Transmitter- and receiver-based optimization of signaling-assisted modulation classification in MIMO-OFDM systems with adaptive modulation and coding

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Adaptive modulation and coding is a powerful technique in OFDM systems to optimally adapt the transmit signal to the current state of the frequency-selective propagation channel. One major drawback is that transmitter and receiver must be synchronized with respect to the modulation and coding schemes used on all subcarriers. In mobile communication systems with rapidly varying propagation channels, explicit signaling of these transmit parameters - especially of the modulation schemes - causes a significant reduction of the useful data rate. Alternatively, the bit allocation table which is the list of modulation schemes on the subcarriers can be automatically classified based upon the observed receive signal.The approach investigated here considered the joint optimization of the adaptive transmit algorithm and modulation classification in a time-division-duplex system where a minor amount of signaling information is utilized. The objective of the overall applied project is to develop new methods to classify digital modulation schemes for multiple-input multiple-output (MIMO) systems with adaptive modulation and coding which maximize the system performance in terms of the effective bandwidth efficiency with minimal signaling overhead.In the first funded period new signaling concepts have been developed which increase the accuracy of the the classification on the one hand, but reduce the overhead compared to conventional signaling concepts on the other hand. Moreover, further improvements have been achieved by a joint optimization of the transmitter and receiver strategy. Currently, the classification methods are extended to multiple-antenna systems. The results achieved in the first project phase show ernormeous potential of signaling-based modulation classification also in application to wireless mobile communication systems and motivate further investigations.In the last third of the project herewith applied, the maximum-a-posteriori classification algorithms are to be verified and their parametrization is to be optimized using a software-defined-radio platform. One key factor of a high classification reliability turned out to be the utilization of reciprocity which at least partly exists in the considered time-division duplex system. The amount of reciprocity available in realistic scenarios is to be determined by the implementation of the classification algorithms in an experimental system. From that follows the requirements to the necessary signaling overhead to ensure a reliable classification.