ber_pi4dqpsk()

Returns the symbol probability of error versus signal-to-noise ratio per bit for pi/4 DQPSK modulation

Syntax
data = ber_pi4dqpsk(vIn, vOut, symRate, noise, samplingDelay, rotation, tranDelay, pathDelay)

Arguments
Name Description Range Type Required
vIn complex envelope voltage signals at the input node (-∞, ∞) complex yes
vOut complex envelope voltage signals at the output node (-∞, ∞) complex yes
symRate symbol rate (real) of the modulation signal (0, ∞) real yes
noise RMS noise vector (0, ∞) real yes
samplingDelay clock phase in seconds [0, ∞) real yes
rotation carrier phase in radians [0, ∞) real yes
tranDelay time in seconds that causes this time duration of symbols to be eliminated from the bit error rate calculation † [0, ∞) real yes
pathDelay delay from input to output in seconds [0, ∞) real yes
† Usually the filters in the simulation have transient responses, and the bit error rate calculation should not start until these transient responses have finished

Examples

y = ber_pi4dqpsk(videal[1], vout[1], 0.5e6, {0.1::-0.01::0.02})

Defined in

$HPEESOF_DIR/expressions/ael/digital_wireless_fun.ael

See Also

ber_qpsk(), constellation()

Notes/Equations

Used in Circuit Envelope and Signal Processing simulations.
The arguments vIn and vOut usually come from a circuit envelope simulation, while noise usually comes from a harmonic balance simulation, and is assumed to be additive white Gaussian. It can take a scalar or vector value. The function uses the quasi-analytic approach for estimating BER: for each symbol, Eb / N0 and BER are calculated analytically; then the overall BER is the average of the BER values for the symbols.
Note that ber_pi4dqpsk returns a list of data:
data[0]= symbol probability of error versus Eb / N0
data[1]= path delay in seconds
data[2]= carrier phase in radians
data[3]= clock phase in seconds
data[4]= complex(Isample, Qsample)

 

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