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Nested Tucker tensor decomposition with application to MIMO relay systems using tensor space-time coding (TSTC)
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DOI：10.1016/j.sigpro.2016.04.009.png)
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Abstract
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The aim of this paper is twofold. In a first part, we present a new tensor decomposition that we call Tucker train decomposition or nested Tucker decomposition (NTD). NTD can be viewed as a particular case of tensor-train decomposition recently proposed for representing and approximating high-dimensional tensors in a compact way. NTD of a fourth-order tensor is more specially analysed in terms of parameter estimation and uniqueness issue. In a second part, We show that the use of a tensor space-time coding (TSTC) structure at both the source node and the relay node of a one-way two-hop multi input multi-output (MIMO) relay communication system leads to a nested Tucker decomposition of the fourth-order tensor formed by the signals received at the destination. Two semi-blind receivers are then proposed for jointly estimating the transmitted information symbols and the two individual relay channels. The first one is iterative, based on a three-step alternating least squares (ALS) algorithm, whereas the second one; denoted 2LSKP, is a closed-form solution based on the LS estimations of two Kronecker products. Two supervised receivers are also derived by using a (short) pilot-assisted closed form solution for calculating channel estimates. These estimates are exploited either for initializing the ALS receiver or for designing a zero-forcing (ZF) receiver. Extensive Monte Carlo simulation results are provided to demonstrate the performance of the proposed relay system. (C) 2016 Elsevier B.V. All rights reserved.
Keywords:
Channel estimation
Nested Tucker model
MIMO systems
Relay systems
Semi-blind receivers
Space-time coding
Symbol estimation
Tensor decompositions
Tensor coding
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