Proceedings of the 15th International Conference on Underwater Networks & Systems最新文献_第4页

An Experimental Testbed for Underwater Acoustic Sensor Network Protocol Dedicated to Offshore Wind Turbines 海上风力机专用水声传感器网络协议实验试验台

Proceedings of the 15th International Conference on Underwater Networks & Systems Pub Date : 2021-11-22 DOI: 10.1145/3491315.3491365

Fekher Khelifi, B. Parrein

引用次数: 2

FH-FSK Remote Control Acoustic Release System with Mechanical Push-Off Mechanism FH-FSK机械推离机构遥控声释放系统

Proceedings of the 15th International Conference on Underwater Networks & Systems Pub Date : 2021-11-22 DOI: 10.1145/3491315.3491355

Songzuo Liu, Yanan Liu, Jun Yang, Qinfeng Yi, Wangyi Pu, Lu Ma

引用次数: 0

Influence of acoustic field interference structure on underwater acoustic target recognition based on a convolutional neural network 声场干扰结构对基于卷积神经网络的水声目标识别的影响

Proceedings of the 15th International Conference on Underwater Networks & Systems Pub Date : 2021-11-22 DOI: 10.1145/3491315.3491368

Meng Zhao, Zhenzhu Wang, Wen Wang, Qunyan Ren, Li Ma

{"title":"Influence of acoustic field interference structure on underwater acoustic target recognition based on a convolutional neural network","authors":"Meng Zhao, Zhenzhu Wang, Wen Wang, Qunyan Ren, Li Ma","doi":"10.1145/3491315.3491368","DOIUrl":"https://doi.org/10.1145/3491315.3491368","url":null,"abstract":"The acoustic field in a shallow sea waveguide has a complex spatial interference structure caused by the sea surface and seabed [1]. This spatial interference will distort the spectrum of the target signal in the propagation process, increasing the difficulty of recognizing underwater acoustic targets. Of course, sufficient target data at different receiving positions can improve the generalization ability of a classifier model. This solution can partly arrest the degradation of the recognition rate, but the high cost and difficulty of acquiring experimental data offset this advantage. Instead, researchers have begun expanding the simulation target data using sound propagation models [2-4]. The target data obtained by this method are reliable. Sufficient simulation data can also compensate the insufficient experimental data. In shallow ocean with low frequency, the normal mode (NM) model can accurately and quickly calculate the acoustic field. Therefore, the NM model is often chosen as the acoustic field calculation model. The NM model represents acoustic field by the superposition of various normal modes. Although the data expansion method based on ocean acoustic fields can improve the recognition rate of targets, which normal modes dominate the recognition rate improvement remains unclear. And classifier based on the deep learning model has high generalization ability, partial acoustic field interference may not affect the recognition rate of targets. When identifying the normal modes that mainly influence the recognition rate, target recognition can be simplified, which has considerable significance.","PeriodicalId":191580,"journal":{"name":"Proceedings of the 15th International Conference on Underwater Networks & Systems","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129076792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Modeling Acoustic Telemetry Detection Ranges in a Shallow Coastal Environment 浅海环境声遥测探测距离建模

Proceedings of the 15th International Conference on Underwater Networks & Systems Pub Date : 2021-11-22 DOI: 10.1145/3491315.3491331

Frank McQuarrie, C. Woodson, C. R. Edwards

{"title":"Modeling Acoustic Telemetry Detection Ranges in a Shallow Coastal Environment","authors":"Frank McQuarrie, C. Woodson, C. R. Edwards","doi":"10.1145/3491315.3491331","DOIUrl":"https://doi.org/10.1145/3491315.3491331","url":null,"abstract":"Acoustic telemetry is a popular way of monitoring underwater environments and habitats, but an understanding of the detection range and efficiency of the receivers in variable conditions can provide a significant advantage over the detections alone. Receivers can be attached or integrated into autonomous underwater vehicles (AUVs) allowing wide spatial coverage for telemetry networks while collecting environmental data. The integration of calculated sound speeds and received pings gives an estimation of variation in detection efficiency due to changes in environmental conditions, allowing underwater network users to better quantify the range of reliable detection. Data from a Slocum glider deployed over an array of 16 moored telemetry instruments on the inner shelf off Georgia in 2019 and 2020 indicate that detection efficiency and range vary seasonally. Beam density analysis using ray tracing is proposed as a novel approach that quantifies probability of detection as a function of range, modeling sound speed variability and propagation using co-located temperature and salinity measurements. This approach is validated through comparison of modeled to observed distributions, which suggests that beam density analysis is a promising method to remotely estimate detection efficiency in real time. This real time capability can be leveraged through adaptive sampling in the design and implementation of robotic acoustic telemetry networks.","PeriodicalId":191580,"journal":{"name":"Proceedings of the 15th International Conference on Underwater Networks & Systems","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127629719","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Improved acoustic underwater communication with orthogonal Kasami-based sequences for multi-user communication 基于正交kasami序列的多用户通信改进水声通信

