[verified]: Sigcov

[ \text{Sigcov} = \int_X C(x) \cdot f(S(x)) , dx ] where ( f ) maps signal quality to a [0,1] utility (e.g., a logistic function of SINR or inverse variance). For discrete samples, sigcov could be the sum of weights over covered points where the signal exceeds a threshold. Traditional optimization often treats signal processing and coverage planning separately. A cellular engineer maximizes coverage; a communication theorist maximizes channel capacity. But a user at the cell edge with -120 dBm but no interference might have usable service, while a user with -90 dBm but heavy jamming has none. Sigcov forces joint optimization.