Comparative performance assessment between FFT‐based and FRFT‐based MIMO‐OFDM systems in underwater acoustic communications

Nassiri, Mahdi; Baghersalimi, Gholamreza

doi:10.1049/iet-com.2017.0776

Cited by 19 publications

(28 citation statements)

References 27 publications

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“…When the channel is time and frequency selective, or there is a frequency offset in the receiver; the simple equalization procedure fails because the DFT cannot diagonalize the channel matrix any longer, resulting in appearing the ICI; consequently, a complicated equalizer is required that depends on the inversion of the estimated channel matrix [11]- [13], such as an MMSE equalizer. Martone [2] proposed the Fractional Fourier Transform as a new base for the OFDM that can improve the system performance under time and frequency selective fading channel, due to its chirp carrier's nature that can compensate the effect of the Doubler shift [14]. DFrFT-OCDM system will be discussed carefully in the next section.…”

Section: Dfrft-ocdm and Ofdm Systems Equalizationmentioning

confidence: 99%

“…The ICI increases significantly with the increase of the MCM block size, which is the case in the DVB-H, carrier frequency and velocity. Numerous techniques have been suggested to counter such ICI effects in the OFDM system, and in the DFrFT-OCDM system, such as in [4]- [6], [12], [18]- [23], and [8], [13], [14], respectively.…”

Section: Ofdm and Dfrft-ocdm Equalization Techniques Under Doublmentioning

confidence: 99%

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A Low-Complexity Equalizer for Video Broadcasting in Cyber-Physical Social Systems Through Handheld Mobile Devices

et al. 2020

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In Digital Video Broadcasting-Handheld (DVB-H) devices for cyber-physical social systems, the Discrete Fractional Fourier Transform-Orthogonal Chirp Division Multiplexing (DFrFT-OCDM) has been suggested to enhance the performance over Orthogonal Frequency Division Multiplexing (OFDM) systems under time and frequency-selective fading channels. In this case, the need for equalizers like the Minimum Mean Square Error (MMSE) and Zero-Forcing (ZF) arises, though it is excessively complex due to the need for a matrix inversion, especially for DVB-H extensive symbol lengths. In this work, a low complexity equalizer, Least-Squares Minimal Residual (LSMR) algorithm, is used to solve the matrix inversion iteratively. The paper proposes the LSMR algorithm for linear and nonlinear equalizers with the simulation results, which indicate that the proposed equalizer has significant performance and reduced complexity over the classical MMSE equalizer and other low complexity equalizers, in time and frequencyselective fading channels. INDEX TERMS Least-squares minimal residual (LSMR), digital video broadcasting-handheld (DVB-H), orthogonal frequency division multiplexing (OFDM), zero-forcing (ZF) and cyber-physical social systems. HANI ATTAR received the Ph.D. degree from the Department of Electrical and Electronic Engineering, University of Strathclyde, U.K., in 2011. Since 2011, he has been working as a Researcher of electrical engineering and energy systems. He is currently a University Lecturer with Zarqa University, Jordan. His research interests include network coding, wireless sensor networks, and wireless communications.

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Section: Dfrft-ocdm and Ofdm Systems Equalizationmentioning

confidence: 99%

Section: Ofdm and Dfrft-ocdm Equalization Techniques Under Doublmentioning

confidence: 99%

A Low-Complexity Equalizer for Video Broadcasting in Cyber-Physical Social Systems Through Handheld Mobile Devices

et al. 2020

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“…Nassiri and Baghersalimi [13] present a performance evaluation of an underwater MIMO-OFDM system based on the fractional Fourier transform (FRFT) and the fast Fourier transform (FFT). The results show that the computational complexity of FRFT is basically the same as that of FFT while the performance better.…”