Proceedings of the 15th International Conference on Underwater Networks & Systems Pub Date : 2021-11-22 DOI: 10.1145/3491315.3491319

Marcel Rieß, F. Slomka

{"title":"Improved acoustic underwater communication with orthogonal Kasami-based sequences for multi-user communication","authors":"Marcel Rieß, F. Slomka","doi":"10.1145/3491315.3491319","DOIUrl":"https://doi.org/10.1145/3491315.3491319","url":null,"abstract":"Wireless acoustic underwater communication systems have a limited energy resource and require an energetic consideration of all design decisions, including communication protocols. Besides reducing the power consumption is a robust detection of signals in the doubly spread channel, which varies in time and frequency, the main focus of wake-up and detection signals. Due to the challenging properties of the underwater channel, like the multipath propagation and the Doppler effects, correlation-based methods with fixed sequences only lead to the desired success under good to perfect conditions without signal-, symbol- and timing-reconstruction. This work presents a Kasami-based approach for reducing the overhead using a cross-layer adapted frame structure for the RTS/CTS hand-shaking protocol. It reduces the power consumption up to 88.3 % with an increased payload of 3.8 %, a possible collision detection till -4 dB, a supported relative speed of +/-20 m/s with a detection and decoding rate of up to 100 % using Kasami code-based sequences, related to predefined IDs and frame types for optimized cross-layer functionality of the handshake-based MAC protocol.","PeriodicalId":191580,"journal":{"name":"Proceedings of the 15th International Conference on Underwater Networks & Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130193164","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Equalization in Underwater Acoustic Orbital Angular Momentum Mode-Division Multiplexing 水声轨道角动量模分复用中的均衡化

Proceedings of the 15th International Conference on Underwater Networks & Systems Pub Date : 2021-11-22 DOI: 10.1145/3491315.3491328

Zhipeng Li, Qing Zhang, Xin Wen, Fengzhong Qu, Yan Wei

引用次数: 0

A Study of Mapping Sequences Spread Spectrum Underwater Acoustic Communications Using Gold Codes 利用金码映射序列扩频水声通信的研究

Proceedings of the 15th International Conference on Underwater Networks & Systems Pub Date : 2021-11-22 DOI: 10.1145/3491315.3491333

Yan Li, Biaodi Liu, Ning Jia, Jianchun Huang, D. Xiao, Shengming Guo

{"title":"A Study of Mapping Sequences Spread Spectrum Underwater Acoustic Communications Using Gold Codes","authors":"Yan Li, Biaodi Liu, Ning Jia, Jianchun Huang, D. Xiao, Shengming Guo","doi":"10.1145/3491315.3491333","DOIUrl":"https://doi.org/10.1145/3491315.3491333","url":null,"abstract":"Parallel combinatory spread spectrum (PCSS) is a solution to increase the data rate of spread spectrum communication system. However, when multiple spread spectrum sequences are combined, the envelope is not constant, which will consequently reduce the energy efficiency. Hence, mapping sequences spread spectrum is introduced, which can simultaneously transmit three sequences by transforming three spread spectrum sequences into a constant envelope sequence before transmission. The mapping sequences spread spectrum can effectively reduce the peak-to-average power ratio (PAPR) of the PCSS signal. However, there is still a problem with mapping sequences spread spectrum: when three Gold codes are combined and mapped into a binary sequence, a pseudo correlation peak will appear caused by an interference Gold code when the received signal is correlated with normalized replicas of M possible transmission signals. In this paper, a PCSS underwater acoustic communication system based on the phase differences of correlation peaks method (PDCP-PCSS) is proposed, which can identify and eliminate the pseudo correlation peak by judging the phase differences of the correlation peaks. Compared with the conventional parallel combinatory spread spectrum underwater acoustic communication method, the proposed method can improve the performance of mapping sequences spread spectrum communication system effectively.","PeriodicalId":191580,"journal":{"name":"Proceedings of the 15th International Conference on Underwater Networks & Systems","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121997089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Underwater Acoustic Communication Channel Modeling using Deep Learning 基于深度学习的水声通信信道建模

