Browsing by Subject "Concatenated coding"

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Open Access
Channel combining and splitting for cutoff rate improvement
(Institute of Electrical and Electronics Engineers, 2006) Arikan, E.
The cutoff rate R0(W) of a discrete memoryless channel (DMC) W is often used as a figure of merit alongside the channel capacity C(W). If a channel W is split into two possibly correlated subchannels W1, W2, the capacity function always satisfies C(W1) + C(W2) ≤ C(W), while there are examples for which R0(W1) + R0(W2) > R0(W). The fact that cutoff rate can be "created" by channel splitting was noticed by Massey in his study of an optical modulation system. This paper gives a general framework for achieving similar gains in the cutoff rate of arbitrary DMCs by methods of channel combining and splitting. The emphasis is on simple schemes that can be implemented in practice. We give several examples that achieve significant gains in cutoff rate at little extra system complexity. Theoretically, as the complexity grows without bound, the proposed framework is capable of boosting the cutoff rate of a channel to arbitrarily close to its capacity in a sense made precise in the paper. Apart from Massey's work, the methods studied here have elements in common with Forney's concatenated coding idea, a method by Pinsker for cutoff rate improvement, and certain coded-modulation techniques, namely, Ungerboeck's set-partitioning idea and Imai-Hirakawa multilevel coding; these connections are discussed in the paper.
Open Access
Performance analysis of concatenated coding schemes
(1999) Akkor, Gün
In this thesis we concentrate on finding tight upperbounds on the output error rate of concatenated coding systems with binary convolutional inner codes and Reed-Solomon outer codes. Performance of such a system can be estimated by first calculating the error rate of the inner code and then by evaluating the outer code performance. Two new methods are proposed to improve the classical union bound on convolutional codes. The methods provide better error estimates in the low signal-to-noise ratio (SNR) region where the union bound increases abruptly. An ideally-interleaved system performance is evaluated based on the convolutional code bit error rate estimates. Results show that having better estimates for the inner code performance improves the estimates on the overall system performance. For the analysis of a non-interleaved system, a new model based on a Markov Chain representation of the system is proposed. For this purpose, distribution of errors between the inner and outer decoding stages is obtained through simulation. Markov Chain parameters are determined from the error distribution and output error rate is obtained by analyzing the behavior of the model. The model estimates the actual behavior over a considerable SNR range. Extensive computer simulations are run to evaluate the accuracy of these methods.