Improving the Constituent Codes of Turbo Encoders

The performance of Turbo codes can be improved by choosing the best constituent encoder. Previous lists of the best constituent codes were found based on maximising the input weight two effective free distance d 2 . We show that minimising the number of nearest neighbours N 2 is also an important requirement. If there are multiple codes having the same d 2 and N 2 , we show that the minimum distance dmin can be a useful criteria to identify the best code. A list of generator polynomials suitable for Turbo codes are presented in this paper which satisfy the criteria mentioned above. The previously published results are also extended to include larger memory. 1 Introduction Since the first introduction of Turbo codes in 1993 there has been a large amount of research on both improving performance and reducing complexity of Turbo codes [1]. Turbo codes are a new class of codes which consists of two or more recursive systematic convolutional codes with each input being permuted by an inte..