α-stable interference modeling and cauchy receiver for an IR-UWB Ad Hoc network

Abstract

In this paper we investigate ad hoc networks based on impulse radio ultra wideband. Due to multiple access, the interference distribution is not Gaussian. One important reason for errors is the presence of close interferers generating pulse collision. However such events are rare and we propose an α-stable model compatible with this fact due to its heavy tailed distribution. We derive the analytical expression of the two significant parameters. They depend on the attenuation coefficient, the users' density, the pulse collision probability and the pulse shape. We finally propose receiver strategies (Cauchy receiver and p-norm) that outperforms the classical Gaussian receiver.

Impulsive interference mitigation in ad hoc networks based on alpha-stable modeling and particle filtering

“…They show the theoretical validity of the stable approach for different situations in network interference, including ad hoc and cognitive radio. We also suggest that the ad hoc configuration gives the shape of the MAI distribution which is then accurately represented by symmetric α-stable distributions [6].…”

-stable multiple access interference modelling for amplify-and-forward multihop ad hoc networks

“…They show that, when interferers are scattered according to a Poisson process, the aggregate interference amplitude follows a symmetric stable distribution. We also show in [2] that in UWB ad hoc networks, the MAI can be accurately modelled by an a-stable random variable.…”

“…It has been shown [1,2] that I m can be accurately modelled with an a-stable random variable. The instantaneous signal-to-interference and noise ratio (SINR) is then:…”

CupCarbon: A new platform for the design, simulation and 2D/3D visualization of radio propagation and interferences in IoT networks

“…To avoid too heavy calculations, it is possible to randomly generate the interference. However, as shown in many papers (see [6], [7] for instance) a Gaussian model is not accurate. One solution is to accurately evaluate the main contributions of the interference and to randomly generate the global contribution of the less impacting interferers.…”