Proceedings of the 15th International Conference on Underwater Networks & Systems Pub Date : 2021-11-22 DOI: 10.1145/3491315.3491323

Oluwaseyi Onasami, D. Adesina, Lijun Qian

{"title":"Underwater Acoustic Communication Channel Modeling using Deep Learning","authors":"Oluwaseyi Onasami, D. Adesina, Lijun Qian","doi":"10.1145/3491315.3491323","DOIUrl":"https://doi.org/10.1145/3491315.3491323","url":null,"abstract":"With the recent increase in the number of underwater activities, having effective underwater communication systems has become increasingly important. Underwater acoustic communication has been widely used but greatly impaired due to the complicated nature of the underwater environment. In a bid to better understand the underwater acoustic channel so as to help in the design and improvement of underwater communication systems, attempts have been made to model the underwater acoustic channel using mathematical equations and approximations under some assumptions. In this paper, we explore the capability of machine learning and deep learning methods to learn and accurately model the underwater acoustic channel using real underwater data collected from a water tank with disturbance and from lake Tahoe. Specifically, Deep Neural Network (DNN) and Long Short Term Memory (LSTM) are applied to model the underwater acoustic channel. Experimental results show that these models are able to model the underwater acoustic communication channel well and that deep learning models, especially LSTM are better models in terms of mean absolute percentage error.","PeriodicalId":191580,"journal":{"name":"Proceedings of the 15th International Conference on Underwater Networks & Systems","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115783142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

A Scalable and Fair Power Allocation Scheme Based on Deep Multi-Agent Reinforcement Learning in Underwater Wireless Sensor Networks 基于深度多智能体强化学习的水下无线传感器网络可扩展公平功率分配方案

Proceedings of the 15th International Conference on Underwater Networks & Systems Pub Date : 2021-11-22 DOI: 10.1145/3491315.3491335

T. Zhang, Yu Gou, Jun Liu, Tingting Yang, Shanshan Song, Jun-hong Cui

{"title":"A Scalable and Fair Power Allocation Scheme Based on Deep Multi-Agent Reinforcement Learning in Underwater Wireless Sensor Networks","authors":"T. Zhang, Yu Gou, Jun Liu, Tingting Yang, Shanshan Song, Jun-hong Cui","doi":"10.1145/3491315.3491335","DOIUrl":"https://doi.org/10.1145/3491315.3491335","url":null,"abstract":"Providing qualified communications and optimizing network performance for Underwater Wireless Sensor Networks (UWSNs) is difficult due to limited battery power and storage, unpredictable channel conditions, and significant communication interference (including ambient noise and inter-nodes interferences). Power allocation is an important technology for UWSNs. In this paper, we analyzed the constraints of UWSNs and proposed a distributed power allocation scheme based on deep multi-agent reinforcement learning, which dynamically tunes the independent transmit power according to changing environments. We improve the number of concurrent communications and optimizes network capacity by fully leveraging the spatial separation of wireless networks. We compared the proposed approach with baseline methods in network capacity and communication fairness in different communication scenarios when the number of underwater nodes increases. Experiments confirmed that our solution achieves a significantly better trade-off between network capacity and fairness, while still satisfying the lifetime criteria.","PeriodicalId":191580,"journal":{"name":"Proceedings of the 15th International Conference on Underwater Networks & Systems","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114658095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Capacity analysis of the Underwater Visible Light Communication Systems over Salinity-Induced Turbulence with Noises 水下可见光通信系统在含噪声的盐度湍流环境下的容量分析

Proceedings of the 15th International Conference on Underwater Networks & Systems Pub Date : 2021-11-22 DOI: 10.1145/3491315.3491344

Gunjan Matta, Priya Pandey, M. Agrawal, R. Bahl

引用次数: 1