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2011•Unpublished venueRequires access

Reduction of sphere decoding complexity using an adaptive SD-OSIC system

Sherlie Portugal, Saransh Malik, Changwoo Seo, Cheolsung Kim, Intae Hwang

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Abstract

Sphere decoding is a technique able to achieve the optimal performance of the maximum likelihood decoder, but its high and variable complexity can make the practical implementation infeasible. In this paper, we present an adaptive system, called adaptive SD-OSIC, as a way of reducing the decoding complexity while maintaining the error performance of conventional sphere decoding.

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What this paper is about

Sphere decoding is a technique able to achieve the optimal performance of the maximum likelihood decoder, but its high and variable complexity can make the practical implementation infeasible. In this paper, we present an adaptive system, called adaptive SD-OSIC, as a way of reducing the decoding complexity while maintaining the error performance of conventional sphere decoding.

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Available abstract

Sphere decoding is a technique able to achieve the optimal performance of the maximum likelihood decoder, but its high and variable complexity can make the practical implementation infeasible. In this paper, we present an adaptive system, called adaptive SD-OSIC, as a way of reducing the decoding complexity while maintaining the error performance of conventional sphere decoding.

Key concepts: Decoding methods, Reduction (mathematics), Computer science, Variable (mathematics), Algorithm, Computational complexity theory, List decoding, Sequential decoding

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