1,707 research outputs found
Machine Learning Inspired Energy-Efficient Hybrid Precoding for MmWave Massive MIMO Systems
Hybrid precoding is a promising technique for mmWave massive MIMO systems, as
it can considerably reduce the number of required radio-frequency (RF) chains
without obvious performance loss. However, most of the existing hybrid
precoding schemes require a complicated phase shifter network, which still
involves high energy consumption. In this paper, we propose an energy-efficient
hybrid precoding architecture, where the analog part is realized by a small
number of switches and inverters instead of a large number of high-resolution
phase shifters. Our analysis proves that the performance gap between the
proposed hybrid precoding architecture and the traditional one is small and
keeps constant when the number of antennas goes to infinity. Then, inspired by
the cross-entropy (CE) optimization developed in machine learning, we propose
an adaptive CE (ACE)-based hybrid precoding scheme for this new architecture.
It aims to adaptively update the probability distributions of the elements in
hybrid precoder by minimizing the CE, which can generate a solution close to
the optimal one with a sufficiently high probability. Simulation results verify
that our scheme can achieve the near-optimal sum-rate performance and much
higher energy efficiency than traditional schemes.Comment: This paper has been accepted by IEEE ICC 2017. The simulation codes
are provided to reproduce the results in this paper at:
http://oa.ee.tsinghua.edu.cn/dailinglong/publications/publications.htm
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
Codebook Based Hybrid Precoding for Millimeter Wave Multiuser Systems
In millimeter wave (mmWave) systems, antenna architecture limitations make it
difficult to apply conventional fully digital precoding techniques but call for
low cost analog radio-frequency (RF) and digital baseband hybrid precoding
methods. This paper investigates joint RF-baseband hybrid precoding for the
downlink of multiuser multi-antenna mmWave systems with a limited number of RF
chains. Two performance measures, maximizing the spectral efficiency and the
energy efficiency of the system, are considered. We propose a codebook based RF
precoding design and obtain the channel state information via a beam sweep
procedure. Via the codebook based design, the original system is transformed
into a virtual multiuser downlink system with the RF chain constraint.
Consequently, we are able to simplify the complicated hybrid precoding
optimization problems to joint codeword selection and precoder design (JWSPD)
problems. Then, we propose efficient methods to address the JWSPD problems and
jointly optimize the RF and baseband precoders under the two performance
measures. Finally, extensive numerical results are provided to validate the
effectiveness of the proposed hybrid precoders.Comment: 35 pages, 9 figures, to appear in Trans. on Signal Process, 201
Joint Hybrid Precoder and Combiner Design for mmWave Spatial Multiplexing Transmission
Millimeter-wave (mmWave) communications have been considered as a key
technology for future 5G wireless networks because of the orders-of-magnitude
wider bandwidth than current cellular bands. In this paper, we consider the
problem of codebook-based joint analog-digital hybrid precoder and combiner
design for spatial multiplexing transmission in a mmWave multiple-input
multiple-output (MIMO) system. We propose to jointly select analog precoder and
combiner pair for each data stream successively aiming at maximizing the
channel gain while suppressing the interference between different data streams.
After all analog precoder/combiner pairs have been determined, we can obtain
the effective baseband channel. Then, the digital precoder and combiner are
computed based on the obtained effective baseband channel to further mitigate
the interference and maximize the sum-rate. Simulation results demonstrate that
our proposed algorithm exhibits prominent advantages in combating interference
between different data streams and offer satisfactory performance improvement
compared to the existing codebook-based hybrid beamforming schemes
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