scholarly journals An Energy Harvesting Underwater Acoustic Transmitter for Aquatic Animals

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Huidong Li ◽  
Chuan Tian ◽  
Jun Lu ◽  
Mitchell J. Myjak ◽  
Jayson J. Martinez ◽  
...  
Keyword(s):  
Energy Harvesting ◽  
Aquatic Animals ◽  
Underwater Acoustic ◽  
Acoustic Transmitter

A novel underwater acoustic transmitter

2005 ◽  
Vol 117 (4) ◽  
pp. 2447-2447
Author(s):  
Chung Chang ◽  
Richard Coates
Keyword(s):  
Underwater Acoustic ◽  
Acoustic Transmitter

scholarly journals A small long-life acoustic transmitter for studying the behavior of aquatic animals

2016 ◽  
Vol 87 (11) ◽  
pp. 114902 ◽  
Author(s):  
J. Lu ◽  
Z. D. Deng ◽  
H. Li ◽  
M. J. Myjak ◽  
J. J. Martinez ◽  
...  
Keyword(s):  
Aquatic Animals ◽  
Acoustic Transmitter ◽  
Long Life

scholarly journals Deep Q-Network-Based Cooperative Transmission Joint Strategy Optimization Algorithm for Energy Harvesting-Powered Underwater Acoustic Sensor Networks

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6519
Author(s):  
Song Han ◽  
Luo Li ◽  
Xinbin Li
Keyword(s):  
Sensor Networks ◽  
Energy Harvesting ◽  
Cooperative Transmission ◽  
Superior Performance ◽  
Acoustic Sensor ◽  
Underwater Acoustic Sensor Networks ◽  
Underwater Acoustic ◽  
Acoustic Sensor Networks ◽  
Joint Strategy

Cooperative transmission is a promising technology for underwater acoustic sensor networks (UASNs) to ensure the effective collection of underwater information. In this paper, we study the joint relay selection and power allocation problem to maximize the cumulative quality of information transmission in energy harvesting-powered UASNs (EH-UASNs). First, we formulate the process of cooperative transmission with joint strategy optimization as a Markov decision process model. In the proposed model, an effective state expression is presented to better reveal interactive relationship between learning and environment, thereby improving the learning ability. Then, we further propose a novel reward function which can guide nodes to adjust power strategy adaptively to balance instantaneous capacity and long-term quality of service (QoS) under the dynamic unpredictable energy harvesting. More specifically, we propose a deep Q-network-based resource allocation algorithm for EH-UASNs to solve the complex coupled strategy optimization problem without any prior underwater environment information. Finally, simulation results verify the superior performance of the proposed algorithm in improving the cumulative network capacity and reducing outages.

scholarly journals Design Parameters of a Miniaturized Piezoelectric Underwater Acoustic Transmitter

Sensors ◽  
2012 ◽  
Vol 12 (7) ◽  
pp. 9098-9109 ◽  
Author(s):  
Huidong Li ◽  
Zhiqun Daniel Deng ◽  
Yong Yuan ◽  
Thomas J. Carlson
Keyword(s):  
Design Parameters ◽  
Underwater Acoustic ◽  
Acoustic Transmitter
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