Iterative Detecting Approach And Simulation Of Serially Concatenated CPM

CPM(The continuous phase modulation) that a kind of modulation signal with invariabla envelope and continuous phase, compared with the other technologies of modulation, has a high efficiency of bandwith and power. And because of its invariable envelope, it is insensitive to the non-linear characteristic of the power amplifier. Besides, the continuous phase make the radicalization outside the bandwith weak, which result in the interference to the adjacent channel weak too. The same as OFDM, CPM has been researched deeply for rencent years and gain abroad regard on aspects of the mobile communication, the satellite communication, the telemetry and so on.Firstly, the basic concept, the spectrum and performance which are the basic characteristics of the CPM signal is discussed. As the CPM signal can be decomposed into a CPE(Continuous Phase Encoder) and a MM(Memoryless Modulator), of which CPE is linear on the integral ring . Therefore, CPM itself can also be seen as a code method. To further improve the power efficiency, CPM as a inner code can be serially concatenated with the binary CC(Convolutional Code) as a outer code, which is a system both has the channel code and the modulation. P. Moqvist and K.R.Narayanan researched on the performance and design of the CPM in AWGN channel. And the results show that SCCPM can significantly improve the power efficiency.Then the iterative detecting algorithm of SCCPM is discussed. And a new SISO algorithm of additive likelihood is claimed, with which the simulation is implemented to the SCCPM . And through the different systems of the simulation, how the convolutional code, the cardinality, the CPM modulation index, the CPM memorial length, the interleaver length and the number of iteration impact on system performance is explored. The simulation results show that system performance gets poor with the increasing state number of convolution code,improves with the increasing number of the cardinality and improves with the increasing memorial length and modulation index at the same time. Besides, the greater length of interleaver and the greater number of iteration, the better system performance can get. Finally, the SISO algorithm of additive likelihood is compared with the SISO algorithm of multiplication, of which the result show a closer performance.