Study Of Multiuser Detection Technology Based On Compressed Sensing

The ocean contains a variety of rich resources,and it is important for human beings to maintain sustainable development.With the acceleration of human exploration and development of the ocean,underwater sensor networks,one of the key technologies to explore the ocean,have been the focus of research.Because the underwater environment is complex and changeable,the harsh communication environment determines that the underwater sensor network is a typical bandwidth-limited and energy-constraint network.Compressed sensing(CS)theory is a new theory of information acquisition.It can reconstruct the signal accurately by reducing the amount of observation and using the sparsity of the original signal.CS theory can be widely used in sensor network acquisition,multiple access,multi-user detection and so on.It provides a new research scheme for the design of high energy consumption sensor networks.This paper mainly studies the data gathering scheme of the underwater sensor network,focuses on the research of multi-user detection based on CS technology,combined with the compression scheme of data acquisition in the construction of rescourse efficiency network.Firstly,we study the multiuser detection based on CS in sporadic communication scenarios.It introduced the concept and application of sporadic communication scenarios,summed up the general multi-user system model,analyzed the active state node and data detection theory feasibility and advantages and characteristics of sensor nodes using sparse data spatial scattered communication scenario of CS theory.Secondly,we study multi-user detection based on CS in code division multiple access(CDMA)and interleave division multiple access(IDMA),respectively.In the CDMA multiple access mode,the CDMA multi-user system model is summarized.Three greedy matching pursuit algorithms are introduced,which are orthogonal matching pursuit algorithm(OMP),orthogonal least square algorithm(OLS),and group orthogonal matching pursuit algorithm(GOMP),which uses sparse characteristics of original signal blocks.Through simulation analysis and performance comparison of compressed sensing algorithm and the traditional multi-user detection algorithm,compressed sensing measurement matrix as the performance analysis of spread spectrum code and three greedy matching pursuit algorithm performance of multiuser detection.In IDMA multiple access mode,we summarize the multi-user IDMA system model and proposes a CS-CBC algorithm,which takes the advantages of combining CS algorithm and traditional active state by chip-by-chip(CBC)multi-user detection algorithm for data detection.The performance of IDMA multiple access is simulated and the excellent multiuser detection performance of CS-CBC algorithm is verified.Finally,the dual-domain compressed sening(DCS)scheme for data gathering that exploits the spatial sparsity of active sensors’ data and the frequency sparsity that exists in most natural signals is proposed.The way of random collection of data acquisition at sensor nodes contributes to the activiy and data detection at recevier side and the reconstrucution information map at the receiver side.DCS data collection scheme combines the advantages of random acquisition and sparse multi-user detection based on compressed sensing,which results in high efficiency collection.Then,we analyz the advantages of DCS scheme in saving bandwidth and energy consumption.