Tensor-Train Modeling for Mimo-OFDM Tensor Coding-and-Forwarding Relay Systems

Yassine Zniyed (1) , Remy Boyer (2) , André L. F. de Almeida (3) , Gérard Favier (4)

1 L2S - Laboratoire des signaux et systèmes
2 CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189
3 GTEL - Wireless Telecom Research Group [Fortaleza]
4 Laboratoire I3S - SIS - Signal, Images et Systèmes

In this paper, we consider a new one-way two-hop amplify-and-forward (AF) relaying scheme with a tensor space-time coding under frequency-selective fading channels. The signals received at the destination of the multi-input multi-output (MIMO) system define a 6-order tensor which satisfies a tensor-train decomposition (TTD). We propose a new TTD based receiver for a joint channel and symbol estimation. The proposed receiver avoids the use of long training sequences and resort to very few pilots to provide unique estimates of the individual channel matrices and the symbol matrix. Numerical simulations show the performance of the new proposed TTD-based semi-blind receiver.

Mots clés: tensor-train decomposition; tensor coding; MIMO relay systems; Channel estimation; semi-blind receiver

Domaines: Sciences de l'ingénieur [physics]; Traitement du signal et de l'image [eess.SP]

Yassine Zniyed, Remy Boyer, André L. F. de Almeida, Gérard Favier. Tensor-Train Modeling for Mimo-OFDM Tensor Coding-and-Forwarding Relay Systems. EUSIPCO 2019 - 27th European Signal Processing Conference, Sep 2019, A Coruna, Spain. ⟨10.23919/eusipco.2019.8902770⟩. ⟨hal-02146466⟩