Dear researchers,
Where the impulsive noise (alpha stable and contaminated Gaussian noise) can be found in real applications?
In other words, is there any field where the impulsive noise is used as a model other than the conventional Gaussian noise?
Best,
Dear
A work published by Jacek Ilow et al. in 1998 entitled " Analytic Alpha-Stable Noise Modeling in a Poisson Field of Interferers or Scatterers" demonstrated that its results are useful for the prediction of noise statistics in a wide range of environments with deterministic and stochastic power propagation laws. Computer simulations are provided to demonstrate the efficiency of the -stable noise model in multiuser communication systems.
The analysis presented in the study will be important in the performance evaluation of complex communication systems and in the design of efficient interference suppression techniques.
For reading the full paper, please see the attached file.
Another recent paper that discusses this topic is the one by Jing Lin et al. entitled " Impulsive Noise Mitigation in Powerline Communications Using Sparse Bayesian Learning".
Abstract:
Additive asynchronous and cyclostationary impulsive noise limits communication performance in OFDM powerline communication (PLC) systems. Conventional OFDM receivers assume additive white Gaussian noise and hence experience degradation in communication performance in impulsive noise.
Alternate designs assume a parametric statistical model of impulsive noise and use the model parameters in mitigating impulsive noise. These receivers require overhead in training and parameter estimation, and degrade due to model and parameter mismatch, especially in highly dynamic environments. In this paper, we model impulsive noise as a sparse vector in the time domain without any other assumptions, and apply sparse Bayesian learning methods for estimation and mitigation without training. We propose three iterative algorithms with different complexity vs. performance trade-offs: (1) we utilize the noise projection onto null and pilot tones to estimate and subtract the noise impulses; (2) we add the
information in the data tones to perform joint noise estimation and OFDM detection; (3) we embed our algorithm into a decision feedback structure to further enhance the performance of coded systems. When compared to conventional OFDM PLC receivers, the proposed receivers achieve SNR gains of up to 9 dB in coded and 10 dB in uncoded systems in the presence of impulsive noise.
For viewing the full paper, please see the attached file.
Hoping this will be helpful,
Rafik
Dear Prof. Karaman,
Thanks for your valuable feedback, appreciate it!
Best regards,
Mahdi
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