3,864 research outputs found
Hybrid Precoder and Combiner Design with Low Resolution Phase Shifters in mmWave MIMO Systems
Millimeter wave (mmWave) communications have been considered as a key
technology for next generation cellular systems and Wi-Fi networks because of
its advances in providing orders-of-magnitude wider bandwidth than current
wireless networks. Economical and energy efficient analog/digial hybrid
precoding and combining transceivers have been often proposed for mmWave
massive multiple-input multiple-output (MIMO) systems to overcome the severe
propagation loss of mmWave channels. One major shortcoming of existing
solutions lies in the assumption of infinite or high-resolution phase shifters
(PSs) to realize the analog beamformers. However, low-resolution PSs are
typically adopted in practice to reduce the hardware cost and power
consumption. Motivated by this fact, in this paper, we investigate the
practical design of hybrid precoders and combiners with low-resolution PSs in
mmWave MIMO systems. In particular, we propose an iterative algorithm which
successively designs the low-resolution analog precoder and combiner pair for
each data stream, aiming at conditionally maximizing the spectral efficiency.
Then, the digital precoder and combiner are computed based on the obtained
effective baseband channel to further enhance the spectral efficiency. In an
effort to achieve an even more hardware-efficient large antenna array, we also
investigate the design of hybrid beamformers with one-bit resolution (binary)
PSs, and present a novel binary analog precoder and combiner optimization
algorithm with quadratic complexity in the number of antennas. The proposed
low-resolution hybrid beamforming design is further extended to multiuser MIMO
communication systems. Simulation results demonstrate the performance
advantages of the proposed algorithms compared to existing low-resolution
hybrid beamforming designs, particularly for the one-bit resolution PS
scenario
Scalable and Energy-Efficient Millimeter Massive MIMO Architectures: Reflect-Array and Transmit-Array Antennas
Hybrid analog-digital architectures are considered as promising candidates
for implementing millimeter wave (mmWave) massive multiple-input
multiple-output (MIMO) systems since they enable a considerable reduction of
the required number of costly radio frequency (RF) chains by moving some of the
signal processing operations into the analog domain. However, the analog feed
network, comprising RF dividers, combiners, phase shifters, and line
connections, of hybrid MIMO architectures is not scalable due to its
prohibitively high power consumption for large numbers of transmit antennas.
Motivated by this limitation, in this paper, we study novel massive MIMO
architectures, namely reflect-array (RA) and transmit-array (TA) antennas. We
show that the precoders for RA and TA antennas have to meet different
constraints compared to those for conventional MIMO architectures. Taking these
constraints into account and exploiting the sparsity of mmWave channels, we
design an efficient precoder for RA and TA antennas based on the orthogonal
matching pursuit algorithm. Furthermore, in order to fairly compare the
performance of RA and TA antennas with conventional fully-digital and hybrid
MIMO architectures, we develop a unified power consumption model. Our
simulation results show that unlike conventional MIMO architectures, RA and TA
antennas are highly energy efficient and fully scalable in terms of the number
of transmit antennas.Comment: submitted to IEEE ICC 201
On Low-Resolution ADCs in Practical 5G Millimeter-Wave Massive MIMO Systems
Nowadays, millimeter-wave (mmWave) massive multiple-input multiple-output
(MIMO) systems is a favorable candidate for the fifth generation (5G) cellular
systems. However, a key challenge is the high power consumption imposed by its
numerous radio frequency (RF) chains, which may be mitigated by opting for
low-resolution analog-to-digital converters (ADCs), whilst tolerating a
moderate performance loss. In this article, we discuss several important issues
based on the most recent research on mmWave massive MIMO systems relying on
low-resolution ADCs. We discuss the key transceiver design challenges including
channel estimation, signal detector, channel information feedback and transmit
precoding. Furthermore, we introduce a mixed-ADC architecture as an alternative
technique of improving the overall system performance. Finally, the associated
challenges and potential implementations of the practical 5G mmWave massive
MIMO system {with ADC quantizers} are discussed.Comment: to appear in IEEE Communications Magazin
Channel Estimation for mmWave Massive MIMO Based Access and Backhaul in Ultra-Dense Network
Millimeter-wave (mmWave) massive MIMO used for access and backhaul in
ultra-dense network (UDN) has been considered as the promising 5G technique. We
consider such an heterogeneous network (HetNet) that ultra-dense small base
stations (BSs) exploit mmWave massive MIMO for access and backhaul, while
macrocell BS provides the control service with low frequency band. However, the
channel estimation for mmWave massive MIMO can be challenging, since the pilot
overhead to acquire the channels associated with a large number of antennas in
mmWave massive MIMO can be prohibitively high. This paper proposes a structured
compressive sensing (SCS)-based channel estimation scheme, where the angular
sparsity of mmWave channels is exploited to reduce the required pilot overhead.
Specifically, since the path loss for non-line-of-sight paths is much larger
than that for line-of-sight paths, the mmWave massive channels in the angular
domain appear the obvious sparsity. By exploiting such sparsity, the required
pilot overhead only depends on the small number of dominated multipath.
Moreover, the sparsity within the system bandwidth is almost unchanged, which
can be exploited for the further improved performance. Simulation results
demonstrate that the proposed scheme outperforms its counterpart, and it can
approach the performance bound.Comment: 6 pages, 5 figures. Millimeter-wave (mmWave), mmWave massive MIMO,
compressive sensing (CS), hybrid precoding, channel estimation, access,
backhaul, ultra-dense network (UDN), heterogeneous network (HetNet). arXiv
admin note: substantial text overlap with arXiv:1604.03695, IEEE
International Conference on Communications (ICC'16), May 2016, Kuala Lumpur,
Malaysi
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