1,017 research outputs found
Massive MIMO performance evaluation based on measured propagation data
Massive MIMO, also known as very-large MIMO or large-scale antenna systems,
is a new technique that potentially can offer large network capacities in
multi-user scenarios. With a massive MIMO system, we consider the case where a
base station equipped with a large number of antenna elements simultaneously
serves multiple single-antenna users in the same time-frequency resource. So
far, investigations are mostly based on theoretical channels with independent
and identically distributed (i.i.d.) complex Gaussian coefficients, i.e.,
i.i.d. Rayleigh channels. Here, we investigate how massive MIMO performs in
channels measured in real propagation environments. Channel measurements were
performed at 2.6 GHz using a virtual uniform linear array (ULA) which has a
physically large aperture, and a practical uniform cylindrical array (UCA)
which is more compact in size, both having 128 antenna ports. Based on
measurement data, we illustrate channel behavior of massive MIMO in three
representative propagation conditions, and evaluate the corresponding
performance. The investigation shows that the measured channels, for both array
types, allow us to achieve performance close to that in i.i.d. Rayleigh
channels. It is concluded that in real propagation environments we have
characteristics that can allow for efficient use of massive MIMO, i.e., the
theoretical advantages of this new technology can also be harvested in real
channels.Comment: IEEE Transactions on Wireless Communications, 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
Massive MIMO has Unlimited Capacity
The capacity of cellular networks can be improved by the unprecedented array
gain and spatial multiplexing offered by Massive MIMO. Since its inception, the
coherent interference caused by pilot contamination has been believed to create
a finite capacity limit, as the number of antennas goes to infinity. In this
paper, we prove that this is incorrect and an artifact from using simplistic
channel models and suboptimal precoding/combining schemes. We show that with
multicell MMSE precoding/combining and a tiny amount of spatial channel
correlation or large-scale fading variations over the array, the capacity
increases without bound as the number of antennas increases, even under pilot
contamination. More precisely, the result holds when the channel covariance
matrices of the contaminating users are asymptotically linearly independent,
which is generally the case. If also the diagonals of the covariance matrices
are linearly independent, it is sufficient to know these diagonals (and not the
full covariance matrices) to achieve an unlimited asymptotic capacity.Comment: To appear in IEEE Transactions on Wireless Communications, 17 pages,
7 figure
Massive MIMO is a Reality -- What is Next? Five Promising Research Directions for Antenna Arrays
Massive MIMO (multiple-input multiple-output) is no longer a "wild" or
"promising" concept for future cellular networks - in 2018 it became a reality.
Base stations (BSs) with 64 fully digital transceiver chains were commercially
deployed in several countries, the key ingredients of Massive MIMO have made it
into the 5G standard, the signal processing methods required to achieve
unprecedented spectral efficiency have been developed, and the limitation due
to pilot contamination has been resolved. Even the development of fully digital
Massive MIMO arrays for mmWave frequencies - once viewed prohibitively
complicated and costly - is well underway. In a few years, Massive MIMO with
fully digital transceivers will be a mainstream feature at both sub-6 GHz and
mmWave frequencies. In this paper, we explain how the first chapter of the
Massive MIMO research saga has come to an end, while the story has just begun.
The coming wide-scale deployment of BSs with massive antenna arrays opens the
door to a brand new world where spatial processing capabilities are
omnipresent. In addition to mobile broadband services, the antennas can be used
for other communication applications, such as low-power machine-type or
ultra-reliable communications, as well as non-communication applications such
as radar, sensing and positioning. We outline five new Massive MIMO related
research directions: Extremely large aperture arrays, Holographic Massive MIMO,
Six-dimensional positioning, Large-scale MIMO radar, and Intelligent Massive
MIMO.Comment: 20 pages, 9 figures, submitted to Digital Signal Processin
On the energy efficiency-spectral efficiency trade-off of distributed MIMO systems
In this paper, the trade-off between energy efficiency (EE) and spectral efficiency (SE) is analyzed for both the uplink and downlink of the distributed multiple-input multiple-output (DMIMO) system over the Rayleigh fading channel while considering different types of power consumption models (PCMs). A novel tight closed-form approximation of the DMIMO EE-SE trade-off is presented and a detailed analysis is provided for the scenario with practical antenna configurations. Furthermore, generic and accurate low and high-SE approximations of this trade-off are derived for any number of radio access units (RAUs) in both the uplink and downlink channels. Our expressions have been utilized for assessing both the EE gain of DMIMO over co-located MIMO (CMIMO) and the incremental EE gain of DMIMO in the downlink channel. Our results reveal that DMIMO is more energy efficient than CMIMO for cell edge users in both the idealistic and realistic PCMs; whereas in terms of the incremental EE gain, connecting the user terminal to only one RAU is the most energy efficient approach when a realistic PCM is considered
- …