Interference Modeling in Wireless Communications

Abstract

In wireless communication networks, signal reception is often corrupted by interference from other sources that share the same propagation medium. Knowledge of the statistics of interference is important in achieving optimum signal detection and estimation. We here discuss statistical‐physical models for modeling interference. The interesting feature of these models is that they are non‐Gaussian, and in certain cases are heavy‐tail distributed. The latter property introduces several challenges in the analysis of interference, since heavy‐tail processes lack second‐order statistics. A introduction on heavy‐tail processes is also provided.