Math Models

Constants

In our RF-Math Module there are some constants defined:

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2
T0 = np.float(290)
N0 = np.float(10*np.log10(constants.k * 290 * 1 * 1000))

Parameter

Gain

The gain gets calculated from the given parameter from each device. The values are linear interpolated between the given frequency points.

Noise Temperature / Noise Figure

The noise parameter are internally calculated as noise-temperature. All other noise parameter are converter from the noise-temperature to their scale.

RFMath.convert_T_n(B=1)[source]

Convert Noise Temperature to Noise Power

Parameters:T (float) – Noise Temperature in [°K]
Returns:n – noise power in [dBm/Hz] / [dBm/(B*Hz)]
Return type:numpy.float
RFMath.convert_T_NF(Gain)[source]

Convert Noise Temperature to NoiseFigure

Parameters:
  • T (float) – Noise Temperature in [°K]
  • Gain (float) – Accumulated Gain in [dB]
Returns:

NF – Noisefigure in [dB]
Return type:

numpy.float

Notes

Output Power

The output power is simply the input power multiplied by the gain

P1dB

The output P1 parameter is simplistic modeled. It’s just a saturating upper bound.

OIP3

The OIP3 resp. IP3 in general is calculated by the famous equation:

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IP3 = P - (2*(IP3) - P + 6)

It is assumed a single CW signal (thus the +6dB)

SNR

The signal-to-noise ratio is exactly the signal - noise in dB.

SFDR

The spurious-dynamic range uses a simple approach and is the distance between output power and intermodulation 3 product.

Dynamic Range

The dynamic range is defined as the smaller of the SNR or SFDR.