Performance of electromagnetic communication in underwater wireless sensor networks

Underwater wireless sensor networks (WSNs) composed of a number of sensor nodes that are deployed to conduct a collaborative monitoring task. Wireless signals are used for communication between the sensor nodes. Acoustic signals are the dominant signals used as a wireless communication medium in underwater WSNs due to the relatively low absorption in the underwater environments. Acoustic signals face a lot of challenges such as ambient noise, manmade noise, limited bandwidth, multipath and low propagation speed. Some of these challenges become more severe in shallow water environment where a high level of ambient and mankind noise, turbidity and multipath propagation are available. Therefore, electromagnetic signals can be applied as an alternative communication signal for underwater WSNs in the shallow water. In this project, the performance of EM communication in underwater WSNs is investigated for the shallow water environment. Theoretical calculations and practical experiments are conducted in fresh and seawater. It is shown that signals propagate for longer ranges in freshwater comparing to seawater. Theoretical results show that attenuation of electromagnetic communication in seawater is much higher than in fresh water. The attenuation is increasing with the increasing of frequency. In addition, velocity of the signal is increasing as the frequency is increasing while loss tangent is decreasing as the frequency increasing. Based on practical experiments, freshwater medium permits short ranges EM communication that does not exceed 25.1 cm for 2.4 GHz frequency. On the other hand, communication in seawater is very difficult to achieve for the same high frequency. Path loss exponent was estimated for freshwater environment based on logdistance path loss model. The estimation was achieved through a comparison between theoretical calculations and practical measurements. The path loss exponent for EM communication in fresh water was estimated to be in the range of 2.3 to 2.4

Reconfigurable Intelligent Surfaces in Challenging Environments: Underwater, Underground, Industrial and Disaster

Reconfigurable intelligent surfaces (RISs) have been introduced to improve the signal propagation characteristics by focusing the signal power in the preferred direction, thus making the communication environment "smart". The typical use cases and applications for the "smart" environment include beyond 5G communication networks, smart cities, etc. The main advantage of employing RISs in such networks is a more efficient exploitation of spatial degrees of freedom. This advantage manifests in better interference mitigation as well as increased spectral and energy efficiency due to passive beam steering. Challenging environments comprise a range of scenarios, which share the fact that it is extremely difficult to establish a communication link using conventional technology due to many impairments typically associated with the propagation medium and increased signal scattering. Although the challenges for the design of communication networks, and specifically the Internet of Things (IoT), in such environments are known, there is no common enabler or solution for all these applications. Interestingly, the use of RISs in such scenarios can become such an enabler and a game changer technology. Surprisingly, the benefits of RIS for wireless networking in underwater and underground medium as well as in industrial and disaster environments have not been addressed yet. In this paper, we aim at filling this gap by discussing potential use cases, deployment strategies and design aspects for RIS devices in underwater IoT, underground IoT as well as Industry 4.0 and emergency networks. In addition, novel research challenges to be addressed in this context are described.Comment: 16 pages, 13 figures, submitted for publication in IEEE journa

Measuring the underwater received power behavior for 433 mhz radio frequency based on different distance and depth for the development of an underwater wireless sensor network

Underwater wireless sensor network (UWSN) important to enhance the widely use of the application of the Internet of things (IoT) for underwater. Uses of the acoustics base of wave propagations are the best ways to establish the UWSN. But the unpracticality of the hardware due to the size and cost has limited the application of UWSN. Radio frequency (RF) wave propagation is the best way to overcome this situation. Low frequency of the RF wave is proven feasible and suitable for underwater communication. 433 MHz RF were chosen to measuring the underwater received power behavior between the transmitter node and receiver node based on different distance and depth. HC12 transceiver module was used as a transmitter and spectrum analyzer with the telescopic antenna was used as a receiver. The received power give a good reading when the transmitter note was at 0.5-meter depth with a maximum operating range within 12 meters from the receiver

Underwater Wireless Communications in Freshwater at 2.4 GHz

Publisher copyright and source must be acknowledged with citationThere are few equations for underwater communications in the related literature. They show that the speed propagation and absorption coefficient in freshwater are independent of the working frequency of the transmitted signals. However, some studies demonstrate that electromagnetic waves present lower losses when they are working at certain frequencies. In this paper, we perform a set of measurements of electromagnetic (EM) waves at 2.4 GHz in the underwater environment. In our study case, we fix the water conditions and we measure the behavior of EM as a function of several network parameters such as the working frequency, data transfer rates and modulations. Our results will show that higher frequencies do not mean worse network performance. We will also compare our conclusion with some statements extracted from other works.This work has been partially supported by the Ministerio de Ciencia e Innovacion, through the Plan Nacional de I+D+i 2008 - 2011 in the Subprograma de Proyectos de Investigacion Fundamental, project TEC2011 - 27516, and by the Polytechnic University of Valencia, through the PAID-05-12 multidisciplinary projects, Ref: SP20120420. This work has also been partially supported by the Instituto de Telecomunicacoes, Next Generation Networks and Applications Group (NetGNA), Portugal, and by National Funding from the FCT Fundacao para a Ciencia e a Tecnologia through the PEst - OE/EEI/LA0008/2013 Project.Sendra Compte, S.; Lloret, J.; Rodrigues, JJPC.; Aguiar, JM. (2013). Underwater Wireless Communications in Freshwater at 2.4 GHz. IEEE Communications Letters. 17(9):1794-1797. https://doi.org/10.1109/LCOMM.2013.072313.131214S1794179717

Underwater Wireless Sensor Communications in the 2.4 GHz ISM Frequency Band

One of the main problems in underwater communications is the low data rate available due to the use of low frequencies. Moreover, there are many problems inherent to the medium such as reflections, refraction, energy dispersion, etc., that greatly degrade communication between devices. In some cases, wireless sensors must be placed quite close to each other in order to take more accurate measurements from the water while having high communication bandwidth. In these cases, while most researchers focus their efforts on increasing the data rate for low frequencies, we propose the use of the 2.4 GHz ISM frequency band in these special cases. In this paper, we show our wireless sensor node deployment and its performance obtained from a real scenario and measures taken for different frequencies, modulations and data transfer rates. The performed tests show the maximum distance between sensors, the number of lost packets and the average round trip time. Based on our measurements, we provide some experimental models of underwater communication in fresh water using EM waves in the 2.4 GHz ISM frequency band. Finally, we compare our communication system proposal with the existing systems. Although our proposal provides short communication distances, it provides high data transfer rates. It can be used for precision monitoring in applications such as contaminated ecosystems or for device communicate at high depth