486 research outputs found
Achievable Rates of Multi-User Millimeter Wave Systems with Hybrid Precoding
Millimeter wave (mmWave) systems will likely employ large antenna arrays at
both the transmitters and receivers. A natural application of antenna arrays is
simultaneous transmission to multiple users, which requires multi-user
precoding at the transmitter. Hardware constraints, however, make it difficult
to apply conventional lower frequency MIMO precoding techniques at mmWave. This
paper proposes and analyzes a low complexity hybrid analog/digital beamforming
algorithm for downlink multi-user mmWave systems. Hybrid precoding involves a
combination of analog and digital processing that is motivated by the
requirement to reduce the power consumption of the complete radio frequency and
mixed signal hardware. The proposed algorithm configures hybrid precoders at
the transmitter and analog combiners at multiple receivers with a small
training and feedback overhead. For this algorithm, we derive a lower bound on
the achievable rate for the case of single-path channels, show its asymptotic
optimality at large numbers of antennas, and make useful insights for more
general cases. Simulation results show that the proposed algorithm offers
higher sum rates compared with analog-only beamforming, and approaches the
performance of the unconstrained digital precoding solutions.Comment: to be presented in IEEE ICC 2015 - Workshop on 5G & Beyond - Enabling
Technologies and Application
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
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
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