Reduced complexity sphere decoding via a reordered lattice representation

Authors:
Luay Azzam;Ender Ayanoglu
Affiliations:
Center for Pervasive Communications and Computing, Department of Electrical Engineering and Computer Science, University of California, Irvine, Irvine, CA;Center for Pervasive Communications and Computing, Department of Electrical Engineering and Computer Science, University of California, Irvine, Irvine, CA
Venue:
IEEE Transactions on Communications
Year:
2009

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Abstract

In this letter, we propose a reordering of the channel representation for Sphere Decoding (SD) where the real and imaginary parts of each jointly detected symbol are decoded independently. Making use of the proposed structure along with a scalar quantization technique, we reduce the decoding complexity substantially. We show that this approach achieves 85% reduction in the overall complexity compared to the conventional SD for a 2 × 2 system, and 92% reduction for the 4 × 4 and 6 × 6 cases at low SNR values, and almost 50% at high SNR, thus relaxing the requirements for hardware implementation.