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

Abstract

In this paper, we tackle the problem of interference mitigation in ad hoc networks. In such context, the multiple access interference (MAI) is known to be of an impulsive nature. Therefore, the conventional Gaussian assumption can not be considered to model this type of interference. Contrariwise, it can be accurately modeled by stable distributions. Here, this issue is addressed within an Orthogonal Frequency Division Multiplexing (OFDM) transmission link assuming a symmetric α-stable model for the signal distortion due to MAI. For this purpose, we propose a method for the joint estimation of the transmitted multicarrier signal and the noise parameters. Based on sequential Monte Carlo (SMC) methods, the proposed scheme allows the online estimation using a Raoblackwellized particle filter.Index Terms-ad hoc networks, multiple access interference, sequential Monte Carlo methods, α-stable distribution

Interference Reduction Technique in Mobile Adhoc Networks using Mathematical Prediction Filters

“…Nouha Jaoua et al [13] have proposed an approach based on Bayesian estimation using particle filtering. They have proposed their approach to estimate jointly the multicarrier signal and the noise parameters.…”