1,115 research outputs found
Massive MIMO in Real Propagation Environments: Do All Antennas Contribute Equally?
Massive MIMO can greatly increase both spectral and transmit-energy
efficiency. This is achieved by allowing the number of antennas and RF chains
to grow very large. However, the challenges include high system complexity and
hardware energy consumption. Here we investigate the possibilities to reduce
the required number of RF chains, by performing antenna selection. While this
approach is not a very effective strategy for theoretical independent Rayleigh
fading channels, a substantial reduction in the number of RF chains can be
achieved for real massive MIMO channels, without significant performance loss.
We evaluate antenna selection performance on measured channels at 2.6 GHz,
using a linear and a cylindrical array, both having 128 elements. Sum-rate
maximization is used as the criterion for antenna selection. A selection scheme
based on convex optimization is nearly optimal and used as a benchmark. The
achieved sum-rate is compared with that of a very simple scheme that selects
the antennas with the highest received power. The power-based scheme gives
performance close to the convex optimization scheme, for the measured channels.
This observation indicates a potential for significant reductions of massive
MIMO implementation complexity, by reducing the number of RF chains and
performing antenna selection using simple algorithms.Comment: Submitted to IEEE Transactions on Communication
A Novel Antenna Selection Scheme for Spatially Correlated Massive MIMO Uplinks with Imperfect Channel Estimation
We propose a new antenna selection scheme for a massive MIMO system with a
single user terminal and a base station with a large number of antennas. We
consider a practical scenario where there is a realistic correlation among the
antennas and imperfect channel estimation at the receiver side. The proposed
scheme exploits the sparsity of the channel matrix for the effective selection
of a limited number of antennas. To this end, we compute a sparse channel
matrix by minimising the mean squared error. This optimisation problem is then
solved by the well-known orthogonal matching pursuit algorithm. Widely used
models for spatial correlation among the antennas and channel estimation errors
are considered in this work. Simulation results demonstrate that when the
impacts of spatial correlation and imperfect channel estimation introduced, the
proposed scheme in the paper can significantly reduce complexity of the
receiver, without degrading the system performance compared to the maximum
ratio combining.Comment: in Proc. IEEE 81st Vehicular Technology Conference (VTC), May 2015, 6
pages, 5 figure
Massive MIMO Performance - TDD Versus FDD: What Do Measurements Say?
Downlink beamforming in Massive MIMO either relies on uplink pilot
measurements - exploiting reciprocity and TDD operation, or on the use of a
predetermined grid of beams with user equipments reporting their preferred
beams, mostly in FDD operation. Massive MIMO in its originally conceived form
uses the first strategy, with uplink pilots, whereas there is currently
significant commercial interest in the second, grid-of-beams. It has been
analytically shown that in isotropic scattering (independent Rayleigh fading)
the first approach outperforms the second. Nevertheless there remains
controversy regarding their relative performance in practice. In this
contribution, the performances of these two strategies are compared using
measured channel data at 2.6 GHz.Comment: Submitted to IEEE Transactions on Wireless Communications,
31/Mar/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
Reduced Switching Connectivity for Large Scale Antenna Selection
In this paper, we explore reduced-connectivity radio frequency (RF) switching
networks for reducing the analog hardware complexity and switching power losses
in antenna selection (AS) systems. In particular, we analyze different hardware
architectures for implementing the RF switching matrices required in AS designs
with a reduced number of RF chains. We explicitly show that fully-flexible
switching matrices, which facilitate the selection of any possible subset of
antennas and attain the maximum theoretical sum rates of AS, present numerous
drawbacks such as the introduction of significant insertion losses,
particularly pronounced in massive multiple-input multiple-output (MIMO)
systems. Since these disadvantages make fully-flexible switching suboptimal in
the energy efficiency sense, we further consider partially-connected switching
networks as an alternative switching architecture with reduced hardware
complexity, which we characterize in this work. In this context, we also
analyze the impact of reduced switching connectivity on the analog hardware and
digital signal processing of AS schemes that rely on channel power information.
Overall, the analytical and simulation results shown in this paper demonstrate
that partially-connected switching maximizes the energy efficiency of massive
MIMO systems for a reduced number of RF chains, while fully-flexible switching
offers sub-optimal energy efficiency benefits due to its significant switching
power losses.Comment: 14 pages, 11 figure
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