15,998 research outputs found
Preliminary Results on 3D Channel Modeling: From Theory to Standardization
Three dimensional beamforming (3D) (also elevation beamforming) is now
gaining a growing interest among researchers in wireless communication. The
reason can be attributed to its potential to enable a variety of strategies
like sector or user specific elevation beamforming and cell-splitting. Since
these techniques cannot be directly supported by current LTE releases, the 3GPP
is now working on defining the required technical specifications. In
particular, a large effort is currently made to get accurate 3D channel models
that support the elevation dimension. This step is necessary as it will
evaluate the potential of 3D and FD(Full Dimensional) beamforming techniques to
benefit from the richness of real channels. This work aims at presenting the
on-going 3GPP study item "Study on 3D-channel model for Elevation Beamforming
and FD-MIMO studies for LTE", and positioning it with respect to previous
standardization works
A Novel Millimeter-Wave Channel Simulator and Applications for 5G Wireless Communications
This paper presents details and applications of a novel channel simulation
software named NYUSIM, which can be used to generate realistic temporal and
spatial channel responses to support realistic physical- and link-layer
simulations and design for fifth-generation (5G) cellular communications.
NYUSIM is built upon the statistical spatial channel model for broadband
millimeter-wave (mmWave) wireless communication systems developed by
researchers at New York University (NYU). The simulator is applicable for a
wide range of carrier frequencies (500 MHz to 100 GHz), radio frequency (RF)
bandwidths (0 to 800 MHz), antenna beamwidths (7 to 360 degrees for azimuth and
7 to 45 degrees for elevation), and operating scenarios (urban microcell, urban
macrocell, and rural macrocell), and also incorporates multiple-input
multiple-output (MIMO) antenna arrays at the transmitter and receiver. This
paper also provides examples to demonstrate how to use NYUSIM for analyzing
MIMO channel conditions and spectral efficiencies, which show that NYUSIM is an
alternative and more realistic channel model compared to the 3rd Generation
Partnership Project (3GPP) and other channel models for mmWave bands.Comment: 7 pages, 8 figures, in 2017 IEEE International Conference on
Communications (ICC), Paris, May 201
Electromagnetic Lens-focusing Antenna Enabled Massive MIMO: Performance Improvement and Cost Reduction
Massive multiple-input multiple-output (MIMO) techniques have been recently
advanced to tremendously improve the performance of wireless communication
networks. However, the use of very large antenna arrays at the base stations
(BSs) brings new issues, such as the significantly increased hardware and
signal processing costs. In order to reap the enormous gain of massive MIMO and
yet reduce its cost to an affordable level, this paper proposes a novel system
design by integrating an electromagnetic (EM) lens with the large antenna
array, termed the EM-lens enabled MIMO. The EM lens has the capability of
focusing the power of an incident wave to a small area of the antenna array,
while the location of the focal area varies with the angle of arrival (AoA) of
the wave. Therefore, in practical scenarios where the arriving signals from
geographically separated users have different AoAs, the EM-lens enabled system
provides two new benefits, namely energy focusing and spatial interference
rejection. By taking into account the effects of imperfect channel estimation
via pilot-assisted training, in this paper we analytically show that the
average received signal-to-noise ratio (SNR) in both the single-user and
multiuser uplink transmissions can be strictly improved by the EM-lens enabled
system. Furthermore, we demonstrate that the proposed design makes it possible
to considerably reduce the hardware and signal processing costs with only
slight degradations in performance. To this end, two complexity/cost reduction
schemes are proposed, which are small-MIMO processing with parallel receiver
filtering applied over subgroups of antennas to reduce the computational
complexity, and channel covariance based antenna selection to reduce the
required number of radio frequency (RF) chains. Numerical results are provided
to corroborate our analysis.Comment: 30 pages, 9 figure
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