Quantifying Performance in Fading Channels Using the Sampling Property of a Delta Function

We apply the sampling property of a delta function to obtain the probability of error in fading channels. Our approach reduces the integration to a sampling. The sampling point is obtained in terms of fading parameters and the average signal-to-noise ratio (SNR) to provide the closed form solution of the performance

Quantifying Performance in Fading Channels Using the Sampling Property of a Delta Function

We apply the sampling property of a delta function to obtain the probability of error in fading channels. Our approach reduces the integration to a sampling. The sampling point is obtained in terms of fading parameters and the average signal-to-noise ratio (SNR) to provide the closed form solution of the performance

Generalizing the Sampling Property of the Q-function for Error Rate Analysis of Cooperative Communication in Fading Channels

This paper extends some approximation methods that are used to identify closed form Bit Error Rate (BER) expressions which are frequently utilized in investigation and comparison of performance for wireless communication systems in the literature. By using this group of approximation methods, some expectation integrals, which are complicated to analyze and have high computational complexity to evaluate through Monte Carlo simulations, are computed. For these integrals, by using the sampling property of the integrand functions of one or more arguments, reliable BER expressions revealing the diversity and coding gains are derived. Although the methods we present are valid for a larger class of integration problems, in this work we show the step by step derivation of the BER expressions for a canonical cooperative communication scenario in addition to a network coded system starting from basic building blocks. The derived expressions agree with the simulation results for a very wide range of signal-to-noise ratio (SNR) values.Comment: 5 pages, 5 figures, Submitted to IEEE International Symposium on Information Theory, ISIT 2013, Istanbul, Turke