Parameter estimation of impulsive noise for channel coded communication systems
Abstract In this paper, an impulsive noise estimation algorithm for generating bit log‐likelihood ratios (LLRs) for channel coded systems in impulsive noise environments is proposed. This approach is to design the LLR detector in the maximum‐likelihood (ML) sense, which requires the parameters of th...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-02-01
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| Series: | IET Communications |
| Online Access: | https://doi.org/10.1049/cmu2.12077 |
| Summary: | Abstract In this paper, an impulsive noise estimation algorithm for generating bit log‐likelihood ratios (LLRs) for channel coded systems in impulsive noise environments is proposed. This approach is to design the LLR detector in the maximum‐likelihood (ML) sense, which requires the parameters of the impulsive noise. The expectation‐maximisation (EM) algorithm is utilised to estimate the parameters of the Bernoulli–Gaussian (B–G) impulsive noise model. The estimated parameters is then used to generate the bit LLRs for the soft‐input channel decoder. Simulation results show that over a wide range of impulsive noise power, the proposed algorithm approaches the optimal performance (with ideal estimation) even under Middleton class‐A (M‐CA) impulsive noise models. |
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| ISSN: | 1751-8628 1751-8636 |