569 research outputs found
Quantized Constant Envelope Precoding with PSK and QAM Signaling
Coarsely quantized massive Multiple-Input Multiple-Output (MIMO) systems are
gaining more interest due to their power efficiency. We present a new precoding
technique to mitigate the Multi-User Interference (MUI) and the quantization
distortions in a downlink Multi-User (MU) MIMO system with coarsely Quantized
Constant Envelope (QCE) signals at the transmitter. The transmit signal vector
is optimized for every desired received vector taking into account the QCE
constraint. The optimization is based on maximizing the safety margin to the
decision thresholds of the receiver constellation modulation. Simulation
results show a significant gain in terms of the uncoded Bit Error Ratio (BER)
compared to the existing linear precoding techniques
Waveforms for the Massive MIMO Downlink: Amplifier Efficiency, Distortion and Performance
In massive MIMO, most precoders result in downlink signals that suffer from
high PAR, independently of modulation order and whether single-carrier or OFDM
transmission is used. The high PAR lowers the power efficiency of the base
station amplifiers. To increase power efficiency, low-PAR precoders have been
proposed. In this article, we compare different transmission schemes for
massive MIMO in terms of the power consumed by the amplifiers. It is found that
(i) OFDM and single-carrier transmission have the same performance over a
hardened massive MIMO channel and (ii) when the higher amplifier power
efficiency of low-PAR precoding is taken into account, conventional and low-PAR
precoders lead to approximately the same power consumption. Since downlink
signals with low PAR allow for simpler and cheaper hardware, than signals with
high PAR, therefore, the results suggest that low-PAR precoding with either
single-carrier or OFDM transmission should be used in a massive MIMO base
station
1-Bit Massive MIMO Transmission: Embracing Interference with Symbol-Level Precoding
The deployment of large-scale antenna arrays for cellular base stations
(BSs), termed as `Massive MIMO', has been a key enabler for meeting the
ever-increasing capacity requirement for 5G communication systems and beyond.
Despite their promising performance, fully-digital massive MIMO systems require
a vast amount of hardware components including radio frequency chains, power
amplifiers, digital-to-analog converters (DACs), etc., resulting in a huge
increase in terms of the total power consumption and hardware costs for
cellular BSs. Towards both spectrally-efficient and energy-efficient massive
MIMO deployment, a number of hardware limited architectures have been proposed,
including hybrid analog-digital structures, constant-envelope transmission, and
use of low-resolution DACs. In this paper, we overview the recent interest in
improving the error-rate performance of massive MIMO systems deployed with
1-bit DACs through precoding at the symbol level. This line of research goes
beyond traditional interference suppression or cancellation techniques by
managing interference on a symbol-by-symbol basis. This provides unique
opportunities for interference-aware precoding tailored for practical massive
MIMO systems. Firstly, we characterize constructive interference (CI) and
elaborate on how CI can benefit the 1-bit signal design by exploiting the
traditionally undesired multi-user interference as well as the interference
from imperfect hardware components. Subsequently, we overview several solutions
for 1-bit signal design to illustrate the gains achievable by exploiting CI.
Finally, we identify some challenges and future research directions for 1-bit
massive MIMO systems that are yet to be explored.Comment: This work has been submitted to the IEEE for possible publication.
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Massive MIMO Downlink 1-Bit Precoding with Linear Programming for PSK Signaling
Quantized massive multiple-input-multiple-output (MIMO) systems are gaining
more interest due to their power efficiency. We present a new precoding
technique to mitigate the multi-user interference and the quantization
distortions in a downlink multi-user (MU) multiple-input-single-output (MISO)
system with 1-bit quantization at the transmitter. This work is restricted to
PSK modulation schemes. The transmit signal vector is optimized for every
desired received vector taking into account the 1-bit quantization. The
optimization is based on maximizing the safety margin to the decision
thresholds of the PSK modulation. Simulation results show a significant gain in
terms of the uncoded bit-error-ratio (BER) compared to the existing linear
precoding techniques.Comment: Submitted to SPAWC 201
Massive MIMO for Next Generation Wireless Systems
Multi-user Multiple-Input Multiple-Output (MIMO) offers big advantages over
conventional point-to-point MIMO: it works with cheap single-antenna terminals,
a rich scattering environment is not required, and resource allocation is
simplified because every active terminal utilizes all of the time-frequency
bins. However, multi-user MIMO, as originally envisioned with roughly equal
numbers of service-antennas and terminals and frequency division duplex
operation, is not a scalable technology. Massive MIMO (also known as
"Large-Scale Antenna Systems", "Very Large MIMO", "Hyper MIMO", "Full-Dimension
MIMO" & "ARGOS") makes a clean break with current practice through the use of a
large excess of service-antennas over active terminals and time division duplex
operation. Extra antennas help by focusing energy into ever-smaller regions of
space to bring huge improvements in throughput and radiated energy efficiency.
Other benefits of massive MIMO include the extensive use of inexpensive
low-power components, reduced latency, simplification of the media access
control (MAC) layer, and robustness to intentional jamming. The anticipated
throughput depend on the propagation environment providing asymptotically
orthogonal channels to the terminals, but so far experiments have not disclosed
any limitations in this regard. While massive MIMO renders many traditional
research problems irrelevant, it uncovers entirely new problems that urgently
need attention: the challenge of making many low-cost low-precision components
that work effectively together, acquisition and synchronization for
newly-joined terminals, the exploitation of extra degrees of freedom provided
by the excess of service-antennas, reducing internal power consumption to
achieve total energy efficiency reductions, and finding new deployment
scenarios. This paper presents an overview of the massive MIMO concept and
contemporary research.Comment: Final manuscript, to appear in IEEE Communications Magazin
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