scholarly journals A Study of Standardizing Frequencies Using Channel Raster for Underwater Wireless Acoustic Sensor Networks

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5669
Author(s):  
Changho Yun ◽  
Suhan Choi
Keyword(s):  
Sensor Networks ◽  
Computational Complexity ◽  
Frequency Band ◽  
Performance Metrics ◽  
Underwater Acoustic Communication ◽  
Acoustic Sensor ◽  
Collision Rate ◽  
Acoustic Frequency ◽  
Upper Limit ◽  
Acoustic Sensor Networks

In this paper, we propose the method to standardize acoustic frequencies for underwater wireless acoustic sensor networks (UWASNs) by applying the channel raster used in the terrestrial mobile communications. The standardization process includes: (1) Setting the available acoustic frequency band where a channel raster is employed via the frequency specification analysis of the state-of-the art underwater acoustic communication modems. (2) Defining the center frequencies and the channel numbers as a function of channel raster, and the upper limit of the value of channel raster. (3) Determining the value of the channel raster suitable for the available acoustic frequency band via simulations. To set the value, three performance metrics are considered: the collision rate, the idle spectrum rate, and the receiver computational complexity. The simulation results show that the collision rate and the idle spectrum rate according to the value of channel raster have a trade-off relationship, but the influence of channel raster on the two performance metrics is insignificant. However, the receiver computational complexity is enhanced remarkably as the value of channel raster increases. Therefore, setting the value of channel raster close to its upper limit is the most adequate in respect of mitigating the occurrence of a collision and enhancing the reception performance. The standardized frequencies based on channel raster can guarantee the frequency compatibility required for the emerging technologies like the Internet of Underwater Things (IoUT) or the underwater cognitive radio, but also improves the network performance by avoiding the arbitrary use of frequencies.

scholarly journals Convex optimization–based multi-user detection in underwater acoustic sensor networks

2018 ◽  
Vol 14 (2) ◽  
pp. 155014771875766 ◽  
Author(s):  
Jianping Wang ◽  
Shujing Zhang ◽  
Wei Chen ◽  
Dechuan Kong ◽  
Zhou Yu
Keyword(s):  
Sensor Networks ◽  
Computational Complexity ◽  
Convex Optimization ◽  
Code Division Multiple Access ◽  
Multiple Access ◽  
Acoustic Sensor ◽  
Underwater Acoustic Sensor Networks ◽  
Underwater Acoustic ◽  
Acoustic Sensor Networks ◽  
Code Division Multiple

Multi-carrier code-division multiple access is an important technical means for high-performance underwater acoustic sensor networks. Nevertheless, severe multiple access interference is a huge challenge. As the core technology, multi-user detection is used to eliminate multiple access interference. The traditional optimal detection algorithms (e.g. maximum likelihood) have very high computational complexity, and the performances of suboptimal detection methods (i.e. zero forcing, minimum mean square error, etc.) are poor. Therefore, taking into account the characteristics of underwater acoustic sensor networks, it is of great significance to design multi-user detection algorithms for achieving a tradeoff between the detection performance and the computational complexity in multi-carrier code-division multiple access systems. In this article, we design a transmitter model of underwater multi-carrier code-division multiple access system and then implement a multi-user detection algorithm based on convex optimization, which is named convex optimization–based algorithm. Next, we conduct the detection performance and computational complexity comparisons of maximum likelihood, zero forcing, minimum mean square error, and convex optimization–based algorithm. The results show that the performance of convex optimization–based algorithm is close to that of maximum likelihood, and the complexity is close to that of zero forcing. Therefore, a tradeoff between the computational complexity and the detection performance is realized in convex optimization–based algorithm. It means that convex optimization–based algorithm is suitable for the multi-user detection in multi-carrier code-division multiple access systems of underwater acoustic sensor networks.

scholarly journals Packet Flow Based Reinforcement Learning MAC Protocol for Underwater Acoustic Sensor Networks

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2284
Author(s):  
Ibrahim B. Alhassan ◽  
Paul D. Mitchell
Keyword(s):  
Sensor Networks ◽  
Mac Protocol ◽  
Propagation Delay ◽  
Basic Function ◽  
Acoustic Sensor ◽  
Underwater Acoustic Sensor Networks ◽  
Medium Access ◽  
Underwater Acoustic ◽  
Q Learning ◽  
Acoustic Sensor Networks

Medium access control (MAC) is one of the key requirements in underwater acoustic sensor networks (UASNs). For a MAC protocol to provide its basic function of efficient sharing of channel access, the highly dynamic underwater environment demands MAC protocols to be adaptive as well. Q-learning is one of the promising techniques employed in intelligent MAC protocol solutions, however, due to the long propagation delay, the performance of this approach is severely limited by reliance on an explicit reward signal to function. In this paper, we propose a restructured and a modified two stage Q-learning process to extract an implicit reward signal for a novel MAC protocol: Packet flow ALOHA with Q-learning (ALOHA-QUPAF). Based on a simulated pipeline monitoring chain network, results show that the protocol outperforms both ALOHA-Q and framed ALOHA by at least 13% and 148% in all simulated scenarios, respectively.

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