Robust radio-frequency (RF) pipelines must balance conflicting objectives: accurate demodulation of signals and low latency. Improving accuracy (true hit rate) often requires operating
in regimes with high signal-to-noise ratio (SNR) and small frequency offset, which may incur increased computational cost and run time. Conversely, minimising latency may require relaxing
accuracy. This paper explores these trade-offs using a synthetic RF benchmark and demonstrates how Pareto fronts and utility-based scalarisation can guide multi-objective optimisation.
We show that the Pareto frontier emerges naturally when plotting accuracy against latency and
that simple weighting schemes allow practitioners to select solutions consistent with particular
preferences. Runtime contour maps illustrate how latency varies across the parameter space
and identify operating regimes satisfying strict latency budgets.