Research On Symbol Timing Synchronization And Adaptive Equalization In Wavelet Packet Transform Based Multicarrier Modulation Communication System

Meeting the need of real time multimedia and Internet access services for the coming wireless communication, whenever and wherever wireless data can be transmitted with high speed and great quality, which is the main advancing direction of the fourth generation wireless communication technique. Multi-carrier modulation (MCM) has become the pivotal technique for its favorable validity and reliability. Wavelet Packet transform based multi-carrier modulation (WPT-MCM) communication system which integrates Wavelet theory with multi-carrier has become the main researching direction of MCM technique, it has a lot of excellences, such as the high frequency efficiency, being easily realized to the multi-speed transmission, and better immunity against interference, et al. In this dissertation, it was analyzed and researched about the symbol timing synchronization and adaptive equalization of WPT-MCM communication system. The main content is outlined as the following:Firstly, the basic Wavelet/Wavelet Packet theory were introduced which are the important base of Wavelet/Wavelet Packet transform based multi-carrier modulation theory and algorithm, and then, WPT-MCM technique was introduced as well as its Power Spectral Density (PSD) and Bandwidth Efficiency (BE). Several WPT-MCM schemes were analyzed and compared each other, such as Fractal Modulation, Wavelet Packet Division Multiplexing (WPDM) and Branch-hopped Wavelet Packet Division Multiplexing (BH-WPDM). Then, the integrated implementing scheme of WPT-MCM communication system was designed in which WPDM was used to being modulated scheme, accordingly, it provide the integrated frame for the following researching the key techniques about WPT-MCM communication system.Secondly, the symbol timing synchronization of WPT-MCM communication system was researched. By introduced the principle of symbol timing synchronization in communication system, there was detailed analysis about the all process of symbol timing synchronization and the symbol timing synchronization of MCM system, sequentially, it was shown how symbol timing offset did harm to WPT-MCM communication system. Consequently, aimed at the shortcomings of several old symbol timing synchronization methods, a new Decision-Aided Extended Kalman Filter (EKF) based Adaptive Timing synchronization for Wavelet Packet Modulated Signals was introduced detailedly. The proposed algorithm gives faster convergence, smaller root mean square (RMS) errors and better bit error rate (BER) performance than traditional timing recovery methods. Thus, the algorithm is able to handle larger timing errors more reliably and to provide with better timing recovery, since the scheme takes into account the nonlinear relationship between the signal samples and timing errors, and the affect of frequency offset. Simulations for various time-varying channels show that the timing recovery algorithm works well for Wavelet Packet transform-based multicarrier modulation communication system. Aiming at the several flaws of the symbol timing synchronization method proposed in the prior article, Decision-Aided Extended Kalman Filter (EKF) based Adaptive Timing synchronization was ameliorated and a new Unscented Kalman Filter (UKF) based Adaptive Timing synchronization was introduced detailedly. Also, Simulations for various time-varying channels show that the proposed UKF based timing recovery algorithm improves greatly the performance of Wavelet Packet transform-based multicarrier modulation communication system.Finally, adaptive equalization was researched detailedly for WPT-MCM communication system. On the basis of introducing equalizing theory, the significance of equalizing technique to WPT-MCM system was proved through analyzing in detail about the performance of WPT-MCM system in several different channel models and the advance after using equalizing technique for WPT-MCM system. Accordingly, adaptive equalization algorithm based on Wavelet Neural Networks (WNN) trained with EKF algorithm was presented. Since the study course of training weights for WNN was equal to estimate parameters of the nonlinear system, the weights of WNN was estimated by EKF algorithm under the rule of minimizing Mean Square Error (MSE). Compared with traditional neural networks based equalization, the main features of the proposed algorithm are fast convergence and good performance using relatively short training symbols, all of these can provide with better performance of equalization. At the same time, it is demonstrated by simulation results that WPT-MCM system using the proposed equalizing method can provide greater immunity to multipath fading channels than the traditional OFDM system. The proposed algorithm is fit for WPT-MCM communication system.Since derivative matrix (Jacobian matrix) need to be computed in the course of linearization for EKF, it is inevitable to bring computing inverse matrix errors. So this will degrade the performance of EKF based WNN equalizer. Aimed at this disadvantage of EKF, an adaptive equalization scheme using a RWNN trained with unscented Kalman filter (UKF) algorithm was presented. This scheme takes UKF as training algorithm which voids to compute Jacobian matrix and improves the estimating precision by the method of extending training sequence. The performance of the proposed scheme was analyzed in two multipath channel models which were linear time-varying channel and nonlinear time-varying channel model. It was demonstrated by simulation results that the performance about convergence speed and Bit Error Rate (BER) of the proposed scheme is improved greatly, besides, this scheme can also provide greater immunity to nonlinear interference and multipath frequency selective fading, compared with several traditional neural networks based equalization algorithms. So the proposed equalization scheme improves greatly the reliability of WPT-MCM communication system for the intricate and changeful transmission environment.