Semi-Blind Receivers for Non-Regenerative Cooperative MIMO Communications Based on Nested PARAFAC Modeling

Abstract : In cooperative communication systems, multiple-input multiple-output (MIMO) amplify-and-forward (AF) relaying is a promising solution for upcoming wireless standards due to its intrinsic benefits in terms of extended coverage and increased spatial diversity. However, the deployment of MIMO AF relays faces some key challenges such as the need of channel state information (CSI) for the partial channels associated with the different communication links, which is required by some transmit optimization techniques. In this paper, we consider a one-way two-hop MIMO AF cooperative scheme employing space-time(ST) codings at thet ransmitter and relay nodes. First, we formulate a nested PARAFAC model for the tensor of signals received at destination. A theoretical study on the identifiability and uniqueness issues for the nested PARAFAC model is also carried out. Then, two iterative semi-blind receivers that exploit differently the algebraic properties of this model are formulated for a joint channel and symbol estimation at the destination. Uniqueness and least squares identifiability conditions are derived for these receivers, and their computational complexities are analyzed. Simulation results evaluate the bit error rate and the channel estimation accuracy obtained with the proposed semi-blind receivers, corroborating the performance improvements over recent semi-blind and supervised competitors,thanks to the use of a double Khatri-Rao coding associated with the source and relay nodes.
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Article dans une revue
IEEE Transactions on Signal Processing, 2015, 63 (18), pp.4985-4998. <10.1109/TSP.2015.2454473>
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https://hal.archives-ouvertes.fr/hal-01246037
Contributeur : Gérard Favier <>
Soumis le : jeudi 17 décembre 2015 - 23:58:54
Dernière modification le : vendredi 18 décembre 2015 - 01:11:59

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Leandro Ximenes, Gérard Favier, André De Almeida. Semi-Blind Receivers for Non-Regenerative Cooperative MIMO Communications Based on Nested PARAFAC Modeling. IEEE Transactions on Signal Processing, 2015, 63 (18), pp.4985-4998. <10.1109/TSP.2015.2454473>. <hal-01246037>

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