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An Efficient Tree Search for Reduced Complexity Sphere Decoding

Summary: An Efficient Tree Search for Reduced Complexity
Sphere Decoding
Luay Azzam and Ender Ayanoglu
Center for Pervasive Communications and Computing
Department of Electrical Engineering and Computer Science
The Henry Samueli School of Engineering
University of California, Irvine
email: lazzam@uci.edu, ayanoglu@uci.edu
Abstract-- The complexity of sphere decoding (SD) has been
widely studied due to the importance of this algorithm in obtain-
ing 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


Source: Ayanoglu, Ender - Department of Electrical and Computer Engineering, University of California, Irvine


Collections: Engineering