Abstract
The use of turbo codes enhances the data transmission efficiency and optimizes the performance of a communication system over wireless fading channels. In this paper, we present a brief overview of the various components of the turbo coding scheme, analyze the complexities of the most popular turbo decoding algorithms, and discuss the various implementation methods of the maximum a posteriori (MAP) algorithm. The paper considers the well-known log-MAP decoding algorithm by a linear approximation of the correction function used by the max* operator. We propose a generalized decoding scheme that optimizes the existing MAP algorithm for faster convergence and better throughput on the basis of varying channel conditions. The proposed scheme of decoding reduces complexity and enhances the throughput with only a negligible loss in BER performance.
Highlights
Increasing demand of bandwidth and support of multimedia traffic in mobile/wireless environment has developed the need of further improvement of wireless communication system performance
We present a brief overview of the various components of the turbo coding scheme, analyze the complexities of the most popular turbo decoding algorithms, and discuss the various implementation methods of the maximum a posteriori (MAP) algorithm
This paper evaluates above decoding schemes and proposes an adaptive turbo decoding architecture, and named it as generalized turbo decoder
Summary
Increasing demand of bandwidth and support of multimedia traffic in mobile/wireless environment has developed the need of further improvement of wireless communication system performance. The performance of iterative turbo decoder approaches near Shannon-capacity with increased number of iterations, which introduces computational delay in the system resulting in reduced throughput. The focus of this paper is on developing adaptive turbo decoder for reducing computational delay and improving throughput of the system [2]. For favorable channel conditions fast converging and least complex algorithm is selected, such as max-log-MAP. Meticulous selection of decoding algorithms results in reduced computational delay, and improving throughput, which are complemented by simulation results. The proposed decoder selects the appropriate decoding algorithm and optimizes the decoding performance, on the basis of channel conditions.
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