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Complexity analysis for ML-based sphere decoder achieving avanishing performance-gap to brute force ML decoding
EURECOM, France. (Mobile Communications Department)
EURECOM, France. (Mobile Communications Department)
KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0001-6630-243X
2012 (English)Conference paper (Refereed)
Abstract [en]

This work identifies the computational reserves required for the maximum likelihood (ML)-based sphere decoding solutions that achieve, in the high-rate and high-SNR limit, a vanishing gap to the error-performance of the optimal brute force ML decoder. These error performance and complexity guarantees hold for most multiple-input multiple-output scenarios, all reasonable fading statistics, all channel dimensions and all full-rate lattice codes. The analysis also identifies a ratereliability- complexity tradeoff establishing concise expressions for the optimal diversity gain achievable in the presence of any run-time constraint imposed due to the unavailability of enough computational resources required to achieve a vanishing gap.

Place, publisher, year, edition, pages
2012. 127-130 p.
National Category
URN: urn:nbn:se:kth:diva-107471DOI: 10.3929/ethz-a-007071378OAI: diva2:576034
International Zürich Seminar on Communications (IZS)
ICT - The Next Generation

QC 20130118

Available from: 2012-12-12 Created: 2012-12-12 Last updated: 2013-04-11Bibliographically approved

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Jaldén, Joakim
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Signal ProcessingACCESS Linnaeus Centre

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