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Register a new userShared Angles-of-Departure in Massive MIMO Channels: Correlation Analysis and Performance Impact
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Added by
Xu Du
Publication date
2020
fields
Informatics Engineering
and research's language is
English
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In practical environments, recent massive MIMO measurements demonstrate that user channels can be correlated. In this paper, we study the user channel correlation induced by shared angles-of-departure. We first derive the user correlation distribution in the large array regime, and then examine the user correlation using actual measurements from a large array. As a data-driven observation, we discover that the correlation of all close-by users is higher than $0.4$ and barely reduces as the number of base-station antennas $M$ increases beyond $36$ antennas. Furthermore, nearly one-third of users, even when they are tens of wavelengths apart, have a correlation that is more than twice the correlation of an i.i.d. Rayleigh fading model. Lastly, we characterize the impact of user correlation on system performance. As $M$ increases, conjugate beamforming systems suffer a linearly growing inter-user interference due to correlated channels. However, for zero-forcing beamforming systems, the inter-user interference is a constant that does not increase with M. In particular, zero-forcing beamforming systems can serve a linearly increasing number of correlated users and achieve a linear growth in the system achievable rate as $M$ increases. Hence, spatial multiplexing correlated users can be an attractive massive MIMO design.
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In this paper, an analytical framework for evaluating the performance of scalable cell-free massive MIMO (SCF-mMIMO) systems in which all user equipments (UEs) and access points (APs) employ finite resolution digital-to-analog converters (DACs) and analog-to-digital converters (ADCs) and operates under correlated Rician fading, is presented. By using maximal-ratio combining (MRC) detection, generic expressions for the uplink (UL) spectral efficiency (SE) for both distributed and centralized schemes are derived. In order to further reduce the computational complexity (CC) of the original local partial MMSE (LP-MMSE) and partial MMSE (P-MMSE) detectors, two novel scalable low complexity MMSE detectors are proposed for distributed and centralized schemes respectively, which achieves very similar SE performance. Furthermore, for the distributed scheme a novel partial large-scale fading decoding (P-LSFD) weighting vector is introduced and its analytical SE performance is very similar to the performance of an equivalent unscalable LSFD vector. Finally, a scalable algorithm jointly consisting of AP cluster formation, pilot assignment, and power control is proposed, which outperforms the conventional random pilot assignment and user-group based pilot assignment policies and, contrary to an equal power transmit strategy, it guarantees quality of service (QoS) fairness for all accessing UEs.
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