Low-Complexity Recursive Least-Squares Adaptive Algorithm Based on Tensorial Forms

Fîciu, Ionuț-Dorinel; Stanciu, Cristian-Lucian; Anghel, Cristian; Elisei-Iliescu, Camelia

doi:10.3390/app11188656

Cited by 7 publications

(11 citation statements)

References 25 publications

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“…Moreover, the computational complexity of the two schemes was computed based on the summation of the number of computations in the operations including additions/subtractions, multiplications/divisions, and XOR operations based on [ 40 , 55 , 56 , 57 , 58 , 59 ]. Because of the identity and symmetry at the transmitter side, this paper only considered calculating the total number of computations at the receiver side.…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

Joint Semi-Blind Self-Interference Cancellation and Equalisation Processes in 5G QC-LDPC-Encoded Short-Packet Full-Duplex Transmissions

Vuong

Gautier

et al. 2022

Sensors

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The paper proposes a joint semi-blind algorithm for simultaneously cancelling the self-interference component and estimating the propagation channel in 5G Quasi-Cyclic Low-Density Parity-Check (QC-LDPC)-encoded short-packet Full-Duplex (FD) transmissions. To avoid the effect of channel estimation processes when using short-packet transmissions, this semi-blind algorithm was developed by taking into account only a small number (four at least) pilot symbols, which was integrated with the intended information sequence and used for the feedback loop of the estimation of the channels. The results showed that this semi-blind algorithm not only achieved nearly optimal performance, but also significantly reduced the processing time and computational complexity. This semi-blind algorithm can also improve the performances of the Mean-Squared Error (MSE) and Bit Error Rate (BER). The results of this study highlight the potential efficiency of this joint semi-blind iterative algorithm for 5G and Beyond and/or practical IoT transmission scenarios.

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Section: Simulation Results and Discussionmentioning

confidence: 99%

Joint Semi-Blind Self-Interference Cancellation and Equalisation Processes in 5G QC-LDPC-Encoded Short-Packet Full-Duplex Transmissions

Vuong

Gautier

et al. 2022

Sensors

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“…Thus, nearly two-third or ∼ 0.65 times reduce in processing time of the partial feedback scheme JIB_DSICED3_PF is shown in 3. Moreover, the computational complexity of three schemes are analyzed based on the summation of the number of computation in operations including additions/subtractions, multiplications/divisions, XOR operation based on [31], [48]- [52]. Because of the identity and symmetric at the transmitter side, this paper only considers to calculate the total number of computations at the receiver side.…”

Section: Comparison Of Processing Time and Computational Complexitymentioning

confidence: 99%

Joint Iterative Blind Self-Interference Cancellation, Propagation Channel Estimation and Decoding Processes in Full-Duplex Transmissions

et al. 2022

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The paper proposes a joint blind iterative Self-Interference (SI) cancellation, propagation channel estimation and decoding algorithm in Full-Duplex (FD) transmissions via feedback of channel estimates and decoded messages combined with the process of Digital Self-Interference Cancellation (DSIC). Different from the conventional algorithm, the proposed blind algorithm simultaneously estimates the self-interference and propagation channels and decodes messages in each decoding iteration of 5G Quasi-Cyclic Low Density Parity Check (QC-LDPC) codes. The temporary propagation channel estimate and decoded message are fed back to improve the self-interference cancellation and also the channel estimation as well as decoding in the next iteration. The results show that the proposed algorithm outperforms the conventional algorithm, especially at high signal to noise ratio (SNR) and small number of symbols, and requires much less processing time and computational complexity while achieving the convergence performance. The results also show that the proposed algorithm is less sensitive to SI level than the conventional algorithm. The paper further proposes a partial feedback scheme, which only use few feedback symbols for channel estimation, to significantly reduce the processing time and computational complexity while maintaining the performance. These good properties seem quite suitable for a use of this proposed blind iterative algorithm for short-length packet FD transmissions in Internet-of-Things (IoT) applications and green communications.

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“…The expression in (3) will be further developed in order to obtain a more intuitive form. The vectors h i will be combined using the outer product •, which can be expressed for two vectors as [15,18]. A new tensor H ∈ R L…”

Section: System Contextmentioning

confidence: 99%

“…In [18,26], the nature of the described MISO systems was exploited by splitting the problem of identifying g into multiple smaller problems, which target the separate estimation of the h i systems. The tracking capabilities proved to be drastically improved using considerable less arithmetic effort, with respect to the classical one-filter configurations.…”

Section: System Contextmentioning

confidence: 99%

“…Another tensor-based efficient adaptive filter that employs the combination between the RLS algorithm and the dichotomous coordinate descent (DCD) iterations, namely RLS-DCD-T [18], has been recently released. This algorithm uses a tensorial decomposition for multilinear forms and it has proven to be a powerful solution for tensor-based leastsquares adaptive systems with low-complexity [19,20].…”

Section: Introductionmentioning

confidence: 99%

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Tensor-Based Recursive Least-Squares Adaptive Algorithms with Low-Complexity and High Robustness Features

et al. 2022

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The recently proposed tensor-based recursive least-squares dichotomous coordinate descent algorithm, namely RLS-DCD-T, was designed for the identification of multilinear forms. In this context, a high-dimensional system identification problem can be efficiently addressed (gaining in terms of both performance and complexity), based on tensor decomposition and modeling. In this paper, following the framework of the RLS-DCD-T, we propose a regularized version of this algorithm, where the regularization terms are incorporated within the cost functions. Furthermore, the optimal regularization parameters are derived, aiming to attenuate the effects of the system noise. Simulation results support the performance features of the proposed algorithm, especially in terms of its robustness in noisy environments.

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Low-Complexity Recursive Least-Squares Adaptive Algorithm Based on Tensorial Forms

Cited by 7 publications

References 25 publications

Joint Semi-Blind Self-Interference Cancellation and Equalisation Processes in 5G QC-LDPC-Encoded Short-Packet Full-Duplex Transmissions

Joint Semi-Blind Self-Interference Cancellation and Equalisation Processes in 5G QC-LDPC-Encoded Short-Packet Full-Duplex Transmissions

Joint Iterative Blind Self-Interference Cancellation, Propagation Channel Estimation and Decoding Processes in Full-Duplex Transmissions

Tensor-Based Recursive Least-Squares Adaptive Algorithms with Low-Complexity and High Robustness Features

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