APPENDIX

I   Monte Carlo Integration

In a generic sense, Monte Carlo simulation1 is an invaluable experimental tool for tackling difficult problems that are mathematically intractable; but the tool is imprecise in that it provides statistical estimates. Nevertheless, provided that the Monte Carlo simulation is conducted properly, valuable insight into a problem of interest is obtained, which would be difficult otherwise.

In this appendix, we focus on Monte Carlo integration, which is a special form of Monte Carlo simulation. Specifically, we address the difficult integration problem encountered in Chapter 5 dealing with computation of the differential entropy h(Y), based on the mathematically intractable conditional probability density function of (5.102) in Chapter 5.

To elaborate, we may say:

Monte Carlo integration is a computational tool, which is used to integrate a given function defined over a prescribed area of interest that is not easy to sample in a random and uniform manner.

Let W denote the difficult area over which random sampling of the differential entropy h(Y) is to be performed. To get around this difficulty, let V denote an area so configured that it incudes the area W and is easy to randomly sample. Desirably, the selected area V enclosed W as closely as possible for the simple reason that samples picked outside of W are of no practical interest.

Suppose now we pick a total of N samples in the area V, randomly and uniformly. Then according to Press, et al. (1998), ...

Get Digital Communication Systems now with the O’Reilly learning platform.

O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.