Impulsive noise modeling and robust receiver design

Abstract Interference is an important limitation in many communication systems. It has been shown situations that the popular Gaussian approximation not adequate and interference exhibits impulsive behavior. This paper surveys different statistical models proposed for such interference, can generally be unified using class of sub-exponential family distributions, its impact on receiver design. Visualizing optimal decision boundaries allows one to show non linear effect induced by noise models, which explains significant loss performance designed under standard approximation. motivates need develop new receivers. We propose a framework design receivers robust variety types, both non-Gaussian. explore three ways thinking about designs: approach; approximating plus distribution; mimicking rule distribution directly. Except approach, other designs are capable replicating non-trivial regions extents. The detection algorithms evaluated via Monte Carlo simulations. focus four efficient architectures, including parameter estimations: Myriad, Normal Inverse Gaussian, p -norm direct estimation likelihood ratio function. They exhibit good performance, close optimal, large range demonstrating they may considered as rules presence heavy tailed or environments.