Underwater acoustic sensor networks

Ocean exploration, through the development of ocean-observation systems, has been recognized as a key step toward a fuller understanding of life on Earth. With the rapid developments in technology, underwater acoustic sensor networks (UASNs) will help to fulfill the needs of these ocean-observation systems, whose applications include gathering of scientific data, early warning systems, ecosystem monitoring, navigation aids, and military surveillance. The applications depending on UASNs are remote control in offshore oil industry, pollution monitoring in environmental systems, collection of scientific data recorded at ocean-bottom stations, disaster detection and early warning, national security and defense (intrusion detection and underwater surveillance), as well as for the discovery of new resources. Due to its importance, UASN has played a key enabling technique for marine technology.

Although a UASN shares many features of a traditional sensor network on land, it has many unique features which require special designs and techniques to handle them. The characteristics of the underwater acoustic channel introduce a unique design complexity into almost every layer of the network protocol stack. This includes low communication bandwidth which reflects on the transmission rate and requires packet sparsing, long propagation delay which necessitates the design of specialized scheduling mechanisms, high error probability that leads to need for two efficient transport protocols, and sensor node mobility which affects packet routing.

This special issue introduces state-of-the-art trends in the design and applications of UASNs. Both theoretical and practical issues related to UASNs are considered. The focus is on the physical layer, the medium access control (MAC) layer, and the network layer. Out of the many high-quality submissions, the papers chosen focus on signal detection, channel coding, transmission scheduling, power control, and routing. The contributions in this special issue present a thorough analysis, algorithmic design, numerical simulations, and results from sea experiments.

The original works in physical layer include three contributions. In UASNs, multipath propagation is unavoidable. The multipath propagation decreases the transmission efficiency and distorts the source signal. In “Alternative Approach for Combination of Fingers in Underwater Acoustic Communication,” the authors propose a more reliable rake receiver based on bit error rate (BER) of training sequence duration. The authors conducted experiments using simulation and also lake trials to evaluate its performance. The authors show that the uncoded BER of the proposed rake receiver is lower than that of the conventional rake receiver and that of the nonrake receiver. The proposed method also shows better performance with correct path detection using BER of training sequence duration.

The authors of “The Partial Power Control Algorithm of Underwater Acoustic Sensor Networks Based on Outage Probability Minimization” focus on reducing the energy consumption of the UASN. A solution is offered to reduce interference due to high-power transmission by modeling the channel as an auto-regression process and estimating the transmission loss, thereby minimizing the outage probability in the network.

In the work titled “Optimization of LDPC Codes over the Underwater Acoustic Channel,” the authors propose a channel coding scheme that combats the large delay spread in the channel through feedback from the channel equalizer and the channel decoder. The result is a low-density parity check decoder optimized to the unique channel conditions of the underwater acoustic channel.

Due to the non-negligible physical restrictions of the UASN communication, most MAC protocols used in existing terrestrial sensor networks become inapplicable. The MAC layer of the network is considered in “MHM: A Multiple Handshaking MAC Protocol for Underwater Acoustic Sensor Networks.” The main idea is to allow multiple nodes to transmit and receive data packets at the same time. The authors propose a multiple handshaking MAC protocol for three UASNs. Using the multiple handshaking and a competitive mechanism of control packets, the new protocol makes the contending nodes share the underwater acoustic channel much more fairly and efficiently. Analysis and simulation results are used to validate their claims.

The authors of “Throughput and Delay Analysis of an Underwater CSMA/CA Protocol with Multi-RTS and Multi-DATA Receptions” proposed an underwater carrier sensing multiple access with collision avoidance (CSMA/CA) protocol with multi-request-to-send (RTS) and multi-DATA receptions using the long underwater propagation delay. The benefit of the method lies in that it does not need to maintain the information of inter-node propagation delay. When there are simultaneous transmissions of RTS frames to an underwater sink, the sink can recover some RTS frames which are not overlapped. Then, the sink transmits clear-to-send (CTS) frame containing the DATA transmission order and the IDs of the sensors which transmitted the recovered RTS frames. Sensors which correspond to the IDs contained by the CTS frame can transmit DATA frame to the sink according to the DATA transmission order. They analyze the throughput and delay of the proposed underwater CSMA/CA protocol through a ring-based underwater network modeling. The analytical and simulation results show that the proposed protocol outperforms the conventional protocols.

The work in “Minimum Delay Multipath Routing Based on TDMA for Underwater Acoustic Sensor Network” suggests a network layer protocol. The authors utilize the large delay difference among the first and third hops to allow parallel transmission. The transmissions are scheduled such that conflict-free transmission is maintained. Then, rather than hop-by-hop transmission, routing is performed in groups of conflict-free hops. The result is a large decrease in the packet delivery delay.

In “Belief Propagation-Based Cognitive Routing in Maritime Ad Hoc Networks,” a cognitive routing method is proposed in order to find a stable path between source and destination. A belief propagation algorithm is applied for collaborative spectrum sensing. Every user exchanges its local decisions with its neighbors to compute the final belief about the state of the channel. These beliefs are applied for estimating the link duration for total number of hops between source and destination. Then, a path is selected which maximizes the path duration among all the paths in the network to reach the destination. Through simulation, they conclude that the scheme provides stable path selection.

Considering that the data from an UASN is almost always referred with respect to its geographical environment, the work in “ADOS-CFAR Algorithm for Multi-Beam Seafloor Terrain 4 Detection” provides a solution for mapping the underwater terrain. The proposed solution combines order statistics detection with threshold-based constant false alarm rate to mitigate the tunnel effect using a multi-beam sonar. The authors constructed their own hardware system and show results for mapping the train of a shallow river.