Adaptive Coding and Bit-Power Loading Algorithms for Underwater Acoustic Transmissions

Zhang, Rongxin; Ma, Xiaoli; Wang, Deqing; Yuan, Fei; Cheng, En

doi:10.1109/twc.2021.3070363

Cited by 12 publications

(3 citation statements)

References 53 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The first method exploits only statistical CSI, assuming that the statistical CSI is stable. In this case, only CSI feedback needs to be performed without performing channel prediction [11][12][13][14]. Qiao et al from Harbin Engineering University proposed outdated CSI and average CSI selection methods based on channel correlation factors in orthogonal frequency-division multiplexing (OFDM) access for UWA [14].…”

Section: Introductionmentioning

confidence: 99%

Channel Prediction for Underwater Acoustic Communication: A Review and Performance Evaluation of Algorithms

Liu,

Ma,

Wang

et al. 2024

Remote Sensing

View full text Add to dashboard Cite

Underwater acoustic (UWA) channel prediction technology, as an important topic in UWA communication, has played an important role in UWA adaptive communication network and underwater target perception. Although many significant advancements have been achieved in underwater acoustic channel prediction over the years, a comprehensive summary and introduction is still lacking. As the first comprehensive overview of UWA channel prediction, this paper introduces past works and algorithm implementation methods of channel prediction from the perspective of linear, kernel-based, and deep learning approaches. Importantly, based on available at-sea experiment datasets, this paper compares the performance of current primary UWA channel prediction algorithms under a unified system framework, providing researchers with a comprehensive and objective understanding of UWA channel prediction. Finally, it discusses the directions and challenges for future research. The survey finds that linear prediction algorithms are the most widely applied, and deep learning, as the most advanced type of algorithm, has moved this field into a new stage. The experimental results show that the linear algorithms have the lowest computational complexity, and when the training samples are sufficient, deep learning algorithms have the best prediction performance.

show abstract

Section: Introductionmentioning

confidence: 99%

Channel Prediction for Underwater Acoustic Communication: A Review and Performance Evaluation of Algorithms

Liu,

Ma,

Wang

et al. 2024

Remote Sensing

View full text Add to dashboard Cite

show abstract

“…In contrast to the terrestrial IoT systems, radio frequency (RF)-based techniques are unsuitable for the IoUT, owing to the severe absorption of electromagnetic waves in underwater environments. As a remedy, underwater acoustic communications (UAC) [3], [4] are widely adopted, but it still remains unrealistic for energylimited IoUT devices to directly transmit their collected data to a surface-station through long-distance propagation, because ten-times higher transmit power is required compared to RFbased communications. To cope with this issue, autonomous underwater vehicles (AUV) have been widely adopted for data collection in underwater environments [5], [6].…”

Section: Introductionmentioning

confidence: 99%

Environment-Aware AUV Trajectory Design and Resource Management for Multi-Tier Underwater Computing

Hou

Wang

Bai

et al. 2023

IEEE J. Select. Areas Commun.

View full text Add to dashboard Cite

The Internet of underwater things (IoUT) is envisioned to be an essential part of maritime activities. Given the IoUT devices' wide-area distribution and constrained transmit power, autonomous underwater vehicles (AUVs) have been widely adopted for collecting and forwarding the data sensed by IoUT devices to the surface-stations. In order to accommodate the diverse requirements of IoUT applications, it is imperative to conceive a multi-tier underwater computing (MTUC) framework by carefully harnessing both the computing and the communications as well as the storage resources of both the surface-station and of the AUVs as well as of the IoUT devices. Furthermore, to meet the stringent energy constraints of the IoUT devices and to reduce the operating cost of the MTUC framework, a joint environment-aware AUV trajectory design and resource management problem is formulated, which is a high-dimensional NP-hard problem. To tackle this challenge, we first transform the problem into a Markov decision process (MDP) and solve it with the aid of the asynchronous advantage actor-critic (A3C) algorithm. Our simulation results demonstrate the superiority of our scheme.

show abstract

“…In [23], the authors propose an OFDM sub-carrier power optimization mechanism based on channel knowledge, achieved with a length-adaptive estimation technique. In [24], second-order statistics of the channel are exploited to derive the signal-to-interference-plus-noise ratio in each sub-carrier, so to realize adaptive coding and bit-power loading. An OFDM acoustic modem is presented in [25], with adaptive modulation being performed based on the channel delay and Doppler spread, measured by using chirp pilots.…”

Section: Introductionmentioning

confidence: 99%

On the Effect of Channel Knowledge in Underwater Acoustic Communications: Estimation, Prediction and Protocol

et al. 2023

View full text Add to dashboard Cite

Underwater acoustic communications are limited by the following channel impairments: time variability, narrow bandwidth, multipath, frequency selective fading and the Doppler effect. Orthogonal Frequency Division Modulation (OFDM) is recognized as an effective solution to such impairments, especially when optimally designed according to the propagation conditions. On the other hand, OFDM implementation requires accurate channel knowledge atboth transmitter and receiver sides. Long propagation delay may lead to outdated channel information. In this work, we present an adaptive OFDM scheme where channel state information is predicted through a Kalman-like filter so as to optimize communication parameters, including the cyclic prefix length. This mechanism aims to mitigate the variability of channel delay spread. This is cast in a protocol where channel estimation/prediction are jointly considered, so as to allow efficiency. The performance obtained through extensive simulations using real channels and interference show the effectiveness of the proposed scheme, both in terms of rate and reliability, at the expense of an increasing complexity. However, this solution is significantly preferable to the conventional mechanism, where channel estimation is performed only at the receiver, with channel coefficients sent back to the transmit node by means of frequent overhead signaling.

show abstract

Adaptive Coding and Bit-Power Loading Algorithms for Underwater Acoustic Transmissions

Cited by 12 publications

References 53 publications

Channel Prediction for Underwater Acoustic Communication: A Review and Performance Evaluation of Algorithms

Channel Prediction for Underwater Acoustic Communication: A Review and Performance Evaluation of Algorithms

Environment-Aware AUV Trajectory Design and Resource Management for Multi-Tier Underwater Computing

On the Effect of Channel Knowledge in Underwater Acoustic Communications: Estimation, Prediction and Protocol

Contact Info

Product

Resources

About