Research On Tensor Communication Waveform Generation Model With Semi-blind Receiving Algorithm

The spectrally modulated spectrally encoded(SMSE)is a multi-carrier waveform generation model which can map the paratemeters into waveforms.SMSE can generate different kinds of communication waveforms for the CR-based SDR platform.But the SMSE framework can not be applied in multiple input multiple output(MIMO)systems because of lacking spatial factors and dimensions.Tensor algebra is an effective way to solve the problem of high-order data modeling.Therefore,the main goal of this thesis is to realize the extension of the SMSE framework to the MIMO communication system by tensor decomposition.Firstly,this thesis proposes a new analytical waveform framework based on tensor decomposition and SMSE,called tensor communcation waveform generation model.It is a high-order extension of the SMSE framework.Comparing to the SMSE framework,the proposed model can not only be suitable for a MIMO system,but also more flexible to generate waveforms for the CR-based SDR platform.With the ideal receiver demodulation algorithm,experimental results demonstrate that the proposed framework can not only realize the function of SMSE in the signle input signle output(SISO)system,but also can achieve excellent performaces compared with the methods of Alamouti coding and maximal ratio combining(MRC)in the MIMO system.Secondly,this thesis proposes a new semi-blind receiving algorithm for the proposed framework by the identifiability and uniqueness of tensor decomposition models.The proposed semi-blind receiver demodulation algorithm can jointly estimate user symbols and channel state information without using pilot sequences via alternating least square(ALS)algorithm.It just needs few sequences to eliminate the inherent ambiguity of the proposed algorithm.According to the theoretical and mathematical proof,the identifiability and uniqueness issues of the proposed semi-blind receiver demodulation algorithm can be satisfied.The performance of the proposed semi-blind ALS receiver decreases 3 dB compared with the ideal receiver demodulation algorithm from numerical simulation results.