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Employing low resolution analog-to-digital converters in massivemultiple-input multiple-output (MIMO) has many advantages in terms of totalpower consumption, cost and feasibility of such systems. However, suchadvantages come together with significant challenges in channel estimation anddata detection due to the severe quantization noise present. In this study, wepropose a novel iterative receiver for quantized uplink single carrier MIMO(SC-MIMO) utilizing an efficient message passing algorithm based on theBussgang decomposition and Ungerboeck factorization, which avoids the use of acomplex whitening filter. A reduced state sequence estimator with bidirectionaldecision feedback is also derived, achieving remarkable complexity reductioncompared to the existing receivers for quantized SC-MIMO in the literature,without any requirement on the sparsity of the transmission channel. Moreover,the linear minimum mean-square-error (LMMSE) channel estimator for SC-MIMOunder frequency-selective channel, which do not require any cyclic-prefixoverhead, is also derived. We observe that the proposed receiver hassignificant performance gains with respect to the existing receivers in theliterature under imperfect channel state information.

A Reduced Complexity Ungerboeck Receiver for Quantized Wideband Massive SC-MIMO