Max-Log-MAP Optimal MU-MIMO Receiver for Joint Data Detection and Interferer Modulation Classification.

We consider a multi-user multiple-input multiple-output (MU-MIMO) system that uses orthogonal frequency division multiplexing (OFDM). Several receivers are developed for data detection, where the receivers have partial state information about the MU-MIMO transmission; however, the modulation constellation of the co-scheduled users is unknown. We propose a joint data detection and maximum likelihood (ML) modulation classification (MC) of the co-scheduled user. We show that the decision metric for MC is an accumulation of the Euclidean distances used by the ML single-user MIMO detector. An efficient hardware architecture emerges that exploits this commonality between the classification and detection steps and results in sharing of hardware resources.