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

Abstract

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.

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Correspondence to Bessem Sayadi.

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Sayadi, B., Marcos, S. A Network of Kalman Filters for MAI and ISI Compensation in a Non-Gaussian Environment. EURASIP J. Adv. Signal Process. 2005, 134082 (2005). https://doi.org/10.1155/ASP.2005.635

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Keywords and phrases:

  • multiuser detection
  • Kalman filtering
  • Gaussian sum approximation
  • impulsive noise
  • likelihood ratio test
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