Reliable and Opportunistic Transmissions for Underwater Acoustic Networks

Chen, Weiqi; Yu, Hua; Guan, Quansheng; Ji, Fei; Chen, Fangjiong

doi:10.1109/mnet.2018.1700280

Cited by 19 publications

(12 citation statements)

References 13 publications

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“…This reporting channel then acts as a line-of-sight link which is noise-limited only [22], [23]. 3 This is inline with the previous literature on impersonation attack detection at the physical layer [5], [31].…”

Section: Impersonation Detection and Transmitter Identification Isupporting

confidence: 62%

“…In contrast to the terrestrial wireless networks, the UWASNs are exposed to the peculiar challenges of the underwater acoustic (UWA) channel, e.g. frequency-selective nature of path-loss and ambient noise, severe multipath (longer delay spreads), battery constraints, low (and variable) propagation speed of acoustic waves, and low data rates (for long-range communication) [1], [3]. The aforementioned challenges make the UWA channel quite error-prone, which calls for design of intelligent forward error correction (FEC) schemes, and retransmission schemes (e.g.…”

Section: Introductionmentioning

confidence: 99%

“…The aforementioned challenges make the UWA channel quite error-prone, which calls for design of intelligent forward error correction (FEC) schemes, and retransmission schemes (e.g. ARQ) [3] tailored for UWASNs.…”

Section: Introductionmentioning

confidence: 99%

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Impersonation Detection in Line-of-Sight Underwater Acoustic Sensor Networks

et al. 2018

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This work considers a line-of-sight underwater acoustic sensor network (UWASN) consisting of M underwater sensor nodes randomly deployed according to uniform distribution within a vertical half-disc (the so-called trusted zone). The sensor nodes report their sensed data to a sink node on water surface on a shared underwater acoustic (UWA) reporting channel in a time-division multiple-access (TDMA) fashion, while an active-yet-invisible adversary (so-called Eve) is present in the close vicinity who aims to inject malicious data into the system by impersonating some Alice node. To this end, this work first considers an additive white Gaussian noise (AWGN) UWA channel, and proposes a novel, multiple-features based, two-step method at the sink node to thwart the potential impersonation attack by Eve. Specifically, the sink node exploits the noisy estimates of the distance, the angle of arrival, and the location of the transmit node as device fingerprints to carry out a number of binary hypothesis tests (for impersonation detection) as well as a number of maximum likelihood hypothesis tests (for transmitter identification when no impersonation is detected). We provide closed-form expressions for the error probabilities (i.e., the performance) of most of the hypothesis tests. We then consider the case of a UWA with colored noise and frequency-dependent pathloss, and derive a maximum-likelihood (ML) distance estimator as well as the corresponding Cramer-Rao bound (CRB). We then invoke the proposed two-step, impersonation detection framework by utilizing distance as the sole feature. Finally, we provide detailed simulation results for both AWGN UWA channel and the UWA channel with colored noise. Simulation results verify that the proposed scheme is indeed effective for a UWA channel with colored noise and frequency-dependent pathloss.

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Section: Impersonation Detection and Transmitter Identification Isupporting

confidence: 62%

Section: Introductionmentioning

confidence: 99%

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Impersonation Detection in Line-of-Sight Underwater Acoustic Sensor Networks

et al. 2018

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“…Then, the fountain codes' success rate, the SNR and the BCH code rate were jointly optimized, allowing to increase the link distance with the cost of a gentle degradation in terms of energy efficiency. A cross-layer FEC scheme using fountain codes in the packetlevel FEC and channel codes in the bit-level FEC, together with a discrete stochastic approximation (DSA) algorithm to optimize the transmission throughput, is proposed in [14] to improve the reliability of underwater acoustic transmissions. It was found out that the proposed approach brings a performance improvement when compared to other cross-layer strategies.…”

Section: Introductionmentioning

confidence: 99%

Energy Efficiency of Multi-Hop Underwater Acoustic Networks Using Fountain Codes

et al. 2020

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Ensuring low energy consumption is a crucial issue in underwater communications, since battery replacement may be difficult and expensive in these scenarios. We analyze in this paper the energy consumption of a multi-hop underwater acoustic network (UWAN) employing fountain codes. Moreover, in order to reduce this energy consumption we optimize the modulation order assuming differential phaseshift keying (M-DPSK), as well as the number of hops. We investigate the required number of fountainencoded packets for different modulation orders. Our results show that, by optimizing the modulation order, the number of hops and the number of fountain packets, we can obtain important energy savings, especially for long distances. In addition, with the proposed scheme the energy consumption decreases significantly compared to the case without fountain codes, reaching up to 40% of savings. INDEX TERMS Fountain codes, energy efficiency, multi-hop systems.

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“…Underwater acoustic sensor networks (UWASNs) find their utilization by a multitude of civilian, commercial, and military applications, for example, marine life exploration, intrusion detection for border surveillance, performance monitoring of oil rigs, searching for (oil, gas, minerals) resources underwater, to name a few 1,2 . Contrary to the terrestrial communication, underwater acoustic (UWA) communication is quite challenging because the UWA channel is characterized by frequency‐dependent pathloss, colored Gaussian noise, low symbol‐rate due to long propagation delays (due to low speed of acoustic waves underwater), and fading effects due to multipath propagation 1,3 …”

Section: Introductionmentioning

confidence: 99%

Maximizing secrecy rate of an orthogonal frequency division multiplexing‐based multihop underwater acoustic sensor network

Aman

Rahman

Haider

et al. 2020

Trans Emerging Tel Tech

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In this article, we consider an eavesdropping attack on a multihop, underwater acoustic sensor network that consists of M + 1 underwater sensors which report their sensed data via orthogonal frequency division multiplexing (OFDM) scheme to a sink node on the water surface. Furthermore, due to the presence of a passive malicious node in nearby vicinity, the multihop underwater acoustic (UWA) channel between a sensor node and the sink node is prone to eavesdropping attack on each hop. Therefore, the problem at hand is to do (helper/relay) node selection (for data forwarding onto the next hop) as well as power allocation (across the OFDM subcarriers) in a way that the secrecy rate is maximized at each hop. To this end, this problem of node selection and power allocation (NSPA) is formulated as a mixed binary‐integer optimization program, which is then optimally solved via decomposition approach, and by exploiting duality theory along with the Karush‐Kuhn‐Tucker conditions. We also provide a computationally efficient, suboptimal solution to the NSPA problem, where we reformulate it as a mixed‐integer linear program and solve it via decomposition and geometric approach. Moreover, when the UWA channel is multipath (and not just line‐of‐sight), we investigate an additional, machine learning‐based approach to solve the NSPA problem. Finally, we compute the computational complexity of all the three proposed schemes (optimal, suboptimal, and learning‐based), and do extensive simulations to compare their performance against each other and against the baseline schemes (which allocate equal power to all the subcarriers and do depth‐based node selection). In a nutshell, this work proposes various (optimal and suboptimal) methods for providing information‐theoretic security at the physical layer of the protocol stack through resource allocation.

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Reliable and Opportunistic Transmissions for Underwater Acoustic Networks

Cited by 19 publications

References 13 publications

Impersonation Detection in Line-of-Sight Underwater Acoustic Sensor Networks

Impersonation Detection in Line-of-Sight Underwater Acoustic Sensor Networks

Energy Efficiency of Multi-Hop Underwater Acoustic Networks Using Fountain Codes

Maximizing secrecy rate of an orthogonal frequency division multiplexing‐based multihop underwater acoustic sensor network

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