Multiuser Receiver for Joint Symbol/Channel Estimation in Dual-Hop Relaying Systems

Han, Xi; Almeida, André L. F. de

doi:10.1007/s11277-015-2377-3

Cited by 8 publications

(5 citation statements)

References 17 publications

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“…In this section, 5000 Monte Carlo simulations are used to verify the performance of the proposed semiblind receiver. Te rMSEs of channel matrices are used to characterize the estimation performance [18,19].…”

Section: Simulation Resultsmentioning

confidence: 99%

A Semiblind Receiver for a Two-Way UAV-Aided PIC System Based on the PARAFAC Model

Han

Liu

et al. 2022

International Journal of Antennas and Propagation

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In this paper, we consider a two-way communication system using the unmanned aerial vehicle (UAV) as a relay (UAV-aided). This system eliminates impulse interference through an adaptive filter based on the least mean square (LMS) and uses the received signal transmitted by the UAVs to construct a parallel factor (PARAFAC) model. Based on the identifiability condition of the PARAFAC model, a pulse interference cancellation orthogonal pilot tensor (PIC-OPT) receiver without iteration is proposed. Our algorithm is also used in millimeter-wave to achieve the acquisition of channel information. Compared with the least squares method, the simulation results demonstrate the superiority of the proposed semiblind receiver in terms of the relative mean square error and bit error rate.

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Section: Simulation Resultsmentioning

confidence: 99%

A Semiblind Receiver for a Two-Way UAV-Aided PIC System Based on the PARAFAC Model

Han

Liu

et al. 2022

International Journal of Antennas and Propagation

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“…The property of uniqueness makes the CPD a basic tool for signal separation, and it is widely used in telecommunication, array processing, machine learning, etc. [15][16][17][18][19][20]. In [15], a novel multiuser receiver for joint symbol and channel estimation by capitalizing on a tensor modeling of the end-to-end system has been proposed.…”

Section: Introductionmentioning

confidence: 99%

“…[15][16][17][18][19][20]. In [15], a novel multiuser receiver for joint symbol and channel estimation by capitalizing on a tensor modeling of the end-to-end system has been proposed. The multiple invariance sensor array processing has been linked to the uniqueness of CPD in [20].…”

Section: Introductionmentioning

confidence: 99%

DOA and Polarization Parameters Estimation by Exploiting Canonical Polyadic Decomposition of Tensors

Liu

Xie

Zhang

2019

Wireless Communications and Mobile Computing

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A new algorithm to estimate the direction of arrival (DOA) and polarization parameters of signals impinging on an array with electromagnetic (EM) vector-sensors is presented by exploiting the canonical polyadic decomposition (CPD) of tensors. In addition to spatial and temporal diversities, further information from the polarization domain is considered and used in this paper. Estimation errors of these parameters are evaluated by the Cramér-Rao lower bound (CRB) benchmark, in the presence of additive white Gaussian noise (AWGN). The superiority of the proposed algorithm is shown by comparing with the derivative algorithms of MUSIC and ESPRIT. In the proposed algorithm, the parameters can be estimated by virtue of the diversities of the spatial and polarization belonging to the factor matrices, rather than the conventional subspace which is the foundation of MUSIC and ESPRIT. Additionally, the classical CPD algorithm based on Alternating Least Squares (ALS) is introduced to verify the efficacy of the proposed CPD algorithm. Results demonstrate that when the number of snapshots is greater than 50, the proposed algorithm requires a smaller number of snapshots to achieve a high level of performance, compared against the subspace-based algorithms and the ALS-based algorithm. Furthermore, in the matter of the array with a small number of sensors, the discovered advantage concerning the Root Mean Square Error (RMSE) in estimating the DOA and the polarization state of the signal is noteworthy.

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“…In [21], a three-hop one-way AF cooperative system was considered and a semi-blind receiver based on the PARATUCK-3 is proposed. The works [22] and [23] present tensor-based approaches for channel estimation and multiuser detection in cooperative MIMO systems, respectively.…”

Section: Introductionmentioning

confidence: 99%

Tensor-Based Multiuser Detection in Cooperative Multirelay Uplink

Peixoto

Fernandes

2019

JCIS

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In this paper, four tensor-based receivers for a multiuser multirelay cooperative uplink are proposed, with the relays employ the amplify-and-forward (AF) protocol and a time-spread coding. Two different scenarios are considered regarding the multiuser interference at the relays. When multiuser interference at the relays is ignored, a quadrilinear PARAFAC model is adopted for the received signals. Otherwise, a new tensor model called Nested PARAFAC-Tucker decomposition (NPT1D) is used to represent the received signals. The proposed receivers jointly estimate the transmitted symbols, channel gains and spatial signatures, two of them being based on the Alternating Least Squares (ALS) algorithm and two of them using the non-iterative Least Squares Khatri-Rao Factorization (LS-KRF) method. Uniqueness is discussed and simulation results are provided to illustrate the performance of the proposed techniques.

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Multiuser Receiver for Joint Symbol/Channel Estimation in Dual-Hop Relaying Systems

Cited by 8 publications

References 17 publications

A Semiblind Receiver for a Two-Way UAV-Aided PIC System Based on the PARAFAC Model

A Semiblind Receiver for a Two-Way UAV-Aided PIC System Based on the PARAFAC Model

DOA and Polarization Parameters Estimation by Exploiting Canonical Polyadic Decomposition of Tensors

Tensor-Based Multiuser Detection in Cooperative Multirelay Uplink

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