BERDFc

<code>BERDF</code> is a standard <code>R</code> data frame created by the <code>simsigs()</code> function in
the forthcoming <code>coherent</code> package. The observations have been <code>condense</code>d

datasets

Provides maximum likelihood estimates of the
performance parameters that drive a binomial distribution of observed
errors, and takes full advantage of zero error observations. High performance
communications systems typically have inherent noise sources and other
performance limitations that need to be estimated. Measurements made at
high signal to noise ratios typically result in zero
errors due to limitation in available measurement time. Package includes
theoretical performance functions for common modulation schemes (Proakis,
"Digital Communications" (1995, <ISBN:0-07-051726-6>)), polarization shifted
QPSK (Agrell & Karlsson (2009, <DOI:10.1109/JLT.2009.2029064>)), and utility
functions to work with the performance functions.

Philip Shea

binfunest

Estimates Parameters of Functions Driving Binomial Random
Variables

BERDFc function

A dataframe with the following fields:<dl>
<dt>Name</dt>
<dd>Name of constellation used to create the record.</dd><dt>SNR</dt>
<dd>The SNR in Decibles of the observation.</dd><dt>Bps</dt>
<dd>The number of bits per symbol. The number of bits in a
simulation run is <code>Bps * N</code></dd><dt>NoisePower</dt>
<dd>The actual noise power in the simulation run. Since
the noise is randomly generated, this is a stochastic item.</dd><dt>N</dt>
<dd>The number of symbols in the simulation run.</dd><dt>SER</dt>
<dd>The number of symbols errors observed in the simulation run.</dd><dt>BER</dt>
<dd>The number of bit errors observed in the simulation run.</dd>
</dl>

Format

An example BERDF dataframe created by simsigs(), a function in a
forthcoming package coherent. — BERDFc

A dataframe with the following fields:<dl>
<dt>Name</dt>
<dd>Name of constellation used to create the record.</dd>

<dt>SNR</dt>
<dd>The SNR in Decibles of the observation.</dd>

<dt>Bps</dt>
<dd>The number of bits per symbol. The number of bits in a
simulation run is <code>Bps * N</code></dd>

<dt>NoisePower</dt>
<dd>The actual noise power in the simulation run. Since
the noise is randomly generated, this is a stochastic item.</dd>

<dt>N</dt>
<dd>The number of symbols in the simulation run.</dd>

<dt>SER</dt>
<dd>The number of symbols errors observed in the simulation run.</dd>

<dt>BER</dt>
<dd>The number of bit errors observed in the simulation run.</dd>


</dl>

BERDFc: An example `BERDF` dataframe created by `simsigs()`, a function in a forthcoming package `coherent`.

Description

Usage

Arguments

Format