Communications Toolbox

berconfint

BER and confidence interval of Monte Carlo simulation

Syntax

[ber,interval] = berconfint(nerrs,ntrials)
[ber,interval] = berconfint(nerrs,ntrials,level)

Description

[ber,interval] = berconfint(nerrs,ntrials) returns the error probability estimate ber and the 95% confidence interval interval for a Monte Carlo simulation of ntrials trials with nerrs errors. interval is a two-element vector that lists the endpoints of the interval. If the errors and trials are measured in bits, then the error probability is the bit error rate (BER); if the errors and trials are measured in symbols, then the error probability is the symbol error rate (SER).

[ber,interval] = berconfint(nerrs,ntrials,level) specifies the confidence level as a real number between 0 and 1.

Examples

If a simulation of a communication system results in 100 bit errors in 10⁶ trials, then the BER (bit error rate) for that simulation is the quotient 10^-4. The command below finds the 95% confidence interval for the BER of the system.

nerrs = 100; % Number of bit errors in simulation
ntrials = 10^6; % Number of trials in simulation
level = 0.95; % Confidence level
[ber,interval] = berconfint(nerrs,ntrials,level)

The output below shows that, with 95% confidence, the BER for the system is between 0.0000814 and 0.0001216.

ber =

  1.0000e-004


interval =

  1.0e-003 *

    0.0814    0.1216

For an example that uses the output of berconfint to plot error bars on a BER plot, see Example: Curve Fitting for an Error Rate Plot

See Also

binofit (Statistics Toolbox), mle (Statistics Toolbox), Performance Evaluation

References

[1] Jeruchim, Michel C., Philip Balaban, and K. Sam Shanmugan, Simulation of Communication Systems, Second Edition, New York, Kluwer Academic/Plenum, 2000.

bercoding

berfading

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