303 research outputs found
Cell-Free Massive MIMO with Multi-Antenna Users over Weichselberger Rician Channels
We consider a cell-free massive multiple-input multiple-output (MIMO) system
with multi-antenna access points and user equipments (UEs) over Weichselberger
Rician fading channels with random phase-shifts. More specifically, we
investigate the uplink spectral efficiency (SE) for two pragmatic processing
schemes: 1) the fully centralized processing scheme with global minimum mean
square error (MMSE) or maximum ratio (MR) combining; 2) the large-scale fading
decoding (LSFD) scheme with local MMSE or MR combining. To improve the system
SE performance, we propose a practical uplink precoding scheme based on only
the eigenbasis of the UE-side correlation matrices. Moreover, we derive novel
closed-form SE expressions for characterizing the LSFD scheme with the MR
combining. Numerical results validate the accuracy of our derived expressions
and show that the proposed precoding scheme can significantly improve the SE
performance compared with the scenario without any precoding scheme.Comment: 14 pages, 5 figures, to appear in IEEE Transactions on Vehicular
Technolog
Hardware-Impaired Rician-Faded Cell-Free Massive MIMO Systems With Channel Aging
We study the impact of channel aging on the uplink of a cell-free (CF)
massive multiple-input multiple-output (mMIMO) system by considering i)
spatially-correlated Rician-faded channels; ii) hardware impairments at the
access points and user equipments (UEs); and iii) two-layer large-scale fading
decoding (LSFD). We first derive a closed-form spectral efficiency (SE)
expression for this system, and later propose two novel optimization techniques
to optimize the non-convex SE metric by exploiting the
minorization-maximization (MM) method. The first one requires a numerical
optimization solver, and has a high computation complexity. The second one with
closed-form transmit power updates, has a trivial computation complexity. We
numerically show that i) the two-layer LSFD scheme effectively mitigates the
interference due to channel aging for both low- and high-velocity UEs; and ii)
increasing the number of AP antennas does not mitigate the SE deterioration due
to channel aging. We numerically characterize the optimal pilot length required
to maximize the SE for various UE speeds. We also numerically show that the
proposed closed-form MM optimization yields the same SE as that of the first
technique, which requires numerical solver, and that too with a much reduced
time-complexity.Comment: This work has been submitted to the IEEE Transactions on
Communications for possible publication. Copyright may be transferred without
notice, after which this version may no longer be accessible, 32 pages, 14
figure
Two-Timescale Design for Reconfigurable Intelligent Surface-Aided Massive MIMO Systems with Imperfect CSI
This paper investigates the two-timescale transmission scheme for reconfigurable intelligent surface (RIS)-aided massive multiple-input multiple-output (MIMO) systems, where the beamforming at the base station (BS) is adapted to the rapidly-changing instantaneous channel state information (CSI), while the nearly-passive beamforming at the RIS is adapted to the slowly-changing statistical CSI. Specifically, we first consider a system model with spatially independent Rician fading channels, which leads to tractable expressions and offers analytical insights on the power scaling laws and on the impact of various system parameters. Then, we analyze a more general system model with spatially correlated Rician fading channels and consider the impact of electromagnetic interference (EMI) caused by any uncontrollable sources present in the considered environment. For both case studies, we apply the linear minimum mean square error (LMMSE) estimator to estimate the aggregated channel from the users to the BS, utilize the low-complexity maximal ratio combining (MRC) detector, and derive a closed-form expression for a lower bound of the achievable rate. Besides, an accelerated gradient ascent-based algorithm is proposed for solving the minimum user rate maximization problem. Numerical results show that, in the considered setup, the spatially independent model without EMI is sufficiently accurate when the inter-distance of the RIS elements is sufficiently large and the EMI is mild. In the presence of spatial correlation, we show that an RIS can better tailor the wireless environment. Furthermore, it is shown that deploying an RIS in a massive MIMO network brings significant gains when the RIS is deployed close to the cell-edge users. On the other hand, the gains obtained by the users distributed over a large area are shown to be modest
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