Reduced Complexity Sphere Decoding for Square QAM via a New Lattice Representation - Computer Science > Information TheoryReport as inadecuate




Reduced Complexity Sphere Decoding for Square QAM via a New Lattice Representation - Computer Science > Information Theory - Download this document for free, or read online. Document in PDF available to download.

Abstract: Sphere decoding (SD) is a low complexity maximum likelihood (ML) detectionalgorithm, which has been adapted for different linear channels in digitalcommunications. The complexity of the SD has been shown to be exponential insome cases, and polynomial in others and under certain assumptions. The sphereradius and the number of nodes visited throughout the tree traversal search arethe decisive factors for the complexity of the algorithm. The radius problemhas been addressed and treated widely in the literature. In this paper, wepropose a new structure for SD, which drastically reduces the overallcomplexity. The complexity is measured in terms of the floating pointoperations per second (FLOPS) and the number of nodes visited throughout thealgorithm tree search. This reduction in the complexity is due to the abilityof decoding the real and imaginary parts of each jointly detected symbolindependently of each other, making use of the new lattice representation. Wefurther show by simulations that the new approach achieves 80% reduction in theoverall complexity compared to the conventional SD for a 2x2 system, and almost50% reduction for the 4x4 and 6x6 cases, thus relaxing the requirements forhardware implementation.



Author: Luay Azzam, Ender Ayanoglu

Source: https://arxiv.org/







Related documents