Low-Complexity Interleaver Design for Turbo Codes

Abstract

A low-complexity method of interleaver design, sub-vector interleaving, for both parallel and serially concatenated convolutional codes (PCCCs and SCCCs, respectively) is presented here. Since the method is low-complexity, it is uniquely suitable for designing long interleavers.

Sub-vector interleaving is based on a dynamical system representation of the constituent encoders employed by PCCCs and SCCCs. Simultaneous trellis termination can be achieved with a single tail sequence using sub-vector interleaving for both PCCCs and SCCCs. In the case of PCCCs, the error floor can be lowered by sub-vector interleaving which allows for an increase in the weight of the free distance codeword and the elimination of the lowest weight codewords generated by weight-2 terminating input sequences that determine the error floor at low signal-to-noise ratios (SNRs). In the case of SCCCs, sub-vector interleaving lowers the error floor by increasing the weight of the free distance codewords. Interleaver gain can also be increased for SCCCs by interleaving the lowest weight codewords from the outer into non-terminating input sequences to the inner encoder.

Sub-vector constrained S-random interleaving, a method for incorporating S-random interleaving into sub-vector interleavers, is also proposed. Simulations show that short interleavers incorporating S-random interleaving into sub-vector interleavers perform as well as or better than those designed by the best and most complex methods for designing short interleavers. A method for randomly generating sub-vector constrained S-random interleavers that maximizes the spreading factor, S, is also examined.

The convergence of the turbo decoding algorithm to maximum-likelihood decisions on the decoded input sequence is required to demonstrate the improvement in BER performance caused by the use of sub-vector interleavers. Convergence to maximum-likelihood decisions by the decoder do not always occur in the regions where it is feasible to generate the statistically significant numbers of error events required to approximate the BER performance for a particular coding scheme employing a sub-vector interleaver. Therefore, a technique for classifying error events by the mode of convergence of the decoder is used to illuminate the effect of the sub-vector interleaver at SNRs where it is possible to simulate the BER performance of the coding scheme.