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Contribution of state modelling in efficient MAP symbol-by-symbol demodulation schemes for CPM-MIMO systems

机译：CPM-MIMO系统中有效MAP逐符号解调方案中状态建模的贡献

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摘要

In [1], a state space model was derived for the demodulation of Continuous Phase Modulation (CPM) signals, based on which the demodulation problem was solved through the symbol-by-symbol Bayesian estimation built around the MAP Symbol-by-symbol Detector (MAPSD). In this paper, a new state space model considered in the augmented state composed of the symbol and the phase state is proposed and the corresponding modified MAPSD demodulation scheme is presented. The main contribution of the paper however consists in deriving optimal and suboptimal symbol-by-symbol MAP detection schemes for MIMO systems operating with CPM signals. For this, a state model description of the corresponding demodulation problem is introduced based on which two CPM-MIMO Bayesian demodulators are proposed. The first one uses a Zero Forcing (ZF) pre-processing block to separate the different CPM signals followed by a bank of MAPSD based CPM demodulators. The second demodulator consists in a joint decision feedback (DF) CPM-MIMO MAPSD detector. Simulations confirm the good performance in term of BER of both proposed structures. Particularly, high BER's performance of the partially joint CPM-MIMO-MAPSD/DF is recorded and an emphasis is made on the implementation simplicity of this new detector with no constraint on the modulation index or the alphabet size.
机译：在[1]中，导出了用于解调连续相位调制（CPM）信号的状态空间模型，在此基础上，通过围绕MAP逐符号检测器建立的逐符号贝叶斯估计解决了解调问题。 （MAPSD）。提出了一种新的状态空间模型，该模型考虑了一个由符号和相位状态组成的增强状态，并提出了相应的改进的MAPSD解调方案。然而，本文的主要贡献在于为使用CPM信号的MIMO系统推导最优和次优的逐符号MAP检测方案。为此，介绍了相应解调问题的状态模型描述，并在此基础上提出了两个CPM-MIMO贝叶斯解调器。第一个使用零强制（ZF）预处理模块来分离不同的CPM信号，然后使用一组基于MAPSD的CPM解调器。第二个解调器包含一个联合决策反馈（DF）CPM-MIMO MAPSD检测器。仿真证实了两种结构在BER方面的良好性能。特别是，记录了部分联合CPM-MIMO-MAPSD / DF的高BER性能，并强调了这种新型检测器的实现简便性，而对调制指数或字母大小没有任何限制。

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