231
Author(s):  
Weiheng Jiang ◽  
Xiaogang Wu ◽  
Yimou Wang ◽  
Bolin Chen ◽  
Wenjiang Feng ◽  
...  
Keyword(s):  
Frequency Analysis ◽  
Classification Accuracy ◽  
Communication Systems ◽  
Mimo Systems ◽  
Decision Fusion ◽  
Frequency Characteristics ◽  
Modulation Classification ◽  
Time Frequency Analysis ◽  
Time Frequency ◽  
Average Classification Accuracy

Blind modulation classification is an important step in implementing cognitive radio networks. The multiple-input multiple-output (MIMO) technique is widely used in military and civil communication systems. Due to the lack of prior information about channel parameters and the overlapping of signals in MIMO systems, the traditional likelihood-based and feature-based approaches cannot be applied in these scenarios directly. Hence, in this paper, to resolve the problem of blind modulation classification in MIMO systems, the time–frequency analysis method based on the windowed short-time Fourier transform was used to analyze the time–frequency characteristics of time-domain modulated signals. Then, the extracted time–frequency characteristics are converted into red–green–blue (RGB) spectrogram images, and the convolutional neural network based on transfer learning was applied to classify the modulation types according to the RGB spectrogram images. Finally, a decision fusion module was used to fuse the classification results of all the receiving antennas. Through simulations, we analyzed the classification performance at different signal-to-noise ratios (SNRs); the results indicate that, for the single-input single-output (SISO) network, our proposed scheme can achieve 92.37% and 99.12% average classification accuracy at SNRs of −4 and 10 dB, respectively. For the MIMO network, our scheme achieves 80.42% and 87.92% average classification accuracy at −4 and 10 dB, respectively. The proposed method greatly improves the accuracy of modulation classification in MIMO networks.

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