Research On Blind Equalization And Identification Of Time-Varying Dispersive Channels In Wireless Communications

In wireless and mobile communications, blind equalization and identification of dispersive channels is a very hot research topic recently, and it is especially a technical difficulty to identify and equalize the time-varying (TV) dispersive channels blindly. It is just now in its infant period as for the theoretic research in this field. In this thesis, we try our best to investigate it deeply based on some of the precedents 's work.The idea of diversity is emphasized in this thesis in signal processing perspective, and two schedules are proposed to perform it. We propose the joint filterbank precoders and decision feedback equalizers structure at first, by which the dispersive channel is equivallent into parallel independent flat fading subchannels such that the diversity gain of the receiver is increased. Then we adopt the discrete-time (DT) canonical model to convert the problem of blind signal processing of TV dispersive channels into processing the time-invariant multi-channels model blindly, and discuss the problem of blind equalization and identification of TV dispersive channels based on this new model. The problem of implementation of blind equalization algorithms is also discussed, and we propose a simple algorithm that is suitable for implementation.A serial of new results of this thesis exists in the following. Firstly, a new joint filterbank precoders and decision feedback equalizers structure is proposed, and the corresponding optimization result based on the maximal mutual information criterion is derived. Secondly, the concept of DT canonical model is proposed, which is very suitable for the task of blind signal processing based on the second-order statistical of the observations. Thirdly, the methods of blind equalization and identification of the TV dispersive channels are researched systematically based on the proposed DT canonical model, and a subspace blind identification algorithm of the time-invariantchannel matrix is developed. Fourthly, as for the problem of error propagation effects, a new two-stage blind identification algorithm is proposed which can eliminate the error propagation. Fifthly, a direct blind equalization algorithm is given based on the DT canonical model. And the last but not the least, a neural network direct adaptive blind equalization algorithm is proposed based on the idea of property recovery.The very recent results of blind equalization and identification of the TV dispersive channels in wireless communications are reviewed at first in detail, the drawbacks of them are pointed out and the basic idea overcoming them are suggested, which is the motivation of this thesis.Then the basic principles of blind equalization and identification technology are introduced simply. As the theory foundation of this thesis, some important relative mathematics tools are outlined.In chapter 3, based on the idea of joint equalization, we adopt the decision feedback equalizers to perform the second equalization to overcome the problem of filterbank precoders-linear equalizers joint optimization proposed recently, and get a new optimal result. This method can convert the dispersive channels into independent flat fading subchannels, so that it increase the diversity gain of the receiver and outperform that of the original paper as for the BER performance and maximum mutual information while maintaining all the advantages of it.In chapter 4, the models of the TV dispersive channels are reviewed in signal processing perspective. After that, the concept of DT canonical model in the CDMA context is proposed to overcome the drawbacks of complex exponenial basis expansion models and the continual-time canonical models. Then this new model is disscused in detail and is extended to some more common TV dispersive channels.In the following chapter 5, we do much effort to research the methods of blind equalization and identification of TV dispersive channels based on the proposed DT canonical model. As for the indirect blind equalization, we first propose a subspace metho...