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Non-orthogonal multiple access (NOMA) has emerged as a promising technology that allows for multiplexing several users over limited time-frequency resources. Among existing NOMA methods, sparse code multiple access (SCMA) is especially attractive; not only for its coding gain using suitable codebook design methodologies, but also for the guarantee...
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... A positive definite kernel on a set χ is a function K that associates two objects to a real number [15]. Kernels can also be viewed from the functional analysis view point, since to each kernel K on χ is associated a Hilbert space Hk of real-valued functions on χ. ...
The subject matter of the article is to identify and equalize the parameters of telecommunication channels. The goal is to develop a new mathematical approach based on positive definite kernels on a Hilbert space. The tasks to be solved are: (a) to formulate a mathematical procedure based on a kernel; a kernel is a function that maps pairs of data points to a scalar value, and positive definite kernels are widely used in machine learning and signal processing applications; (b) to identify the channel parameters using the proposed method; and (c) to apply the Zero Forcing and MMSE equalizer to measure the performance of the proposed system. This article introduces a new method to address the problem of supervised identification of transmission channel parameters based on the positive definite kernel on Hilbert space, which implements Gaussian kernels. The input sequence, used as an input for a system or process, is assumed to be independent, have a zero mean, a non-Gaussian distribution, and be identically distributed. These assumptions are made to simplify the analysis and modeling. The proposed method for estimating the parameters of the channel impulse response yields promising results, indicating that the estimated parameters are close to the measured parameters of the model for various channels. The convergence of the estimated parameters toward the measured parameters of the model is particularly noticeable for BRAN A (indoor) and BRAN E (outdoor) channels. The method has been tested with different channel models, and the results remain consistent. Overall, the proposed method appears to be a reliable and effective approach for estimating channel impulse response parameters. The accuracy of the estimated parameters is particularly noteworthy considering the challenges inherent in modeling wireless channels, which can be influenced by various factors such as obstacles and interference. These findings have important implications for the design and optimization of wireless communication systems. Accurate estimates of channel impulse response parameters are essential for predicting and mitigating the effects of channel distortion and interference, and the proposed method represents a promising tool for achieving this goal. Further research and testing are needed to validate and refine the method and to explore its potential applications in different settings and scenarios. We evaluated the performance of the system using the estimated parameters obtained from the proposed method. Two equalizers, MMSE and ZF, were used, and the results show that MMSE outperforms ZF. Both equalizers produced highly satisfactory outcomes.
... The traditional MPA decoder is used in this study, which is well-known in the literature and can be found in [37][38][39][40][41]. Since no novel decoder is suggested in this investigation, the MPA is just given a brief. ...
This paper presents Discrete Wavelet Transformed Sparse Code Multiple Access (DWT-SCMA) in Power Line Communication (PLC) systems. In the present internet of things era, PLC provides an established infrastructure for low-cost and reliable indoor connectivity. PLC systems can benefit from the Sparse Code Multiple Access (SCMA) technique, which allows multiple users to access a frequency slot simultaneously to maximize spectrum efficiency. However, interuser interference arises in SCMA when numerous users map their data to the same frequency resource; this, in turn, is likely to be enhanced by the noisy PLC channel. This article adopts the intriguing aspects of DWT to address the interference difficulties. A mathematical model of the proposed technique is also presented and compared with Fast Fourier Transformed SCMA (FFT-SCMA). In the PLC environment, DWT-SCMA is found to outperform FFT-SCMA
Non-orthogonal multiple access (NOMA) has been proposed as a potential enabler for massive connectivity. Among the different NOMA schemes, power-domain (PD-NOMA) is particularly appealing as it improves user fairness while enhancing spectral efficiency. However, the practical implementation of NOMA faces several challenges, including radio frequency impairments, such as power-amplifier (PA) nonlinearity, which can limit its performance. In this paper, we study the impact of PA nonlinearity on the detection performance of PD-NOMA, and propose a random Fourier feature (RFF) based solution to mitigate the effects of such imperfections. Computer simulations carried out assuming different PA nonlinearity types demonstrate that the proposed RFF based algorithm considerably improves the BER performance and achieves results that are close to the ideal case. Lastly, the analytical proof of our proposed algorithm's performance is provided to support our simulation results.
