  We investigate a spatial random graph model whose vertices are given as a
marked Poisson process on $\mathbb{R}^d$. Edges are inserted between any pair
of points independently with probability depending on the spatial displacement
of the two endpoints and on their marks. Upon variation of the Poisson density,
a percolation phase transition occurs under mild conditions: for low density
there are finite connected components only, whilst for large density there is
an infinite component almost surely. Our focus is on the transition between the
low- and high-density phase, where the system is critical. We prove that if the
dimension is high enough and the edge probability function satisfies certain
conditions, then an infrared bound for the critical connection function is
valid. This implies the triangle condition, thus indicating mean-field
behaviour. We achieve this result through combining the recently established
lace expansion for Poisson processes with spectral estimates.
