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2008
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An Efficient Tree Search for Reduced Complexity Sphere Decoding

8 years 2 months ago
An Efficient Tree Search for Reduced Complexity Sphere Decoding
The complexity of sphere decoding (SD) has been widely studied due to the importance of this algorithm in obtaining the optimal Maximum Likelihood (ML) performance with lower complexity. In this paper, we propose a proper tree search traversal technique that reduces the overall SD computational complexity without sacrificing the performance. We exploit the similarity among the complex symbols in a square QAM lattice representation and rewrite the squared norm ML metric in a simpler form allowing significant reduction of the number of operations required to decode the transmitted symbols. We also show that this approach achieves > 45% complexity gain for systems employing 4-QAM, and that this gain becomes bigger as the constellation size is larger.
Luay Azzam, Ender Ayanoglu
Added 08 Dec 2010
Updated 08 Dec 2010
Type Conference
Year 2008
Where GLOBECOM
Authors Luay Azzam, Ender Ayanoglu
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