Simulation Of Digital Communication Systems Research Articles

Research on Simulation Teaching of Communication System in Higher Vocational Education Based on MATLAB

With the rapid development of modern computer science and technology, a new generation of visual simulation software MATLAB has been developed. These powerful simulation software make the design and analysis of communication system simulation relatively intuitive and convenient, which also makes the communication system simulation technology get faster development. Through the dynamic simulation environment of MATLAB/Simulink, we can build a digital communication system simulation platform for design and simulation, which fully shows the importance of MATLAB/Simulink in the communication system. This paper mainly analyses the application of MATLAB in communication system simulation. Then this paper analyses the basic principle of DSB signal, the simulation of modulation signal based on M file and the mdl file.

Utilizing Simulink and MATLAB Graphical User Interface in Modelling and Simulation of Chaos-Based Digital Modulation Techniques

This paper describes a software package which is designed using MATLAB's Graphical User Interface (GUI) in order to provide a tool to be used for chaos-based digital communication systems. The basic working principle of this software package (Chaos-based Digital Communication System Simulation Package, CDCSSP) is to perform simulations of chaos-based digital modulation types under different conditions such as distinct chaotic oscillators and channel noise effects. Power spectra of the signals, some important time domain signals and Bit Error Rate (BER) curves for all the modulation types can be observed graphically by using CDCSSP. The main purpose of CDCSSP is to give preliminary information about chaos-based digital modulation schemes by using a visual interface with the graphical and numerical results of the simulations. T-test statistical analysis demonstrates how successful CDCSSP is in terms of enhancing student learning for educational purposes. CDCSSP can be used for educational purposes as an easy-to-use and user-friendly visual instruction tool.

System and Circuit Models for Microwave Antennas

This paper describes how circuit and system models are derived for antennas from measurement of the input reflection coefficient. Circuit models are used to optimize the antenna performance and to calculate the radiated power and the transfer function of the antenna. System models are then derived for transmitting and receiving antennas. The most important contribution of this study is to show how microwave structures can be integrated into the simulation of digital communication systems. This enables system designers to predict the effect of the microwave subsystem on the digital signals and calculate the resulting bit error rate

On the monte carlo simulation of digital communication systems in gaussian noise

We consider the general problem of the simulation of highly reliable systems operating in the presence of Gaussian noise. Our methodology uses importance sampling which has been shown to be a particularly effective method in the general discipline of rare-event simulation. The methods we propose are optimal in a certain sense, i.e., they are efficient. We also give a new class of simulation distributions that are universally efficient in the sense that they depend only on a single scalar parameter, regardless of the dimensionality of the underlying system or of the error sets to be simulated.

Power margin quality measures for correlated random variates derived from the normal distribution

The lack of a well-defined and meaningful measure of the quality of computer-generated correlated random variates complicates the design and comparison of generation algorithms for communications system simulation applications. This paper presents quantitative quality measures for computer-generated random variates having a multivariate Gaussian distribution or having a distribution that derives from the multivariate Gaussian distribution. These measures are, in particular, useful for digital communication system simulation applications. A theoretical basis for the definition of the measures is given and it is shown that the measures also possess useful intuitive interpretations. Examples of the use of these quality measures are provided.

A Modular Approach to the Design and Simulation of Digital Communication Systems

This paper describes an innovative approach for presenting the design and simulation of digital communication systems in a communication engineering course. Such a scheme enables students to design and implement specific parts of communication systems through group projects. This improves students' interest in the subject by addressing practical design issues from the material discussed in class.

The generation of correlated Rayleigh random variates by inverse discrete Fourier transform

A number of different algorithms are used for the generation of correlated Rayleigh random variates. This paper presents an analysis of the statistical properties of methods based on the inverse discrete Fourier transform (IDFT). A modification of the algorithm of Smith (1975) is presented, the new method requiring exactly one-half the number of IDPT operations and roughly two-thirds the computer memory of the original method. Evaluations of and comparisons between various variate generation methods using meaningful quantitative measures are believed to be lacking. New quantitative quality measures for random variate generation have been proposed that are, in particular, meaningful and useful for digital communication system simulation. This paper presents the application of these measures to the IDFT method and three other methods of correlated variate generation, comparing the algorithms in terms of the quality of the generated samples and the required computational effort.

Stochastic gradient optimization of importance sampling for the efficient simulation of digital communication systems

Importance sampling (IS) techniques offer the potential for large speed-up factors for bit error rate (BER) estimation using Monte Carlo (MC) simulation. To obtain these speed-up factors, the IS parameters specifying the simulation probability density function (PDF) must be carefully chosen. With the increased complexity in communication systems, analytical optimization of the IS parameters can be virtually impossible. We present a new IS optimization algorithm based on stochastic gradient techniques. The formulation of the stochastic gradient descent (SGD) algorithm is more general and system-independent than other existing IS methodologies, and its applicability is not restricted to a specific PDF or biasing scheme. The effectiveness of the SGD algorithm is demonstrated by two examples of communication systems where the IS techniques have not been applied before. The first example is a communication system with diversity combining, slow nonselective Rayleigh fading channel, and noncoherent envelope detection. The second example is a binary baseband communication system with a static linear channel and a recursive least square (RLS) linear equalizer in the presence of additive white Gaussian noise (AWGN).

