A Practical Method for BEP Estimation of Convolutional Coding in Impulse Noise Environments

Forward error correction is a means to achieve robust communications. Knowing the performance of the error correcting code under operating circumstances is crucial in making a robust and cost-efficient design choice. Performance of error correcting codes are usually attained under the assumption of additive white Gaussian noise (AWGN). Such performance estimates can be orders of magnitude from the truth in impulse noise environments, that are common in military, automotive and industrial environments with lots of emitters and electronic equipment co-located closely together. A method previously proposed to model the impact of impulse noise, without the use of error correcting coding, is the impulsiveness correction factor (ICF), which can easily be measured. The main contribution of this work is to propose a practical method, using the ICF, to approximate the communication performance in impulse noise channels for a system using convolutional coding. Performance is evaluated in terms of bit error probability (BEP) at a given signal-to-noise ratio (SNR), or analogously the required SNR to achieve a given BEP. The proposed method is practically useful for a wide range of interference types, and is derived numerically since the problem is analytically intractable. The proposed method uses the ICF of the uncoded system, code performance estimates for AWGN, and knowledge of the code parameters.