A method for decoding a receive signal carrying at least one encoded data value, the receive signal having a non-AWGN and an AWGN noise component, the method comprising: deriving a second likelihood value based on a first likelihood value for the encoded data value and an effective error probability of a transmission path of the receive signal, the transmission path being assumed to comprise H sub-paths with H being an integer, wherein the first likelihood value is based on the AWGN noise component which is related to the first H-1 sub-paths being modelled as BSC channels, the effective error probability representing the accumulated error probabilities of the first H-1 sub-paths; the method characterized by: deriving a decoded data value based on the second likelihood value; and estimating the effective error probability using the first likelihood value, a hard decision of the decoded data value and a noise power of the AWGN noise component by: combining the first likelihood value and the hard decision of a decoded data value to obtain a combined value; providing a hard decision based on the combined value; keeping first and second count values which are respectively increased according to the positive and negative hard decision values on successive combined values; computing a count ratio on the first count value and a sum of the first and second count values; and determining an approximation of the effective error probability based on the count ratio and the noise power of the AWGN noise component in the received signal. deriving a second likelihood value based on a first likelihood value for the encoded data value and an effective error probability of a transmission path of the receive signal, the transmission path being assumed to comprise H sub-paths with H being an integer, wherein the first likelihood value is based on the AWGN noise component which is related to the first H-1 sub-paths being modelled as BSC channels, the effective error probability representing the accumulated error probabilities of the first H-1 sub-paths; the method characterized by: deriving a decoded data value based on the second likelihood value; and estimating the effective error probability using the first likelihood value, a hard decision of the decoded data value and a noise power of the AWGN noise component by: combining the first likelihood value and the hard decision of a decoded data value to obtain a combined value; providing a hard decision based on the combined value; keeping first and second count values which are respectively increased according to the positive and negative hard decision values on successive combined values; computing a count ratio on the first count value and a sum of the first and second count values; and determining an approximation of the effective error probability based on the count ratio and the noise power of the AWGN noise component in the received signal. deriving a decoded data value based on the second likelihood value; and estimating the effective error probability using the first likelihood value, a hard decision of the decoded data value and a noise power of the AWGN noise component by: combining the first likelihood value and the hard decision of a decoded data value to obtain a combined value; providing a hard decision based on the combined value; keeping first and second count values which are respectively increased according to the positive and negative hard decision values on successive combined values; computing a count ratio on the first count value and a sum of the first and second count values; and determining an approximation of the effective error probability based on the count ratio and the noise power of the AWGN noise component in the received signal. combining the first likelihood value and the hard decision of a decoded data value to obtain a combined value; providing a hard decision based on the combined value; keeping first and second count values which are respectively increased according to the positive and negative hard decision values on successive combined values; computing a count ratio on the first count value and a sum of the first and second count values; and determining an approximation of the effective error probability based on the count ratio and the noise power of the AWGN noise component in the received signal.