A tunable 3-D statistical channel model for spatio-temporal characteristics of wireless communication networks: A tunable 3-D statistical channel model

A new 3-dimensional geometric channel model is proposed with multiple degrees of freedom in its scattering volume geometry, which enables accurate modeling of realistic propagation scenarios for emerging machine-to-machine wireless networks. Analytical expressions for the joint and marginal statistics in delay and angular domains are derived, and we present the impact of various physical channel parameters such as link distance, antenna height, size and position of the scattering region, as well as shape and orientation of the scattering region on the delay and angular spread of the proposed model. The derived analytical results are validated with simulations and are also shown to provide a good fit to published empirical data sets. Relative to existing models, the proposed model is shown to more accurately adapt to different propagation environments envisioned for emerging communication scenarios such as in indoor picocellular and vehicle-to-vehicle communication applications.