On the asymptotic efficiency of importance sampling techniques

The asymptotic efficiency of importance sampling (IS) techniques for the simulation of rare events in a multidimensional nonlinear setting was studied by J.S. Sadowsky and J.A. Bucklew (see ibid., vol.36, p.579-88, 1990). Fundamental results on the asymptotic efficiency of the mean-value modification (MM) technique were derived. Additionally, a statement was made that other IS techniques cannot be asymptotically efficient. It is shown that for the simulation of digital communication systems with Gaussian input, a broad class of asymptotically efficient IS techniques exists. Necessary and sufficient conditions are provided for the asymptotic efficiency of five different IS techniques (including MM) for one-dimensional linear systems. Multidimensional generalizations of these IS techniques are proposed. A sufficient condition for the asymptotic efficiency of these techniques applied to multidimensional nonlinear systems is provided.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

An algorithmic approach to the optimization of importance sampling parameters in digital communication system simulation

Importance sampling is recognized as a potentially powerful method for reducing simulation runtimes when estimating the bit error rate (BER) of communications systems using Monte Carlo simulation. Analytically, minimizing the variance of the importance sampling (IS) estimator with respect to the biasing parameters has typically yielded solutions for systems for which the BER could be found analytically. A technique for finding an asymptotically optimal set of biasing parameter values, in the sense that as the resolution of the search and the number of runs used both approach infinity, the algorithm converges to the true optimum, is proposed. The algorithm determines the amount of biasing that minimizes a statistical measure of the variance of the BER estimate and exploits a theoretically justifiable relationship, for small sample sizes, between the BER estimate and the amount of biasing. The translation biasing scheme is considered, although the algorithm is applicable to other parametric IS techniques. Only mild assumptions are required of the noise distribution and system. Experimentally, improvement factors ranging from two to eight orders of magnitude are obtained for a number of distributions for both linear and nonlinear systems with memory.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Using weibull density function in importance sampling for digital communication system simulation

A Weibull density function is proposed as the biasing input noise distribution in importance sampling for digital communication system simulation. With this density function, a sample saving factor 2–4 orders larger than a previous composite technique could be obtained. Robustness with respect to the threshold setting is analysed.

Baseband equivalents in digital communication system simulation

In this tutorial the authors attempt to clarify the quantitative relationships among the three signal models, namely, the narrowband, complex envelope, and discrete-time complex sequence forms, commonly used in digital communication systems simulation and analysis. Consistent definitions are adopted in order to prevent confusion and potential resultant 3 dB error. Practical methods are derived for calibration of digital computer simulation quantities.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Noise generators for the simulation of digital communication systems

article Free Access Share on Noise generators for the simulation of digital communication systems Authors: Martina F. Schollmeyer Intelligent Systems Center, University of Missouri-Rolla, Rolla, Missouri Intelligent Systems Center, University of Missouri-Rolla, Rolla, MissouriView Profile , William H. Tranter Department of Electrical Engineering, University of Missouri-Rolla, Rolla, Missouri Department of Electrical Engineering, University of Missouri-Rolla, Rolla, MissouriView Profile Authors Info & Claims ACM SIGSIM Simulation DigestVolume 21Issue 3April 1991 pp 264–275https://doi.org/10.1145/106073.306870Online:01 April 1991Publication History 8citation595DownloadsMetricsTotal Citations8Total Downloads595Last 12 Months5Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

Noise generators for the simulation of digital communication systems

Noise generators for the simulation of digital communication systems

A composite importance sampling technique for digital communication system simulation

A new composite importance sampling technique is presented and investigated. An exact analysis is used to optimize the sample size saving and to investigate its robustness with respect to threshold settings. The composite technique offers a sample size savings of approximately 2.5 compared to the translation technique of D. Lu and K. Yao (1988) for memoryless systems. Applications as well as some questions for further research are discussed. >

An investigation of Gaussian tail and Rayleigh tail density functions for importance sampling digital communication system simulation

The gains achieved by the use of importance sampling in communication system simulation are strongly influenced by the choice of the biased input noise distribution. The Rayleigh tail and the Gaussian tail distributions are investigated for use as biased distributions in importance sampling. The robustness of these schemes with respect to the estimate of the unknown error probability is examined. It is shown that the Gaussian tail distribution previously considered to be theoretically optimum is not optimum in this regard. Methods of generating the biased random variates are presented. >

Improved importance sampling technique for efficient simulation of digital communication systems

An improved importance sampling technique for the efficient simulation of digital communication systems is proposed. Evaluation of low-probability error events by direct use of classical Monte Carlo (MC) simulation techniques usually involves a very large number of runs. Importance-sampling techniques make the low-probability events occur more frequently. The technique proposed here is based on optimized translations of the original probability densities. The only approximation needed in the optimizations is that of replacing the Q function by the simpler exponential expression. Detailed analytical evaluations of the estimation variances of the classical MC and the conventional and improved importance-sampling approaches for systems with memories and signals are presented and compared, showing the superior performance of the latter. Detailed numerical and simulation results are given. >

On the Application of Importance Sampling to BER Estimation in the Simulation of Digital Communication Systems

Importance sampling (IS) is a useful technique for reducing the number of Monte Carlo trials in BER estimation. Two important aspects of recent research work in this area are to find more applications of IS BER estimation and to seek a good bias scheme in the implementation of the estimator. This correspondence presents a general and rigorous mathematical description of these aspects of this problem which, we hope, will be useful for further research. We also present a general result on how to choose a good bias scheme which may provide some insight into the problem.

Application of Gauss Quadrature Rules to Digital Communication Problems

In multilevel bandpass data transmission there is usually a difference between the phase of the carrier signal and the phase of the receiver oscillator, thereby causing imperfect demodulation. The use of nonclassical Gauss quadrature rules (GQR's) allows: 1) a theoretical study of the joint effects of phase jitter, thermal noise, and intersymbol interference on average error probability; and 2) a maximum-precision sampling technique in the simulation of digital communication systems. On this basis, the mean-square-error and zero-forcing equalizers are considered, and their performances evaluated in terms of the average error probability for multilevel pulse-amplitude-modulation (PAM) and partial-response-coded (PRC) signaling schemes.