Scalable Cell-Free Massive MIMO Systems with Finite Resolution ADCs/DACs over Spatially Correlated Rician Fading Channels

This paper presents the first performance analysis in scalable cell-free massive MIMO (SCF-mMIMO) systems by proposing a novel mathematical framework which accommodates for the first time 1-bit quantization (1 b-Q) and multi-bits quantization (Mbits-Q) models. Assuming that each user equipment (UE) and access point (AP) employs finite resolution digital-to-analog converters (DACs) and analog-to-digital converters (ADCs) respectively, and by considering communication over spatially correlated Rician fading for the UE-AP channel, a novel Bussgang MMSE (B-MMSE) channel estimator for the 1 b-Q model is proposed. This approach leads to the derivation of generic spectral efficiency (SE) expressions using maximal ratio combining (MRC) and MMSE detections which are applicable also for the Mbits-Q case. In order to further improve the energy efficiency (EE) by using MMSE detection, two novel MMSE detectors, termed as low complexity local partial MMSE (LC-LP-MMSE) and LC-P-MMSE detectors, are proposed. Simulation results have shown that their SE performance is near to that of the optimal L-MMSE and MMSE detectors, while at the same time their EE performance is significantly improved as compared to the conventional LP-MMSE and P-MMSE detectors. Finally, a low complexity accessing scheme which jointly considers the competition-free cluster formation, pilot assignment, and power control, is proposed. Simulation results have shown that it outperforms the conventional random pilot assignment and user-group based pilot assignment schemes. Furthermore, in contrast to the equal power transmit strategy, it guarantees quality of service (QoS) fairness for all UEs.