A Network of Kalman Filters for MAI and ISI Compensation in a Non-Gaussian Environment | Zendy

Bessem Sayadi | Zendy; Sylvie Marcos | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

A Network of Kalman Filters for MAI and ISI Compensation in a Non-Gaussian Environment

Author(s) -

Bessem Sayadi,

Sylvie Marcos

Publication year - 2005

Publication title -

eurasip journal on advances in signal processing

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.317

H-Index - 88

eISSN - 1687-6180

pISSN - 1687-6172

DOI - 10.1155/asp.2005.635

Subject(s) - kalman filter , detector , gaussian , intersymbol interference , gaussian noise , algorithm , interference (communication) , control theory (sociology) , computer science , mathematics , statistics , telecommunications , physics , artificial intelligence , channel (broadcasting) , decoding methods , control (management) , quantum mechanics

This paper develops a new multiuser detector based on a network of kalman filters (NKF) dealing with multiple access-interference (MAI), intersymbol Interference (ISI), and an impulsive observation noise. The two proposed schemes are based on the modeling of the DS-CDMA system by a discrete-time linear system that has non-Gaussian state and measurement noises. By approximating the non-Gaussian densities of the noises by a weighted sum of Gaussian terms and under the common MMSE estimation criterion, we first derive an NKF detector. This version is further optimized by introducing a feedback exploiting the ISI interference structure. The resulting scheme is an NKF detector based on a likelihood ratio test (LRT). Monte-Carlo simulations have shown that the NKF and the NKF based on LRT detectors significantly improve the efficiency and the performance of the classical Kalman algorithm

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research