Section: Related Workmentioning

confidence: 99%

A Novel Signal Detection Algorithm for Underwater MIMO-OFDM Systems Based on Generalized MMSE

et al. 2019

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The MIMO-OFDM system fully exploits the advantages of MIMO and OFDM, effectively resisting the channel multipath fading and inter-symbol interference while increasing the data transmission rate. Studies show that it is the principal technical mean for building underwater acoustic networks (UANs) of high performance. As the core, a signal detection algorithm determines the performance and complexity of the MIMO-OFDM system. However, low computational complexity and high performance cannot be achieved simultaneously, especially for UANs with a narrow bandwidth and limited data rate. This paper presents a novel signal detection algorithm based on generalized MMSE. First, we propose a model for the underwater MIMO-OFDM system. Second, we design a signal coding method based on STBC (space-time block coding). Third, we realize the detection algorithm namely GMMSE (generalized minimum mean square error). Finally, we perform a comparison of the algorithm with ZF (Zero Forcing), MMSE (minimum mean square error), and ML (Maximum Likelihood) in terms of the BER (bit error rate) and the CC (computational complexity). The simulation results show that the BER of GMMSE is the lowest one and the CC close to that of ZF, which achieves a tradeoff between the complexity and performance. This work provides essential theoretical and technical support for implementing UANs of high performance.

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“…The MIMO configurations are used for UWA communications . Two types of data transmission have been used in MIMO configurations; spatial multiplexing for increasing the system data rate, and spatial diversity for improving the system reliability .…”

Section: Introductionmentioning

confidence: 99%

“…Also, the proposed JLRZF equalizer can preserve the UWA-OFDM system performance in the case of estimation errors and variations in the normalized CFO.The MIMO configurations are used for UWA communications. 5,29,30 Two types of data transmission have been used in MIMO configurations; spatial multiplexing for increasing the system data rate, and spatial diversity for improving the system reliability. 31 Moreover, in the case of MIMO UWA-OFDM communication, the co-channel interference is an additional source of performance degradation.…”

mentioning

confidence: 99%

Joint low‐complexity equalization and carrier frequency offset compensation for underwater acoustic OFDM communication systems with banded‐matrix approximation at different channel conditions

Ramadan¹,

Dessouky

El-Kordy

et al. 2018

Int J Communication

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Summary Underwater acoustic wireless communication is considered as one of the most challenging communication technologies due to low propagation speed, water salinity, water depth, PH degree, and water temperature. Equalization is one of the means to improve the system performance. Matched filter (MF), zero forcing (ZF), and minimum mean square error (MMSE) equalizers can be used for channel equalization. Unfortunately, the performance of the matched filter is destroyed in the Multiple‐Input Multiple‐Output (MIMO) configurations. In addition, the ZF equalizer suffers from noise enhancement and high complexity because of the direct matrix inversion. On the other hand, the MMSE equalizer requires estimating the operating signal‐to‐noise ratio (SNR) to work properly. In this paper, we present a joint low‐complexity regularized ZF equalizer and carrier frequency offset (CFO) compensation scheme to deal with these problems. The proposed equalization algorithm mitigates the noise enhancement problem using a constant regularization parameter, and it can be implemented with low complexity using the banded‐matrix approximation. Also, we test the performance of the proposed system at different channel conditions. Simulation results show that the proposed equalizer has the ability to enhance the system performance with lower complexity than those of the other equalization algorithms at different channel conditions.

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Comparative performance assessment between FFT‐based and FRFT‐based MIMO‐OFDM systems in underwater acoustic communications

Cited by 19 publications

References 27 publications

A Low-Complexity Equalizer for Video Broadcasting in Cyber-Physical Social Systems Through Handheld Mobile Devices

A Low-Complexity Equalizer for Video Broadcasting in Cyber-Physical Social Systems Through Handheld Mobile Devices

A Novel Signal Detection Algorithm for Underwater MIMO-OFDM Systems Based on Generalized MMSE

Joint low‐complexity equalization and carrier frequency offset compensation for underwater acoustic OFDM communication systems with banded‐matrix approximation at different channel conditions

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