Simulation of Communication Systems

Abstract

Digital communications and computers are having a tremendous impact on the world today. In order to meet the increasing demand for digital communication services, engineers must design systems in a timely and cost-effective manner. The number of technologies available for providing a given service is growing daily, covering transmission media, devices, and software. The resulting design, analysis, and optimization of performance can be very demanding and difficult. Over the past decades, a large body of computer-aided engineering techniques have been developed to facilitate the design process of complex technological systems. These techniques rely on models of devices and systems, both analytic and simulation, to guide the analysis and design throughout the life cycle of a system. Computer-aided design, analysis, and simulation of communication systems constitute a new and important part of this process.This thesis studies different aspects of the simulation of communication systems by covering some basic ideas, approaches, and methodologies within the simulation context. Performance measurement of a digital communication is the main focus of this thesis. However, some popular visual indicators of signal quality, which are often generated in a simulation to provide a qualitative sense of the performance of a digital system, are also considered.Another purpose of this thesis is to serve as a model for developing simulations or template of other systems. In other words, students learning to simulate a system can use the work presented here as a starting point.iii Acknowledgement

Sparse channel estimation and tracking for cyclic delay diversity orthogonal frequency division multiplexing systems

“…Figure 6 shows the NMSE performance with two transmit antennas under the ITU Pedestrian A channel model with path delays at OE0 0:11 0:19 0:41 s and relative powers OE0 9:7 19:2 22:8 dB [24]. The sampling period is 0:1 s. Because most of the paths are not aligned with the sampling clock, energy is spread to the surrounding taps and causes leakage on both sides [25], thereby introducing small nonzero taps. Compared with Figure 5, the performance loss of the ideal LS exact sparse estimation to the MMSE exact sparse estimation is more significant.…”

Finding characteristically rich nonlinear solution space: a statistical mechanics approach

“…Furthermore, since = Const (=0) on Ω is perpendicular to the boundary and contains negative of one-dimensional Dirac delta function in the outward normal direction ( Figure 4) resulting in Equation (33). Therefore, for the uniform probability density we can rewrite Equation (25) as, using Equations (26) and (33),…”

“…According to Reference, 26 the time and frequency responses of an LTV system can be expressed as time and frequency convolutions between the system input u and the kernel C:…”

Symbol rate and signal capture in LMDS systems

“…In this paper, the relationships among symbol rate, temperature variation, and capture probability are investigated, based on the Monte-Carlo simulation [8] of the frequency tolerance and drift parameters in a LMDS system. To guarantee 100% probability of signal capture, symbol-rate limitations are presented.…”

“…They have generated growing interest in the antennas domain since, for example, they have become very useful to improve patch-antenna performances [2][3][4] or control beam radiation [5,6]. EBG materials are also of interest for the design of very efficient reflectors [7,8], or directive antennas [9 -12].…”