The Blind Channel Equalization For Remote Medical Data Wireless Transmission

Wireless communication is an important technology of data communication in telemedicine, it is mainly used for the remote medical data transmission in field exploration, transportation (e.g., ambulance, etc.), geological disasters, and rural and island which are far away from the town. However, the wireless channel passed by is usually multipath fading, which cause a serious distortion of the receive signal directly. In order to ensure the quality of data transmission, channel equalization is needed. This thesis focuses on the blind channel equalization for remote medical data wireless transmission.It is about forty years ago that the concept "blind equalization" was put forward. Since the blind equalization avoids using training sequences in the whole process, which can save the channel resources and improve the effective utilization rate of channel. As a result, it has caught widely attention in the field and many related algorithms were proposed. This thesis carries on the research and summary on the basis of these predecessors’theories and results, combined with the demand characteristics of telemedicine data transmission for blind channel equalization, and put forward some new algorithms of improvement.First of all, this thesis summarized several typical blind equalization algorithms, namely the blind equalization algorithm based on CR principle, the blind equalization algorithm based on subspace(SS) and the blind equalization algorithm based on linear prediction(LP). SS method and LP method are batch processing, which cannot satisfy the real-time characteristic need for remote medical data transmission, so we propose adaptive algorithms specifically for them two. In addition, many blind equalization algorithm implementations requires to know the channel order, and their performance is usually sensitive to the channel order, so a variety of common blind channel order estimation algorithms are summarized in this thesis, and some general conclusions are drawn after computer simulation experiment.If the channel transmission environment is more open and the multipath interference is smaller, common linear blind equalizer can meet the requirements of transmission quality. However, the wireless channel environment in telemedicine is usually bad, the intersymbol interference is more serious, while the data and information transmitted in the telemedicine is about people’s life and health, which means higher real-time performance and BER performance requirements are needed for blind channel equalization, as a result, the general linear equalizer cannot meet the requirements. The last chapter in this thesis introduces the decision feedback blind equalization (DFE), which can compensate the severe intersymbol interference of the channel due to the feedback structure. In this chapter, firstly introduces two kinds of adaptive DFE algorithm, namely CMDFE algorithm and VCMDFE algorithm. Then, on the basis of these two algorithms, a series of modified variable step DFE algorithms are proposed combined with the variable step size LMS algorithm and DD algorithm. And the simulation results shows that the improved algorithms have better convergence performance and equalization performance.