MIMO-OFDM system with impulsive noise reduction technique based on auto level Selection Mechanism

Hakam, Ali; Khalid, Mohammed; Aly, Noha Abou; Jimaa, Shihab; Al-Araji, Saleh R.

doi:10.1109/icct.2013.6820377

Cited by 3 publications

(2 citation statements)

References 6 publications

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“…However, there is a strong correlation between the GSNR value and the optimal kernel size. Since GSNR is related to the γ parameter of the impulsive noise model, as indicated by Equation (16), this parameter must be estimated as accurately as possible at the receiver.…”

Section: A Kernel Size Adjustmentmentioning

confidence: 99%

“…Recently, some works have investigated the MIMO transmission technique in non-Gaussian scenarios. The authors in [16] presented an adaptive reception technique based on the use of an impulsive noise level detector. On the other hand, the work developed in [17] introduces an alternative solution to the same problem using an adaptive reception technique through adaptive recursive least mean square (RLS), adaptive normalized least mean square (NLMS), and variable stepsize adaptive normalized least mean (VSNLMS) algorithms, which aim to minimize the effect of impulsive noise on the system performance.…”

Section: Introductionmentioning

confidence: 99%

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A Novel Signal Detector in MIMO Systems Based on Complex Correntropy

et al. 2019

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In cellular systems, information signals must be transmitted at high rates and with high reliability. One of the possible solutions to meet such criteria is the use of systems with multiple transmitting and/or receiving antenna arranged in the form of a multiple-input, multiple-output (MIMO) system. However, signal processing techniques in MIMO systems are developed under the assumption of transmission on Gaussian channels, which may lead to the decrease of efficiency in non-Gaussian communication scenarios. In this context, the widespread use of MIMO systems in recent years has motivated the development of new processing techniques that can be employed in scenarios that also consider the presence of non-Gaussian noise in communication channels. This work proposes a novel signal detection technique for MIMO systems, which is called maximum correntropy detector (MCD), being adequate to environments characterized by Gaussian and non-Gaussian noise. The introduced approach is based on complex correntropy function and can be seen as a generalization of the maximum likelihood detector (MLD) concept. The MCD is evaluated on Gaussian and non-Gaussian channels, where superior performance is achieved when compared with the classic detectors, without significant increase of the computational complexity.

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Section: A Kernel Size Adjustmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%