Contribution of state modelling in efficient MAP symbol-by-symbol demodulation schemes for CPM-MIMO systems
We develop state models describing the CPM demodulation problem for single antenna then for a MIMO system. We derive the corresponding MAP symbol-by-symbol detection schemes based on a matricial implementation of the Bayes filtering equations. Two Bayesian CPM-MIMO demodulators are proposed: the first uses a ZF preprocessing block with a bank of MAPSD CPM demodulators. The second alternative is a joint decision feedback CPM-MIMO MAPSD detector; presenting an implementation simplicity with acceptable complexity. High BER's performance of the suggested CPM-MIMO demodulators, with no constraint on the modulation index or the alphabet size.
continuous phase modulation maximum a posteriori bayesian estimation/detection state space model optimal bayes filtering multi-input multi-output system