1,356 research outputs found
Massive MIMO 1-Bit DAC Transmission: A Low-Complexity Symbol Scaling Approach
We study multi-user massive multiple-input single-output (MISO) systems and
focus on downlink transmission, where the base station (BS) employs a large
antenna array with low-cost 1-bit digital-to-analog converters (DACs). The
direct combination of existing beamforming schemes with 1-bit DACs is shown to
lead to an error floor at medium-to-high SNR regime, due to the coarse
quantization of the DACs with limited precision. In this paper, based on the
constructive interference we consider both a quantized linear beamforming
scheme where we analytically obtain the optimal beamforming matrix, and a
non-linear mapping scheme where we directly design the transmit signal vector.
Due to the 1-bit quantization, the formulated optimization for the non-linear
mapping scheme is shown to be non-convex. To solve this problem, the non-convex
constraints of the 1-bit DACs are firstly relaxed, followed by an element-wise
normalization to satisfy the 1-bit DAC transmission. We further propose a
low-complexity symbol scaling scheme that consists of three stages, in which
the quantized transmit signal on each antenna element is selected sequentially.
Numerical results show that the proposed symbol scaling scheme achieves a
comparable performance to the optimization-based non-linear mapping approach,
while its corresponding complexity is negligible compared to that of the
non-linear scheme.Comment: 15 page
Advanced Quantizer Designs for FDD-Based FD-MIMO Systems Using Uniform Planar Arrays
Massive multiple-input multiple-output (MIMO) systems, which utilize a large
number of antennas at the base station, are expected to enhance network
throughput by enabling improved multiuser MIMO techniques. To deploy many
antennas in reasonable form factors, base stations are expected to employ
antenna arrays in both horizontal and vertical dimensions, which is known as
full-dimension (FD) MIMO. The most popular two-dimensional array is the uniform
planar array (UPA), where antennas are placed in a grid pattern. To exploit the
full benefit of massive MIMO in frequency division duplexing (FDD), the
downlink channel state information (CSI) should be estimated, quantized, and
fed back from the receiver to the transmitter. However, it is difficult to
accurately quantize the channel in a computationally efficient manner due to
the high dimensionality of the massive MIMO channel. In this paper, we develop
both narrowband and wideband CSI quantizers for FD-MIMO taking the properties
of realistic channels and the UPA into consideration. To improve quantization
quality, we focus on not only quantizing dominant radio paths in the channel,
but also combining the quantized beams. We also develop a hierarchical beam
search approach, which scans both vertical and horizontal domains jointly with
moderate computational complexity. Numerical simulations verify that the
performance of the proposed quantizers is better than that of previous CSI
quantization techniques.Comment: 15 pages, 6 figure
Energy efficiency of mmWave massive MIMO precoding with low-resolution DACs
With the congestion of the sub-6 GHz spectrum, the interest in massive
multiple-input multiple-output (MIMO) systems operating on millimeter wave
spectrum grows. In order to reduce the power consumption of such massive MIMO
systems, hybrid analog/digital transceivers and application of low-resolution
digital-to-analog/analog-to-digital converters have been recently proposed. In
this work, we investigate the energy efficiency of quantized hybrid
transmitters equipped with a fully/partially-connected phase-shifting network
composed of active/passive phase-shifters and compare it to that of quantized
digital precoders. We introduce a quantized single-user MIMO system model based
on an additive quantization noise approximation considering realistic power
consumption and loss models to evaluate the spectral and energy efficiencies of
the transmit precoding methods. Simulation results show that
partially-connected hybrid precoders can be more energy-efficient compared to
digital precoders, while fully-connected hybrid precoders exhibit poor energy
efficiency in general. Also, the topology of phase-shifting components offers
an energy-spectral efficiency trade-off: active phase-shifters provide higher
data rates, while passive phase-shifters maintain better energy efficiency.Comment: Published in IEEE Journal of Selected Topics in Signal Processin
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