884 research outputs found
Asymptotic analysis of downlink MIMO systems over Rician fading channels
In this work, we focus on the ergodic sum rate in the downlink of a
single-cell large-scale multi-user MIMO system in which the base station
employs N antennas to communicate with single-antenna user equipments. A
regularized zero-forcing (RZF) scheme is used for precoding under the
assumption that each link forms a spatially correlated MIMO Rician fading
channel. The analysis is conducted assuming and grow large with a non
trivial ratio and perfect channel state information is available at the base
station. Recent results from random matrix theory and large system analysis are
used to compute an asymptotic expression of the signal-to-interference-
plus-noise ratio as a function of the system parameters, the spatial
correlation matrix and the Rician factor. Numerical results are used to
evaluate the performance gap in the finite system regime under different
operating conditions.Comment: 5 pages, 2 figures. Published at the 41st IEEE International
Conference on Acoustics, Speech and Signal Processing (ICASSP 2016),
Shanghai, 20-25 March 201
Asymptotic Analysis of Multicell Massive MIMO over Rician Fading Channels
This work considers the downlink of a multicell massive MIMO system in which
base stations (BSs) of antennas each communicate with
single-antenna user equipments randomly positioned in the coverage area. Within
this setting, we are interested in evaluating the sum rate of the system when
MRT and RZF are employed under the assumption that each intracell link forms a
MIMO Rician fading channel. The analysis is conducted assuming that and
grow large with a non-trivial ratio under the assumption that the data
transmission in each cell is affected by channel estimation errors, pilot
contamination, and an arbitrary large scale attenuation. Numerical results are
used to validate the asymptotic analysis in the finite system regime and to
evaluate the network performance under different settings. The asymptotic
results are also instrumental to get insights into the interplay among system
parameters.Comment: 7 pages, 2 figures, submitted to GLOBECOM16, Washington, DC USA.
arXiv admin note: text overlap with arXiv:1601.0702
Hardware Impairments in Large-scale MISO Systems: Energy Efficiency, Estimation, and Capacity Limits
The use of large-scale antenna arrays has the potential to bring substantial
improvements in energy efficiency and/or spectral efficiency to future wireless
systems, due to the greatly improved spatial beamforming resolution. Recent
asymptotic results show that by increasing the number of antennas one can
achieve a large array gain and at the same time naturally decorrelate the user
channels; thus, the available energy can be focused very accurately at the
intended destinations without causing much inter-user interference. Since these
results rely on asymptotics, it is important to investigate whether the
conventional system models are still reasonable in the asymptotic regimes. This
paper analyzes the fundamental limits of large-scale multiple-input
single-output (MISO) communication systems using a generalized system model
that accounts for transceiver hardware impairments. As opposed to the case of
ideal hardware, we show that these practical impairments create finite ceilings
on the estimation accuracy and capacity of large-scale MISO systems.
Surprisingly, the performance is only limited by the hardware at the
single-antenna user terminal, while the impact of impairments at the
large-scale array vanishes asymptotically. Furthermore, we show that an
arbitrarily high energy efficiency can be achieved by reducing the power while
increasing the number of antennas.Comment: Published at International Conference on Digital Signal Processing
(DSP 2013), 6 pages, 5 figure
Multiuser Precoding and Channel Estimation for Hybrid Millimeter Wave MIMO Systems
In this paper, we develop a low-complexity channel estimation for hybrid
millimeter wave (mmWave) systems, where the number of radio frequency (RF)
chains is much less than the number of antennas equipped at each transceiver.
The proposed channel estimation algorithm aims to estimate the strongest
angle-of-arrivals (AoAs) at both the base station (BS) and the users. Then all
the users transmit orthogonal pilot symbols to the BS via these estimated
strongest AoAs to facilitate the channel estimation. The algorithm does not
require any explicit channel state information (CSI) feedback from the users
and the associated signalling overhead of the algorithm is only proportional to
the number of users, which is significantly less compared to various existing
schemes. Besides, the proposed algorithm is applicable to both non-sparse and
sparse mmWave channel environments. Based on the estimated CSI, zero-forcing
(ZF) precoding is adopted for multiuser downlink transmission. In addition, we
derive a tight achievable rate upper bound of the system. Our analytical and
simulation results show that the proposed scheme offer a considerable
achievable rate gain compared to fully digital systems, where the number of RF
chains equipped at each transceiver is equal to the number of antennas.
Furthermore, the achievable rate performance gap between the considered hybrid
mmWave systems and the fully digital system is characterized, which provides
useful system design insights.Comment: 6 pages, accepted for presentation, ICC 201
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