Interleaver Construction Research Articles

On Progressive Edge-Growth Interleavers for Turbo Codes

In this letter, we show that the family of progressive edge growth interleavers ensures optimal growth of the minimum distance of turbo codes, which grows as log(N), where N is the interleaver size. This family of interleavers fits well the self-concatenated structure of turbo codes, hence it works with irregular turbo codes as well. We will start by introducing the self-concatenated structure of turbo codes. We then recall the progressive edge-growth interleaver construction, and we show that the minimum distance grows optimally with such interleavers. We end up by showing simulation comparisons with other families of interleavers.

Construction of turbo code interleavers from 3-regular hamiltonian graphs

In this letter, we present a new construction of interleavers for turbo codes from 3-regular Hamiltonian graphs. The interleavers can be generated using a few parameters, which can be selected in such a way that the girth of the interleaver graph (IG) becomes large, inducing a high summary distance. The size of the search space for these parameters is derived. The proposed interleavers themselves work as their de-interleavers.

Interleaver Design for Serially Concatenated Convolutional Codes: Theory and Application

This paper addresses the problem of interleaver design for serially concatenated convolutional codes (SCCCs) tailored to the constituent codes of the SCCC configuration. We present a theoretical framework for interleaver optimization based on a cost function closely tied to the asymptotic bit-error rate (BER) of the block code C/sub s/ resulting from proper termination of the constituent codes in the SCCC code. We define a canonical form of the interleaving engine denoted as the finite state permuter (FSP) and using its structural property, develop a systematic iterative technique for construction of interleavers. The core theoretical results focus on the asymptotic behavior of a class of cost functions and their martingale property, which is then used to develop an order recursive interleaver optimization algorithm. We address the issue of the complexity of the interleaver growth algorithm presented in the paper and demonstrate that it has polynomial complexity. Subsequently, we provide details about the application of the proposed technique and present a modification of the algorithm that employs error pattern feedback for improved performance at a reduced complexity. Sample experimental results are provided for an SCCC code of rate 1/3 and information block length 320 that achieves a minimum distance of d/sub min/=44.

Interleaver design method for turbo codes based on genetic algorithm

This paper describes a new interleaver construction technique for turbo code. The technique searches as much as possible pseudo-random interleaving patterns under a certain condition using genetic algorithms(GAs). The new interleavers have the superiority of the S-random interleavers and this interleaver construction technique can reduce the time taken to generate pseudo-random interleaving patterns under a certain condition. The results obtained indicate that the new interleavers yield an equal to or better performance than the S-random interleavers. Compared to the S-random interleaver, this design requires a lower level of computational complexity.

Interleaver Pruning for Construction of Variable-Length Turbo Codes

The issue of pruning (i.e., shortening) a given interleaver in a parallel concatenated convolutional code (PCCC or turbo codes) employing recursive systematic convolutional (RSC) constituent codes has been addressed. The encoder uses two RSC codes coupled with an interleaver represented by the permutation vector. Since the encoding and decoding delay associated with turbo codes are essentially dominated by the block length (interleaver length), it is of considerable practical interest to be able to modify it in order to obtain a variable length block code. Most other interleaver construction techniques do not have a recursive build nature and as a consequence, each time the interleaver length is modified, the interleaver itself must be redesigned. In the case of turbo codes, it is desirable to identify a technique that would allow any interleaver performing a given permutation to be reduced in size with gradual performance degradation of the resulting PCCC, but without the need for changing almost completely the operation of the interleaver.

Design of interleavers for turbo codes: iterative interleaver growth algorithms of polynomial complexity

This paper addresses the problem of designing interleavers for parallel concatenated convolutional codes (PCCCs) tailored to specific constituent codes. We start by establishing the role of the interleaver in the PCCC and the various parameters that influence the performance of the PCCC with a given interleaver. Subsequently, we define a canonical form of the interleaving engine denoted as the finite-state permuter (FSP) and demonstrate the minimal delay property of this canonical form. For any given permutation, we present a procedure for deriving the canonical FSP engine. We address the issue of implementation of the FSP and propose a very simple structure for the FSP. Next, using the structural property of the FSP engine, we develop a systematic iterative technique for construction of interleavers with a complexity that is polynomial in the interleaver size. Subsequently, we develop a cost function that, coupled with the iterative interleaver growth procedure, can be used to design optimized interleavers for PCCCs. We provide examples of application of the interleaver design technique, and compare the designed interleavers with some of the interleavers of comparable size found in the literature.