Comparing Various Channel Estimation Techniques for OFDM Systems Using MATLAB

Mohammed, Raghad K.

doi:10.5121/ijwmn.2019.11302

Cited by 3 publications

(2 citation statements)

References 11 publications

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“…The performance of LS is not satisfactory despite its easy implementation. The minimum mean square error (MMSE) estimator outperforms LS although it requires noise and statistical channel information, which is not always available in the receiver or may vary in time-varying wireless channels [3,4]. Since communication channel variations are nonlinear in time and frequency domains, the accuracy of estimation decreases significantly when using such basic methods as the LS algorithm.…”

Section: Introductionmentioning

confidence: 99%

Least squares support vector regression-based channel estimation for OFDM systems in the presence of impulsive noise

Mirsalari,

Haghbin,

Khatir

et al. 2024

Preprint

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This work aimed to investigate a multipath channel estimation technique for orthogonal frequency division multiplexing (OFDM) systems based on least squares support vector regression (LSSVR) in the presence of Gaussian and impulse noise. Since impulsive noise can considerably affect the performance of communication systems and also due to the time-varying and frequency selectivity of wireless channels, it is unavoidable to have a proper channel estimation and interpolation technique. Therefore, in this contribution, an autoregressive modeled multipath channel was estimated using LSSVR in the presence of impulsive and Gaussian noises. Considering that the proposed method does not need to solve a quadratic programming (QP) problem, it is less complex than standard support vector regression (SVR). The simulation results indicate that the proposed method outperforms standard SVR and the cubic-spline interpolated LS in terms of bit error rate (BER) and mean square error (MSE) criteria.

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Section: Introductionmentioning

confidence: 99%

Least squares support vector regression-based channel estimation for OFDM systems in the presence of impulsive noise

Mirsalari,

Haghbin,

Khatir

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…Thus, in order to avoid signal loss at the receiver side, an extra processing should be implemented. This processing is called equalization [2], [3] and it is used in order to suppress interferences and recover the original transmitted signal.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Fractionally Spaced Widely Linear Equalization over Frequency Selective Channels With Multiple Interferences

Fhima¹,

Roviras²,

Bouallègue³

2019

IJWMN

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This paper deals with the performance analysis of both linear (LE) and widely linear (WLE) equalization processes studied in the symbol spaced mode (SSE) as well as in the fractionally spaced one (FSE). This analysis is evaluated-using Matlab software-in terms of bit error rate (BER) and mean square error (MSE) in a system using a rectilinear modulation of type Pulse Amplitude Modulation (PAM) over a frequency selective channel and corrupted by multiple interferences. Moreover, the impact of the number of external interferers on the behavior of the different equalizers is studied. Thus, simulation results show the outstanding performance of the fractionally spaced mode when compared to the symbol spaced one besides the out-performance of the widely linear processing in both modes. Furthermore, results show the performance degradation for the different studied equalizers when the number of interferences increases.

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Advancing Multiband OFDM Channel Sounding: An Iterative Time Domain Estimation for Spectrally Constrained Systems

Iqbal,

Drieberg,

Jeoti

et al. 2023

IEEE Access

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The emerging wireless applications are facing new challenges in combating frequency congestion problems. As a result, the opportunistic utilization of available frequency spectrum and channel bonding is becoming increasingly common in new wireless standards. In these systems, the transmit waveforms are required to have nulls in specific frequency bands to avoid interference with primary users. However, these nulls can significantly affect the performance of channel estimation algorithms. This work proposes a novel Iterative Multiband (MB) Spectrally Constrained Time-Domain (SCTD) technique to developed to reduce the residual error of correlation due to spectrally constrained waveforms. The performance of the newly developed technique is evaluated through extensive numerical experiments, where the Mean Squared Error (MSE) and Bit Error Rate (BER) are computed for various scenarios. The accuracy of the proposed technique is compared with known channel state information and with conventional techniques. The simulation results show that the proposed Time-Domain Iterative Method, SCTD, performs better than conventional techniques for various Rayleigh channel conditions with Additive White Gaussian Noise (AWGN). It was found that after ten iterations, the proposed technique outperforms the conventional technique for both stationary and mobile frequency-selective channels. Furthermore, it was observed that the proposed SCTD technique requires fewer pilot signals to achieve a similar performance. The results show that the proposed SCTD method supersedes the conventional techniques for stationary and mobile frequency selective channel scenarios within ten iterations. Subsequently, it is observed that the proposed SCTD method requires 50% fewer pilots to provide similar performance compared to conventional methods. It is also observed that the proposed SCTD method provides an average of 6 dB mean squared error (MSE) advantage for low signal-to-noise ratio per bit (𝐸 𝑏 𝑁 0 ⁄ ) regime cases. It can be concluded that the proposed technique is highly suitable, particularly for low 𝐸 𝑏 𝑁 0 ⁄ regimes and can be used for various communication systems.

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Comparing Various Channel Estimation Techniques for OFDM Systems Using MATLAB

Cited by 3 publications

References 11 publications

Least squares support vector regression-based channel estimation for OFDM systems in the presence of impulsive noise

Least squares support vector regression-based channel estimation for OFDM systems in the presence of impulsive noise

Analysis of Fractionally Spaced Widely Linear Equalization over Frequency Selective Channels With Multiple Interferences

Advancing Multiband OFDM Channel Sounding: An Iterative Time Domain Estimation for Spectrally Constrained Systems

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