Node Activity Scheduling Scheme For Underwater Sensor Network Based On Compressed Sensing

Marine scientific research,civil development or marine military activities must be based on marine environmental information.Therefore,the growing demand for understanding ocean is driving the construction of large-scale and efficient ocean monitoring sensor networks.Underwater sensor networks based on compressed sensing framework can provide energy-efficient and high-efficiency solutions for large-scale underwater information acquisition.For the center-type underwater sensor network which has sensor nodes with different data transmission costs,the node activity scheduling results of the information acquisition mode based on compressed sensing have direct impacts on the network energy consumption and the accuracy of data reconstruction.Therefore,the thesis is based on the information acquisition mode of underwater sensor network in the compressed sensing framework.With the difference of the data transmission cost between the sensor node and the sink node,this thesis explores the node activity scheduling scheme and the multi-user detection method adapted to it.This is of positive significance for building energy-efficient and high-efficiency underwater sensor network for environment information acquisition.Firstly,the information acquisition mode of sensor network under the compressed sensing framework and the traditional random strategy of node activity scheduling are introduced.Secondly,on the basis of the two-dimensional center-type underwater sensor network model,the attenuation and noise of underwater channel are described,and the calculation method of single-hop transmission energy consumption related to the transmission distance is given,which is seen as the difference of the data transmission cost for each node in this thesis.Then,based on the consideration of the difference of data transmission cost for each node,this thesis focuses on the design of the node activity scheduling scheme for the underwater sensor network under the compressed sensing framework.The principle of scheme design is to implement the strategy of saving network energy consumption on the basis of data reconstruction accuracy constraint.And the optimization problem based on this principle is solved at the sink node for node activity scheduling.This thesis simulates the information acquisition processes for underwater environment based on the node activity scheduling scheme which considers transmission cost and random strategy of node activity scheduling.Meanwhile the thesis compares the performances of the two node activity scheduling schemes in the two aspects of the data reconstruction precision and the network survival time.It mainly includes two parts:small observation area with single sink node and large observation area with multiple sink nodes.The simulation results show that,the node activity scheduling scheme givenin the thesis makes the network survival time effectively extended,but also reduces the accuracy of data reconstruction.In addition,for larger observation areas,there should be multiple sink nodes for node activity scheduling and data recovery in partial areas.Finally,by analyzing the activity detection when users' activity information are unknown,this thesis also pays attention to the multi-user detection method which is adapted to the node activity scheduling operation at the sink node.That is to say,the sink node can use the known activity information to perform more complex multi-user detection algorithm which is of better performance.This thesis introduces the multi-user detection algorithm under interleave division multiple access and low-density signature,and compares the BER performances of these two processing methods.It can be seen from the simulation results that the multi-user detection based on low-density signature can achieve better BER performance.