Repeat-puncture superorthogonal convolutional turbo codes in AWGN channel

Abstract

In this paper we study the use of repeat- puncture superorthogonal convolutional turbo codes in an additive white Gaussian noise (AWGN) channel. The performance of turbo codes (TC) have been shown to be near the theoretical limit in the AWGN channel. By using orthogonal signaling, which allows for bandwidth expansion, the performance of the turbo coding scheme can be improved even further. Since this is a low-rate code, the code is mainly suitable for spread-spectrum modulation applications. In classical turbo codes the frame length is set equal to the interleaver size, however, the codeword distance spectrum of turbo codes improves with an increasing interleaver size. It has been reported that the performance of turbo codes can be improved by using repetition and puncturing. Repeat-puncture turbo codes (RPTC) have shown a significant increase in performance at moderate to high signal-to-noise ratios. In this paper, we study the use of orthogonal signaling and parallel concatenation together with repetition and puncturing to improve the performance of superorthogonal convolutional turbo codes for reliable and effective communications. Simulation results in AWGN channel are presented together with analytical upper bounds, which have been derived using transfer function bounding techniques.