Receiver Interference Error Model

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Description

The Receiver Interference Error Model introduces configurable bit error injection to a Receiver component, independent of the link budget calculations performed by the Telemetry System. This model allows users to override the computed bit error rate with a fixed interference fraction, simulating external interference sources, environmental noise, or degraded receiver performance that may not be captured by the standard link analysis.

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Example Use Cases

• Interference Testing: Evaluate receiver and protocol robustness under known interference conditions.
• Environmental Noise Simulation: Model bit errors from sources not included in the link budget (e.g., on-board electronics noise).
• Sensitivity Analysis: Determine system tolerance to varying levels of signal degradation.
• Fault Injection: Introduce controlled errors for testing error detection and correction mechanisms.

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Module Implementation

The interference error model is attached to a Receiver component and overrides the bit error rate applied to incoming packets.

Interference Fraction

The model exposes a single parameter, the interference fraction $P_i\in [0,1]$, which defines the probability that any individual bit will be flipped during reception:

$$P(\text{bit flip})=P_i$$

When $P_i=0$, no additional interference is applied and the receiver uses the bit error rate computed from the link budget. When $P_i>0$, it overrides the link-calculated BER.

Override Behaviour

The interference fraction is applied as an override to the receiver’s normal bit error processing. For each incoming packet, the receiver uses the maximum of the link-calculated BER and the override interference:

$${\text{BER}}_{\text{applied}}=\max ({\text{BER}}_{\text{link}},P_i)$$

This ensures that the interference model can only increase the error rate, not reduce it below what the link budget predicts.

Bit Error Application

When the interference fraction is active, bit errors are applied to each packet using the receiver’s standard error injection process. For low error rates ($P_i<0.001$), the expected number of errors is sampled from a Poisson distribution:

$$N_{\text{errors}}\sim \text{Poisson}(n_{\text{bits}}\cdot P_i)$$

For higher error rates, each bit is tested independently against the interference probability.

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Assumptions/Limitations

• The interference fraction overrides rather than adds to the link-calculated bit error rate.
• Bit errors are applied independently to each bit; correlated or burst errors are not modelled.
• The model does not distinguish between different interference sources or frequency-dependent effects.
• Setting the interference fraction to zero allows the link budget BER to be used normally.
• The interference fraction must be in the range [0, 1]; values outside this range may produce undefined behavior.

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References

[1] F. A. Haight, Handbook of the Poisson Distribution. New York, NY, USA: John Wiley & Sons, 1967.