Semi-Supervised Receivers for MIMO Systems with Multiple Khatri-Rao Coding

Pinho, Pablo H. de; Maria, Fiqih; Favier, Gérard; Paulo, C L da Costa Joao; Andre, L F de Almeida; Maranhão, João Paulo A.

doi:10.1109/icspcs47537.2019.9008759

Cited by 1 publication

(4 citation statements)

References 12 publications

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“…Thus, increasing the time span of one matrix leads to a performance improvement on the detection of the other matrix. A similar behavior was observed in the KRF-KRF receiver of [18].…”

Section: Simulation Results and Discussionsupporting

confidence: 78%

“…, and ν = 16. In Figures 1 and 2, we compare SER and NMSE performances of the proposed receiver CTALS with: (i) the tradi-tional trilinear ALS (TALS) [16] and multidimensional Khatri-Rao factorization [19] of three matrices (KRF3) methods for systems that employ MKRST coding [17], [18]; (ii) the twostage KRF-KronF receiver [17]; (iii) the single-stage BALS (bilinear ALS) assuming a perfect knowlegde of the MIMO channel matrix to estimate the individual symbol matrices. More specifically, this receiver is a bilinear version of what is designed from Algorithm 1.…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

“…Therein, a one-way two-hop MIMO relay system with codings both at the source and relay nodes was considered and semiblind receivers based on a trilinear PARAFAC-based model were presented. In [18], the authors proposed a two-stage iterative and non-iterative semi-supervised receivers for a MKRST coding based MIMO system, still using a trilinear PARAFAC modeling approach.…”

Section: Introductionmentioning

confidence: 99%

“…At the destination, we derive a new semi-supervised receiver that exploits a constrained quadrilinear PARAFAC model. In contrast to [17] and [18], which resorts to trilinear PARAFAC models and estimate the transmitted symbols and channels in two stages, our proposed semi-supervised receiver jointly and directly estimates the transmitted symbol and channel matrices by means of a single-stage iterative alternating least squares algorithm. Our numerical results corroborate the performance improvement of the proposed received in terms of symbol error rate over competing solutions, such as the one proposed in [17] while comparing to the its version with perfect channel knowledge.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Semi-Supervised Receiver for MIMO Systems with Mixed Khatri-Rao-Kronecker Coding

Magalhaes¹,

Gomes²,

Almeida³

2020

Anais De XXXVIII Simpósio Brasileiro De Telecomunicações E Processamento De Sinais

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In this work, we propose a multiple Kronecker product-based space-time (MKronST)-based coding for singlehop point-to-point multiple-input multiple-output (MIMO) systems that employ space-time spreading scheme whose certain number of data streams are spatially spread within the antennas of a subarray while other ones are spread across antennas of different subarrays. Capitalizing on a tensor formalism, the received signals are modelled as a constrained quadrilinear parallel factor (PARAFAC) model, which allows us to derive a semi-supervised iterative receiver for joint symbol and channel estimation. Simulation results are provided to evaluate the performance of the proposed receiver. Our numerical results show that the proposed semi-supervised receiver is capable of jointly estimating the symbol and channel matrices with a superior performance in comparison to competing receivers outlined in the literature.

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“…Thus, increasing the time span of one matrix leads to a performance improvement on the detection of the other matrix. A similar behavior was observed in the KRF-KRF receiver of [18].…”

Section: Simulation Results and Discussionsupporting

confidence: 78%