ISSNIP

Energy-Efficient Communication Protocol for Underwater Acoustic Sensor Networks

Investigators
Staff:

Jemal Abbawajy.

Student: Shivali Goel.
Collaborations
Description
Introduction: The availability of tiny sensors and low-power wireless communications will enable the deployment of distributed sensor/actuator networks for a wide range of applications. However, wireless sensor networks pose diverse set of challenges that need to be tackled for efficient deployment of the wireless sensor networks in various environments including underwater.
Significance: In this research, we focus on fundamental wireless networking challenges that underpins wireless sensor network systems. Specifically, a wireless communication system suffers from multipath, Doppler spread and high propagation delays. These effects are more pronounced in a microcell environment due to different types of buildings and irregular distribution of scatterers present in the environment, giving rise to multipath. These multipath signals arrive at the receiver from different directions at different times. All of these multi-paths taken by the wireless signal possess different properties, and hence, each multipath signal has its own distinctive carrier phase shift, amplitude, angle of arrival, and time delay. High propagation delays can further give rise to inter-symbol interference. A possible approach to address these issues is through the geometrical definition of the scattering region to calculate the above parameters. The geometry of the multipath propagation plays a vital role for communication systems to suppress multipath. In the proposed network, the sensors are deployed on the area which has to be effectively covered and an ad-hoc network is established between the sensors to communicate with each other. The system model assumes a cluster based wireless sensor network (WSN) which collects information from these sensors, filters and modulates the data and transmit it through a wireless channel to be collected at the receiver. Using this model, wireless sensor networks can be put into a number of applications like pollution detection systems by monitoring the level of polluting substances and identifying the source in the deployed area, by deploying on buildings and structures these networks can be used to ensure reliability and safety by continuous monitoring, can also be used to detect and locate damages on the deployment area, can be used for home/office automation, motion tracking, intrusion detection and many more.
Applications: The model justifies the use of receive diversity at the receiver for reliable communication between the cluster head and the receiving arrays when applying receive diversity. We also quantify the fact that with the increase in the number of antenna elements, we are able to increase the reliability and robustness of the system. Initially the model parameters and the overall efficiency of the system is solved with lesser number of antenna elements in the receiving array; however, they can be extended to N numbers for a large receiving array.
Challenges: We propose a Geometrically Based Single Bounce Elliptical Model (GBSBEM) for multipath components involving randomly placed scatterers in the scattering region with sensors deployed on a field. We first develop a GBSBE model and based on this model we develop our channel model. We add reliability and robustness to this cluster based WSN by using smart antennas at the receiver. Use of Smart antenna system at the receiver end, which exploits various receive diversity combining techniques like Maximal Ratio Combining (MRC), Equal Gain Combining (EGC), and Selection Combining (SC), adds novelty to this system. The focus of the model is to consider the scenario of local scattering giving rise to multipaths. This multipaths and the resulting fading are modelled as stochastic processes and channel characteristics like time-variation, amplitude, and angular spread are modelled using GBSBEM. Another important issue with the sensor networks is efficient power usage. The model in itself proves that the performance of the system increases if the transmission power increases. Since the cluster head is located very near to the sensor nodes, the sensor nodes do not require high transmission powers so they do not face the reach-back problem.
Publication
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