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Algorithmes de décodage pour les systèmes multi-antennes à complexité réduite

Rym Ouertani 1 
1 Communications numériques
LTCI - Laboratoire Traitement et Communication de l'Information
Abstract : In recent years, a great interest has been accorded to Multiple-Input Multiple-Output systems due to the large capacity they offer. Space-time codes are used to give a coding gain. A lattice representation of multi-antenna systems has been proposed, which make it possible to decode such systems using lattice decoders. Several decoders exist in the literature. Unfortunately, their complexity increases drastically with the lattice dimension and the constellation size. In our work, we propose a new sequential algorithm which combines the stack decoder search strategy and the sphere decoder search region. The proposed decoder that we call the Spherical-Bound-Stack decoder (SB-Stack) can be used to resolve lattice and large size constellations decoding. Furthermore, it outperforms the existing decoders in term of complexity while achieving ML performance. By introducing a bias parameter, the SB-Stack gives a range of performances from ML to ZF-DFE with proportional complexities. So, different performance/complexity trade-offs could be obtained. The proposed algorithm is given to decode space-time codes. However, when a channel coding is integrated to the transmission scheme, soft decoding becomes necessary. The SB-Stack is then extended to support soft-output detection over linear channels. A straightforward idea was to exploit internal nodes still stored in the stack at the end of hard decoding process to calculate LLR. We show that the potential gain of such method is rather large then classical soft decoders. For practical implementation, the decoding complexity is a critical point, but also the big variation of the complexity between low and high SNR (Signal to Noise Ratio) is an additional problem because of the variable decoding time. We propose an adaptive decoder based on the SB-Stack. This one switches between optimal and sub-optimal decoders according to the channel realization and the system specifications. This decoder has an almost constant complexity while keeping good performance. Lattice reduction is used to accelerate the decoding of infinite lattice. Using the MMSE-GDFE, it becomes possible to apply lattice reduction when finite constellations are considered. Therefore, interesting results are obtained when considering MIMO schemes combining the lattice reduction, the MMSE-GDFE process and the sequential decoders given previously.
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Submitted on : Monday, July 16, 2012 - 2:44:23 PM
Last modification on : Friday, July 31, 2020 - 10:44:11 AM
Long-term archiving on: : Thursday, December 15, 2016 - 11:52:10 PM


  • HAL Id : pastel-00718214, version 1


Rym Ouertani. Algorithmes de décodage pour les systèmes multi-antennes à complexité réduite. Théorie de l'information [cs.IT]. Télécom ParisTech, 2009. Français. ⟨pastel-00718214⟩



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