Channel Estimation For Underwater Acoustic Backscatter Communication Systems

The continuous development of the fifth-generation network(5G)has become the main driving force for the growth of Internet of Things(IoT)applications.Compared with 4G,5G solves the machine type communication(MTC)problem that 4G networks cannot support,i.e.,the key problem of IoT communication.The IoT allows smart devices to interact with each other and share data without human assistance.If millions of smart devices are connected to the IoT,a truly large-scale Internet can be created.5G not only has fast transmission speed and low latency,but also can improve the coverage of MTC,enabling it to be used in more demanding environments.Nowadays,more and more attentions of academia and industry are on the IoT based on 5G technology.Therefore,the research on the related technologies of the IoT continues to promote the vigorous development of the IoT in the 5G era.As one of the important technologies of the IoT,backscatter communication technology solves the problems of energy supply and high cost of traditional IoT sensors,making the application scenarios of the IoT more extensive.Therefore,people considered expanding the application of the IoT from land to underwater,and proposed an underwater acoustic backscatter system,and successfully realized low-power underwater acoustic communication.This paper first introduces the backscattering technology,then leads to its underwater application,and carries out mathematical modeling for this scene,using the traditional orthogonal frequency division multiplexing(OFDM)transmission method to construct underwater sound Backscatter communication system.Finally,this paper studies the channel estimation solutions for emerging underwater acoustic backscatter communication systems:(1)Two traditional channel estimations: least square(LS)and linear minimum mean square error(LMMSE)methods are used to estimate the channels of the underwater acoustic backscatter system.Our simulation results reveal the limitations of traditional channel estimations in the underwater acoustic sparse channel environment.(2)Starting from the basic principle of compressed sensing,we show that compressed sensing is suitable for sparse channel estimation of underwater acoustic backscatter systems,and we choose the gradient projection sparse reconstruction(GPSR)algorithm based on the basic principles of compressed sensing.The basic idea of gradient projection algorithm is introduced,and then the underwater acoustic backscattering channel estimation method based on GPSR algorithm is designed and analyzed.Through MATLAB simulation,the GPSR algorithm is compared with the traditional channel estimation algorithm.The simulation results show that the GPSR algorithm outperforms the traditional estimations in a sparse channel environment.