SUMMARYIn the multi-standard communications systems, the intermediate frequency (IF) signal usually consists of several subband signals with nonequal bandwidths and arbitrary band locations, and in some special cases the number, location and bandwidth of the subband signal are dynamically changeable during receiving. This paper presents an efficient architecture based on nonuniform filter banks to channelise these signals. The nonuniform filter bank can be constructed by directly merging the relevant uniform cosine-modulated filter bank (CMFB) according to the nonuniform matrix. The whole filter design can be boiled down to design a prototype filter that meets some constraints. The proposed structure can be optimised to reduce the computational complexity using the relationships among different decimation factors of different subband signals. Along with signals dynamically changing, new channelisation can be implemented as long as updating the nonuniform matrix. New structure is provided with low cost in hardware and high flexibility. Simulation results are also presented to illustrate its feasibility.
SUMMARYA dual-mode multi-modulus algorithm (DM-MMA) and a stop-and-go dual-mode multi-modulus algorithm (SAG-DMMMA) for blind equalisation of high-order quadrature amplitude modulation (QAM) signals are proposed. Simulation results show the proposed blind equalisation algorithms have faster convergence speed and smaller steady-state mean square error, compared with the recently introduced multi-modulus algorithm.
In this paper, a novel automatic modulation recognition method is proposed based on unsupervised learning Neural Networks, which adopts Self-Organizing Map (SOM) algorithm. Firstly the basic structure of the SOM Neural Networks is described, and then the traditional training algorithm of SOM is improved in terms of learning efficiency and classification performance. Practical Communication signal is made use of testing the method performance. Experiment results illustrate that SOM Neural Networks based digital modulation identification method has higher recognition rate than the method based on Back-Propagation Neural Networks. The method proposed in this paper provides a new approach for communication signal modulation identification.
In the multi-standard mobile base-station or software defined radio system, the received intermediate frequency (IF) signal usually consists of several subband signals with nonequal bandwidth and arbitrary band location. In order to channelize these signals efficiently, this paper presents an architecture based on nonuniform filter banks. In the proposed structure, the whole design of the nonuniform filter bank can be boiled down to design a prototype filter that meets some requirements. In addition to low cost in hardware, new structure can be optimized to reduce the computational complexity using the relationship among different decimators of different subband signals. Simulations are also presented to demonstrate the feasibility of the proposed structure.
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