berconfint

Error probability estimate and confidence interval of Monte Carlo simulation

Description

[errprobest,interval] = berconfint(nerrs,ntrials) returns the error probability estimate and 95% confidence interval for a Monte Carlo simulation of ntrials trials with nerrs errors.

example

[errprobest,interval] = berconfint(nerrs,ntrials,level) specifies the confidence level.

Examples

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Compute the confidence interval for the simulation of a communication system that has 100 bit errors in 106 trials. The bit error rate (BER) for that simulation is ${10}^{-4}$.

Compute the 90% confidence interval for the BER of the system. The output shows that, with 90% confidence level, the BER for the system is between 0.0000841 and 0.0001181.

nerrs = 100;    % Number of bit errors in simulation
ntrials = 10^6; % Number of trials in simulation
level = 0.90;   % Confidence level
[ber,interval] = berconfint(nerrs,ntrials,level)
ber = 1.0000e-04
interval = 1×2
10-3 ×

0.0841    0.1181

For an example that uses the output of the berconfint function to plot error bars on a BER plot, see Use Curve Fitting on Error Rate Plot.

Input Arguments

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Number of errors from Monte Carlo simulation results, specified as a scalar.

Data Types: single | double

Number of trials from Monte Carlo simulation results, specified as a scalar.

Data Types: single | double

Confidence level for a Monte Carlo simulation, specified as a scalar in the range [0, 1].

Data Types: single | double

Output Arguments

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Error probability estimate for a Monte Carlo simulation, returned as a scalar.

• If the errors and trials are measured in bits, the error probability is the bit error rate (BER).

• If the errors and trials are measured in symbols, the error probability is the symbol error rate (SER).

Confidence interval for a Monte Carlo simulation, returned as a two-element column vector that lists the endpoints of the confidence interval for the confidence level specified by the input level.

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