Abstract
Efficient system design requires the use of tools for evaluating the performance of a given system. Based on a performance analysis method, design algorithms can be constructed, for example, with a specific performance optimization goal. The ideal analysis tool should be (i) fast, (ii) accurate, and, possibly, (iii) highly informative, i.e., it should provide a comprehensive description of the system under analysis. However, exact analytical evaluation of the relevant statistical parameters characterizing a realistic communication system is, usually, unfeasible. Therefore, it is necessary to resort to approximate evaluation tools. A universal technique satisfying the requirements (ii) and (iii) is given by a Monte Carlo simulation-based analysis of the system performance. In particular, this simulation method allows to collect all needed system statistical parameters with the desired accuracy. Unfortunately, system simulation is usually a computationally intensive task. This makes this technique not appealing for automated system parameter optimization (or design), which usually calls for repeated analyses. Nevertheless, Monte Carlo simulation is an invaluable tool suited for accurately testing the performance of a complex system. Iterative receiver schemes can also be investigated through a number of approximate tools which exploit their internal structures. For example, density evolution and extrinsic information transfer (EXIT) charts admit efficient numerical implementation, since they are characterized by a limited computational complexity.
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© 2009 Springer-Verlag Berlin Heidelberg
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(2009). Performance Analysis Techniques. In: LDPC Coded Modulations. Signals and Communication Technology. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69457-1_4
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DOI: https://doi.org/10.1007/978-3-540-69457-1_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69455-7
Online ISBN: 978-3-540-69457-1
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