Research On Blind Signal Detection Techniques In Adaptive Single- And Multi-Carrier Modulation

As one of the key techniques of new generation mobile communication systems and broadband wireless communications systems, "Adaptive transmission" technique can exploit potential channel transmission ability sufficiently so that it enables the systems to reach the maximum transmission capacity and reliability by dynamically adjusting transmission parameters according to channel estimation and traffic QoS requirement.The most important character of the next generation mobile system will be smart transmission whose function module will be implemented by smart processing unit. This paper deals with the blind detection techniques in adaptive transmission. The main research works and results are listed as follows.1. Methods of estimating baud rate, Signal to Noise Ratio (SNR) and reference phase are investigated. A modified Euclidean algorithm is proposed to estimate baud rate of the burst packets. A cumulant based algorithm of estimating SNR of star-QAM is proposed which has better estimation performance in medium scope of SNR.2. The blind modulation detection algorithms in adaptive single- and multi-carrier modulation are studied. The principles of adaptive star-QAM and the optimum constellation of star QAM are given. In adaptive single-carrier modulation, a blind modulation detection algorithm based on Higher Order Cumulants (HOC) for AQAM and APSK is proposed. The excellent detection performance of algorithm is evaluated in Gaussian and narrow-band Rayleigh fading channel. In adaptive multi-carrier modulation, the principle of blind detection assisted adaptive OFDM (AOFDM) is given and a blind modulation detection algorithm is proposed for AOFDM in frequency selective fading channel. The performance of the algorithm is compared with the available algorithms and the effectiveness and robustness of the blind detection algorithm are proved through simulation.3. Take the HOC based blind modulation detection algorithm as an example, the relationship between the blind modulation detection algorithm and synchronization is investigated. An unproved detection algorithm robust to frequency offset is proposed which solves the problem caused by the error incarrier synchronization. How to synchronize a received signal with unknown modulation type is studied and a blind algorithm to estimate symbol timing of the signals with unknown modulation type is presented. The algorithm finds the best samples for the unknown received signals and realizes coherent recognition of modulations. An adaptive receiver structure is proposed which combines the blind modulation detection, SNR estimation, synchronization and demodulation. The receiver can properly receive the adaptive modulated signals.4. The design of classifier is dealt with and the support vector machine (SVM), a new result of statistics learning theory, is used in modulation recognition firstly. The choice of classification feature is analyzed. The classification feature vectors are extracted from Multi-level Wavelet Decomposition (MWD) and HOC of the received signals. SVM maps input vectors nonlinearly into a high dimensional feature space and constructs the optimum separating hyperplane in the spade to realize modulation recognition. Moreover, this method is robust to the variety of SNR and avoids overfitting and local minimum in neural nelwork. The percenlage of correcl idenlificalion for signals is salisfied wilh the fewer training data.