179 research outputs found
A Coordinated Approach to Channel Estimation in Large-scale Multiple-antenna Systems
This paper addresses the problem of channel estimation in multi-cell
interference-limited cellular networks. We consider systems employing multiple
antennas and are interested in both the finite and large-scale antenna number
regimes (so-called "massive MIMO"). Such systems deal with the multi-cell
interference by way of per-cell beamforming applied at each base station.
Channel estimation in such networks, which is known to be hampered by the pilot
contamination effect, constitute a major bottleneck for overall performance. We
present a novel approach which tackles this problem by enabling a low-rate
coordination between cells during the channel estimation phase itself. The
coordination makes use of the additional second-order statistical information
about the user channels, which are shown to offer a powerful way of
discriminating across interfering users with even strongly correlated pilot
sequences. Importantly, we demonstrate analytically that in the
large-number-of-antennas regime, the pilot contamination effect is made to
vanish completely under certain conditions on the channel covariance. Gains
over the conventional channel estimation framework are confirmed by our
simulations for even small antenna array sizes.Comment: 10 pages, 6 figures, to appear in IEEE Journal on Selected Areas in
Communication
Jamming Resistant Receivers for Massive MIMO
We design jamming resistant receivers to enhance the robustness of a massive
MIMO uplink channel against jamming. In the pilot phase, we estimate not only
the desired channel, but also the jamming channel by exploiting purposely
unused pilot sequences. The jamming channel estimate is used to construct the
linear receive filter to reduce impact that jamming has on the achievable
rates. The performance of the proposed scheme is analytically and numerically
evaluated. These results show that the proposed scheme greatly improves the
rates, as compared to conventional receivers. Moreover, the proposed schemes
still work well with stronger jamming power.Comment: Accepted in the 42nd IEEE Int. Conf. Acoust., Speech, and Signal
Process. (ICASSP2017
Fractional Pilot Reuse in Massive MIMO Systems
Pilot contamination is known to be one of the main impairments for massive
MIMO multi-cell communications. Inspired by the concept of fractional frequency
reuse and by recent contributions on pilot reutilization among non-adjacent
cells, we propose a new pilot allocation scheme to mitigate this effect. The
key idea is to allow users in neighboring cells that are closest to their base
stations to reuse the same pilot sequences. Focusing on the uplink, we obtain
expressions for the overall spectral efficiency per cell for different linear
combining techniques at the base station and use them to obtain both the
optimal pilot reuse parameters and the optimal number of scheduled users.
Numerical results show a remarkable improvement in terms of spectral efficiency
with respect to the existing techniques.Comment: Paper presented at the IEEE ICC 2015 Workshop on 5G & Beyond -
Enabling Technologies and Application
Pilot Decontamination in CMT-based Massive MIMO Networks
Pilot contamination problem in massive MIMO networks operating in
time-division duplex (TDD) mode can limit their expected capacity to a great
extent. This paper addresses this problem in cosine modulated multitone (CMT)
based massive MIMO networks; taking advantage of their so-called blind
equalization property. We extend and apply the blind equalization technique
from single antenna case to multi-cellular massive MIMO systems and show that
it can remove the channel estimation errors (due to pilot contamination effect)
without any need for cooperation between different cells or transmission of
additional training information. Our numerical results advocate the efficacy of
the proposed blind technique in improving the channel estimation accuracy and
removal of the residual channel estimation errors caused by the users of the
other cells.Comment: Accepted in ISWCS 201
Distributed Massive MIMO in Cellular Networks: Impact of Imperfect Hardware and Number of Oscillators
Distributed massive multiple-input multiple-output (MIMO) combines the array
gain of coherent MIMO processing with the proximity gains of distributed
antenna setups. In this paper, we analyze how transceiver hardware impairments
affect the downlink with maximum ratio transmission. We derive closed-form
spectral efficiencies expressions and study their asymptotic behavior as the
number of the antennas increases. We prove a scaling law on the hardware
quality, which reveals that massive MIMO is resilient to additive distortions,
while multiplicative phase noise is a limiting factor. It is also better to
have separate oscillators at each antenna than one per BS.Comment: First published in the Proceedings of the 23rd European Signal
Processing Conference (EUSIPCO-2015) in 2015, published by EURASIP. 5 pages,
3, figure
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