A new optimized least‐square sparse channel estimation scheme for underwater acoustic communication

Kumar, Anand

doi:10.1002/dac.5436

Cited by 3 publications

(2 citation statements)

References 42 publications

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“…However, this method often faces high complexity when training with larger signals. Kumar et al 33 established the extended CE technology for UWAC‐OFDM systems. This paper introduced the least squares (LS) based CE technique to estimate the channel effectively.…”

Section: Related Workmentioning

confidence: 99%

Optimized deep learning driven signal detection and adaptive channel estimation in underwater acoustic IoT networks

Kapileswar,

Phani Kumar

2023

Int J Communication

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SummaryNowadays, multiple input multiple outputs with orthogonal frequency division multiplexing (MIMO‐OFDM) provide better communication performance that can be applied to the fast‐growing Internet of Things (IoTs). In underwater IoT, information fades away rapidly due to varying water conditions. Therefore, the MIMO model can be applied to the OFDM acoustic system, enabling high‐speed data transmission without affecting the channel effectively. However, detecting the underwater signal and estimating the channel is highly necessary for enhancing underwater acoustic communication (UWAC). Recently, many techniques have been introduced for effectively performing signal detection and channel estimation. However, those techniques face high time complexity due to increased channel interferences and noises during data transmission. Hence, this article brings a novel technique for SD and CE for the UWAC‐IoT‐enabled MIMO‐OFDM system. An adaptive recursive least square (ARLS) technique is proposed in this study for CE that aids in evaluating the acoustic channel parameters effectively. For performing SD, a bi‐directional deep pelican convolutional neural network (BDPCNN) technique is introduced to ensure the presence and absence of signals at the receiver end. The proposed method is analyzed via the MATLAB platform, and the performances are analyzed under different water types like turbid water, coastal water, clear ocean water, and pure seawater. Different performance metrics like bit error rate (BER), mean square error (MSE), energy efficiency (EE), and time complexity are analyzed with different existing techniques. The experimental section obtains the BER of 0.0086, 0.013, 0.017, and 0.021 for turbid, coastal, clear, and pure seawater, respectively.

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Section: Related Workmentioning

confidence: 99%

Optimized deep learning driven signal detection and adaptive channel estimation in underwater acoustic IoT networks

Kapileswar,

Phani Kumar

2023

Int J Communication

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“…In UASNs, the predetermined MAC protocols like TDMA, FDMA, or CDMA cannot be adopted because of limited bandwidth, high delay in propagation, complexity in lock synchronization, etc. Vector Base Forwarding (VBF) and its enhanced routing protocols (5,6) are devised only for the network layer. In such environments, security in conventional UASNs is not considered.…”

Section: Introductionmentioning

confidence: 99%

Secure Fuzzy Simple Shortest Path Routing Protocol (SF_SSP) for Underwater Communication

Shahapur,

Khanai,

Torse

et al. 2023

IJST

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Objectives: The primary objective of the protocol is to detect malicious nodes accurately and efficiently. Malicious nodes can disrupt communication, drop packets, or launch various attacks on the network. By using fuzzy logic, this protocol considers multiple parameters and behaviors of nodes to identify potential malicious activities. Methods: In this work, fuzzy logic rules are utilized for evaluating various parameters and behaviors for nodes. Fuzzy inference system with linguistic variables and fuzzy rules is also established. Findings: In UWSN, Security is one of the key points of consideration in implementing the protocol. However current routing protocols have not been designed to defend against security attacks that can degrade the network performance. Since the nodes in UWSN are susceptible to malicious attacks, it is easier for an adversary to operate and to select UWSN channel along with communication nodes. In the UWSN environment, the presence of selfish nodes degrades the performance of the confidence nodes. This presence of selfish nodes in UWSN also leads to connection letdown between communication nodes. In this research work, an intelligent routing technique is introduced to Simple Shortest Path (SSP) routing protocol. We have added fuzzy-based security to SSP that enhances the SSP performance. This research work proposes fuzzy-based selfish node detection and removing those selfish nodes from routing. The parameters which describe the behavior of individual nodes are extracted and evaluated using fuzzy rules. The proposed SF_SSP provides higher throughput and packet Delivery Ratio compared to VBF, and SSP. Novelty: The novelty of detecting malicious nodes in underwater communication lies in its adaptive and robust trust evaluation using fuzzy logic to handle uncertainty and dynamic underwater conditions effectively. In this work, we have strengthened the Simple Shortest Path (SSP) routing scheme by adding fuzzy-based security rules.

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Suitable pilot search method for channel estimation in underwater acoustic OFDM systems

Thi Nga,

Phan,

Cao

et al. 2023

JMST

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The underwater environment poses challenges to the Underwater Acoustic OFDM (UWA-OFDM) system, causing the tendency of lacking pilots to recover the channel impulse response (CIR). Our previous research (pilot enrichment estimator) supplemented potential pilots based on the distance to the nearest constellation point below a fixed threshold T. However, this does not guarantee that the extracted pilots have sufficiently good quality. Therefore, this article presents a suitable pilot search (SPS) method with the flexible threshold T and second minimum mean square error (MMSE) estimation to improve channel estimation effectiveness in UWA-OFDM systems. Our approach is compared to the MMSE and PE methods across various criteria, such as pilot spacing and different modulators. The experiments demonstrate that the SPS estimator performs better than the MMSE and PE techniques regarding bit error rate (BER).

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A new optimized least‐square sparse channel estimation scheme for underwater acoustic communication

Cited by 3 publications

References 42 publications

Optimized deep learning driven signal detection and adaptive channel estimation in underwater acoustic IoT networks

Optimized deep learning driven signal detection and adaptive channel estimation in underwater acoustic IoT networks

Secure Fuzzy Simple Shortest Path Routing Protocol (SF_SSP) for Underwater Communication

Suitable pilot search method for channel estimation in underwater acoustic OFDM systems

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