1,416 research outputs found
1-Bit Massive MIMO Downlink Based on Constructive Interference
In this paper, we focus on the multiuser massive multiple-input single-output
(MISO) downlink with low-cost 1-bit digital-to-analog converters (DACs) for PSK
modulation, and propose a low-complexity refinement process that is applicable
to any existing 1-bit precoding approaches based on the constructive
interference (CI) formulation. With the decomposition of the signals along the
detection thresholds, we first formulate a simple symbol-scaling method as the
performance metric. The low-complexity refinement approach is subsequently
introduced, where we aim to improve the introduced symbol-scaling performance
metric by modifying the transmit signal on one antenna at a time. Numerical
results validate the effectiveness of the proposed refinement method on
existing approaches for massive MIMO with 1-bit DACs, and the performance
improvements are most significant for the low-complexity quantized zero-forcing
(ZF) method.Comment: 5 pages, EUSIPCO 201
Large System Analysis of Power Normalization Techniques in Massive MIMO
Linear precoding has been widely studied in the context of Massive
multiple-input-multiple-output (MIMO) together with two common power
normalization techniques, namely, matrix normalization (MN) and vector
normalization (VN). Despite this, their effect on the performance of Massive
MIMO systems has not been thoroughly studied yet. The aim of this paper is to
fulfill this gap by using large system analysis. Considering a system model
that accounts for channel estimation, pilot contamination, arbitrary pathloss,
and per-user channel correlation, we compute tight approximations for the
signal-to-interference-plus-noise ratio and the rate of each user equipment in
the system while employing maximum ratio transmission (MRT), zero forcing (ZF),
and regularized ZF precoding under both MN and VN techniques. Such
approximations are used to analytically reveal how the choice of power
normalization affects the performance of MRT and ZF under uncorrelated fading
channels. It turns out that ZF with VN resembles a sum rate maximizer while it
provides a notion of fairness under MN. Numerical results are used to validate
the accuracy of the asymptotic analysis and to show that in Massive MIMO,
non-coherent interference and noise, rather than pilot contamination, are often
the major limiting factors of the considered precoding schemes.Comment: 12 pages, 3 figures, Accepted for publication in the IEEE
Transactions on Vehicular Technolog
Massive MU-MIMO-OFDM Downlink with One-Bit DACs and Linear Precoding
Massive multiuser (MU) multiple-input multiple- output (MIMO) is foreseen to
be a key technology in future wireless communication systems. In this paper, we
analyze the downlink performance of an orthogonal frequency division
multiplexing (OFDM)-based massive MU-MIMO system in which the base station (BS)
is equipped with 1-bit digital-to-analog converters (DACs). Using Bussgang's
theorem, we characterize the performance achievable with linear precoders (such
as maximal-ratio transmission and zero forcing) in terms of bit error rate
(BER). Our analysis accounts for the possibility of oversampling the
time-domain transmit signal before the DACs. We further develop a lower bound
on the information-theoretic sum-rate throughput achievable with Gaussian
inputs.
Our results suggest that the performance achievable with 1-bit DACs in a
massive MU-MIMO-OFDM downlink are satisfactory provided that the number of BS
antennas is sufficiently large
Massive MU-MIMO Downlink TDD Systems with Linear Precoding and Downlink Pilots
We consider a massive MU-MIMO downlink time-division duplex system where a
base station (BS) equipped with many antennas serves several single-antenna
users in the same time-frequency resource. We assume that the BS uses linear
precoding for the transmission. To reliably decode the signals transmitted from
the BS, each user should have an estimate of its channel. In this work, we
consider an efficient channel estimation scheme to acquire CSI at each user,
called beamforming training scheme. With the beamforming training scheme, the
BS precodes the pilot sequences and forwards to all users. Then, based on the
received pilots, each user uses minimum mean-square error channel estimation to
estimate the effective channel gains. The channel estimation overhead of this
scheme does not depend on the number of BS antennas, and is only proportional
to the number of users. We then derive a lower bound on the capacity for
maximum-ratio transmission and zero-forcing precoding techniques which enables
us to evaluate the spectral efficiency taking into account the spectral
efficiency loss associated with the transmission of the downlink pilots.
Comparing with previous work where each user uses only the statistical channel
properties to decode the transmitted signals, we see that the proposed
beamforming training scheme is preferable for moderate and low-mobility
environments.Comment: Allerton Conference on Communication, Control, and Computing,
Urbana-Champaign, Illinois, Oct. 201
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