scholarly journals Filtered Multitone Modulation Underwater Acoustic Communications Using Low-Complexity Channel-Estimation-Based MMSE Turbo Equalization

Sensors ◽  
2019 ◽  
Vol 19 (12) ◽  
pp. 2714 ◽  
Author(s):  
Lin Sun ◽  
Mei Wang ◽  
Guoheng Zhang ◽  
Haisen Li ◽  
Lan Huang
Keyword(s):  
Channel Estimation ◽  
Simulation Analysis ◽  
Multipath Propagation ◽  
Minimum Mean Square Error ◽  
Real Data ◽  
Low Complexity ◽  
Turbo Equalization ◽  
Adaptive Equalization ◽  
Communication Performance ◽  
Underwater Acoustic

Filtered multitone (FMT) modulation divides the communication band into several subbands to shorten the span of symbols affected by multipath in underwater acoustic (UWA) communications. However, there is still intersymbol interference (ISI) in each subband of FMT modulation degrading communication performance. Therefore, ISI suppression techniques must be applied to FMT modulation UWA communications. The suppression performance of traditional adaptive equalization methods often exploited in FMT modulation UWA communications is limited when the effect of ISI spans tens of symbols or large constellation sizes are used. Turbo equalization consisting of adaptive equalization and channel decoding can improve equalization performance through information exchanging and iterative processes. To overcome the shortcoming of traditional minimum mean square error (MMSE) equalization and effectively suppress the ISI with relatively low computation complexity, an FMT modulation UWA communication using low-complexity channel-estimation-based (CE-based) MMSE turbo equalization is proposed in this paper. In the proposed method, turbo equalization is first exploited to suppress the ISI in FMT modulation UWA communications, and the equalizer coefficients of turbo equalization are adjusted using the low-complexity CE-based MMSE algorithm. The proposed method is analyzed in theory and verified by simulation analysis and real data collected in the experiment carried out in a pool with multipath propagation. The results demonstrate that the proposed method can achieve better communication performance with a higher bit rate than the FMT modulation UWA communication using traditional MMSE adaptive equalization.

Experimental Multipath Delay Profile of Underwater Acoustic Communication Channel in Shallow Water

2016 ◽  
Vol 2 (2) ◽  
pp. 351 ◽  
Author(s):  
Yasin Yousif Al_Aboosi ◽  
Ahmad Zuri Sha'ameri
Keyword(s):  
Shallow Water ◽  
Acoustic Communication ◽  
Multipath Propagation ◽  
Water Channel ◽  
Underwater Acoustic Communication ◽  
Communication Performance ◽  
Underwater Acoustic ◽  
Research Fields ◽  
Different Depths ◽  
Major Factors

<p>The shallow water channel is an environment that is of particular interest to many research fields. An underwater acoustic channel is characterized as a multipath channel. Time-varying multipath propagation is one of the major factors that limit the acoustic communication performance in shallow water. This study conducts two underwater acoustic experiments in Tanjung Balau, Johor, Malaysia. A transducer and a hydrophone are submerged at different depths and separated by different distances. Linear frequency modulated (LFM) pulses are chosen as the main transmit signal for the experiments. The cross-correlation between the transmitted and received signals represents the impulse response of the channel (multipath profile). The results show that the amplitude of the successive paths will not rapidly decline, and vice versa, when the distance between the sender and the receiver increases. Moreover, the time difference between the different paths will be small in the case of distance increase. In other words, the successive paths will converge in time.</p>

scholarly journals A Joint Approach for Low-Complexity Channel Estimation in 5G Massive MIMO Systems

Electronics ◽  
2018 ◽  
Vol 7 (10) ◽  
pp. 218 ◽  
Author(s):  
Kifayatullah Bangash ◽  
Imran Khan ◽  
Jaime Lloret ◽  
Antonio Leon
Keyword(s):  
Computational Complexity ◽  
Channel Estimation ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Minimum Mean Square Error ◽  
Low Complexity ◽  
Least Square ◽  
Mimo Channel ◽  
Finite Sample ◽  
The Impact

Traditional Minimum Mean Square Error (MMSE) detection is widely used in wireless communications, however, it introduces matrix inversion and has a higher computational complexity. For massive Multiple-input Multiple-output (MIMO) systems, this detection complexity is very high due to its huge channel matrix dimension. Therefore, low-complexity detection technology has become a hot topic in the industry. Aiming at the problem of high computational complexity of the massive MIMO channel estimation, this paper presents a low-complexity algorithm for efficient channel estimation. The proposed algorithm is based on joint Singular Value Decomposition (SVD) and Iterative Least Square with Projection (SVD-ILSP) which overcomes the drawback of finite sample data assumption of the covariance matrix in the existing SVD-based semi-blind channel estimation scheme. Simulation results show that the proposed scheme can effectively reduce the deviation, improve the channel estimation accuracy, mitigate the impact of pilot contamination and obtain accurate CSI with low overhead and computational complexity.

scholarly journals A Low-Complexity Pilot-Based Frequency-Domain Channel Estimation for ICI Mitigation in OFDM Systems

Electronics ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1404
Author(s):  
Francisco J. Martín-Vega ◽  
Gerardo Gómez
Keyword(s):  
Channel Estimation ◽  
Frequency Domain ◽  
Signal To Noise Ratio ◽  
Minimum Mean Square Error ◽  
Estimation Method ◽  
Low Complexity ◽  
High Signal ◽  
Ofdm Systems ◽  
Coupling Matrix ◽  
Pilot Pattern

A low-complexity pilot pattern and a frequency-domain channel estimation method for Inter-Carrier Interference (ICI) mitigation is proposed for Orthogonal Frequency Division Multiple Access (OFDM) systems. The proposed method exploits the band structure of the coupling matrix to perform an ICI-free channel estimation in the frequency domain. This ICI-free estimation relies on some conditions imposed over the pilot pattern that simplify the complexity of channel estimation significantly, since its complexity is the same as classical least squares (LS) channel estimation used in low mobility scenarios. Then, the ICI is removed by using a modified version of Minimum Mean Square Error (MMSE) equalization, which reduces the computational complexity considerably. This modified MMSE equalization relies on the sparse and banded structure of the coupling matrix and on a low complexity variant of the Cholesky decomposition, which is named LDLH factorization. It is shown that the proposed method greatly improves the Bit Error Rate (BER) in the high Signal-to-Noise Ratio (SNR) regime.

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