  We proposed a deterministic multidimensional growth model for small-world
networks. The model can characterize the distinguishing properties of many
real-life networks with geometric space structure. Our results show the model
possesses small-world effect: larger clustering coefficient and smaller
characteristic path length. We also obtain some accurate results for its
properties including degree distribution, clustering coefficient and network
diameter and discuss them. It is also worth noting that we get an accurate
analytical expression for calculating the characteristic path length. We verify
numerically and experimentally these main features.
