Enhanced Tensor Based Semi-blind Estimation Algorithm for Relay-Assisted MIMO Systems

Zhang, Jianshu; Nimr, Ahmad; Naskovska, Kristina; Haardt, Martin

doi:10.1007/978-3-319-22482-4_8

Cited by 5 publications

(15 citation statements)

References 11 publications

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“…For instance, let us assume the 4-way tensor A ∈ C I×J×M×N defined in equation ( 1). In the generalized unfolding [A] ([1,2], [3,4]) the 1-st mode varies faster than the 2-nd mode along the rows and the 3-rd mode varies faster than the 4-th mode along the columns. Moreover, for a tensor with a CP structure, its unfoldings and generalized unfoldings can be expressed in terms of the factor matrices.…”

Section: B the Cp Decomposition And Generalized Tensor Unfoldingsmentioning

confidence: 99%

“…In the generalized unfolding [A] ([1,2], [3,4]) the 1-st mode varies faster than the 2-nd mode between the rows and the 3-rd mode varies faster then the 4-th mode between the columns.…”

Section: Tensor Contractionmentioning

confidence: 99%

“…In the same way, some proposed tensor based models for MIMO-ODFM communication systems have only an element-wise or a slice-wise representation [3]. Further examples include the slice-wise description of MIMO communication systems using two-way relaying [4], [5]. This description of the signal models does not reveal the tensor structure explicitly.…”

Section: Introductionmentioning

confidence: 99%

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Using Double Contractions to Derive the Structure of Slice-Wise Multiplications of Tensors with Applications to Semi-Blind MIMO OFDM

Naskovska,

de Almeida,

Haardt

2020

Preprint

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The slice-wise multiplication of two tensors is required in a variety of tensor decompositions (including PARAFAC2 and PARATUCK2) and is encountered in many applications, including the analysis of multidimensional biomedical data (EEG, MEG, etc.) or multi-carrier MIMO systems. In this paper, we propose a new tensor representation that is not based on a slice-wise (matrix) description, but can be represented by a double contraction of two tensors. Such a double contraction of two tensors can be efficiently calculated via generalized unfoldings. It leads to new tensor models of the investigated system that do not depend on the chosen unfolding and reveal the tensor structure of the data model (such that all possible unfoldings can be seen at the same time). As an example, we apply this new concept to the design of new receivers for multicarrier MIMO systems in wireless communications. In particular, we consider MIMO OFDM systems with and without Khatri-Rao coding. The proposed receivers exploit the channel correlation between adjacent subcarriers, require the same amount of training symbols as traditional OFDM techniques, but have an improved performance in terms of the symbol error rate. Furthermore, we show that the spectral efficiency of the Khatri-Rao coded MIMO-OFDM can be increased by introducing "random coding" such that the "coding matrix" also contains useful information symbols. Considering this transmission technique, we derive a tensor model and two types of receivers for randomly coded MIMO-OFDM systems using the double contraction of two tensors.

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Section: B the Cp Decomposition And Generalized Tensor Unfoldingsmentioning

confidence: 99%

“…In the generalized unfolding [A] ([1,2], [3,4]) the 1-st mode varies faster than the 2-nd mode between the rows and the 3-rd mode varies faster then the 4-th mode between the columns.…”

Section: Tensor Contractionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Using Double Contractions to Derive the Structure of Slice-Wise Multiplications of Tensors with Applications to Semi-Blind MIMO OFDM

Naskovska,

de Almeida,

Haardt

2020

Preprint

Self Cite

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“…where K = (M D + JM D ) can be seen as the overall virtual number of antennas for the sake of receive diversity. From (6) and (13), the vertical concatenation of the signals from the direct link and relay link leads to…”

Section: Algorithm 1 Als-z [11]mentioning

confidence: 99%

“…Only recently the (semi-)blind estimation in relay AF MIMO systems has been proposed in the literature [10]- [13]. These works give one step ahead into the combination of the main aspects of the tensor-based works cited in the previous paragraph.…”

Section: Introductionmentioning

confidence: 99%

Combining Relay and Direct Links for Joint Symbol and Channel Estimation in MIMO Amplify-and-Forward (AF) Systems

Ximenes¹,

Almeida²

2016

Anais De XXXIV Simpósio Brasileiro De Telecomunicações

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The non-regenerative Amplify-and-Forward (AF) relaying is a powerful yet simple way to extend signal coverage in wireless communications. Without any decoding procedure, relay stations operating under this protocol offers a very small cost of deployment and operation in comparison with regenerative protocols. However, the AF protocol has its disadvantages, particularly the challenge of estimating the channel matrices that compose the relay link. Besides, few works were dedicated to estimate those channels without using bandwidth-consuming pilot symbols. We resort to a recent nested PARAFAC tensor modeling of the considered relay MIMO system, and then we propose a semi-blind receiver that combines the signals from the relay link with an eventual direct link, providing an improved symbol estimation along with the identification of the channels that compose the relaying network. Compared with an inspiring previous receiver that exploits the PARATUCK2 tensor model, our new receiver have presented consistent coding gains.

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Generalized tensor contraction with application to khatri-rao coded MIMO OFDM systems

Naskovska

Haardt

Almeida

2017

2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)

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Enhanced Tensor Based Semi-blind Estimation Algorithm for Relay-Assisted MIMO Systems

Cited by 5 publications

References 11 publications

Using Double Contractions to Derive the Structure of Slice-Wise Multiplications of Tensors with Applications to Semi-Blind MIMO OFDM

Using Double Contractions to Derive the Structure of Slice-Wise Multiplications of Tensors with Applications to Semi-Blind MIMO OFDM

Combining Relay and Direct Links for Joint Symbol and Channel Estimation in MIMO Amplify-and-Forward (AF) Systems

Generalized tensor contraction with application to khatri-rao coded MIMO OFDM systems

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