Iterative Decision-Feedback in Non-Coherent Multi-User Massive MIMO Systems

Recently, methods for the non-coherent detection of signals in multi-user massive MIMO systems were introduced. Based on a block-wise processing of the received signal, sorted decision-feedback differential detection (DFDD) is used to detect the differentially encoded symbols of a particlar user. In order to cope with the multi-user interference in the massive MIMO system, we employ so-called non-coherent decision-feedback equalization (nDFE). Both methods do not require any knowledge of the current channel state, but simply rely on statistical parameters of the channel. Here, we assess the potentials of iterating the nested decision-feedback algorithms applied in the given non-coherent multi-user massive MIMO scenario. In order to identify rewarding (iterative) combinations of DFDD and nDFE, we numerically study ultimate limits for the individual buidling blocks DFDD and nDFE by assuming perfect feedback (genie-aided nDFE and DFDD, respectively).