1,059 research outputs found
Fundamental Asymptotic Behavior of (Two-User) Distributed Massive MIMO
This paper considers the uplink of a distributed Massive MIMO network where
base stations (BSs), each equipped with antennas, receive data from
users. We study the asymptotic spectral efficiency (as )
with spatial correlated channels, pilot contamination, and different degrees of
channel state information (CSI) and statistical knowledge at the BSs. By
considering a two-user setup, we can simply derive fundamental asymptotic
behaviors and provide novel insights into the structure of the optimal
combining schemes. In line with [1], when global CSI is available at all BSs,
the optimal minimum-mean squared error combining has an unbounded capacity as
, if the global channel covariance matrices of the users are
asymptotically linearly independent. This result is instrumental to derive a
suboptimal combining scheme that provides unbounded capacity as
using only local CSI and global channel statistics. The latter scheme is shown
to outperform a generalized matched filter scheme, which also achieves
asymptotic unbounded capacity by using only local CSI and global channel
statistics, but is derived following [2] on the basis of a more conservative
capacity bound.Comment: 6 pages, 2 figures, to be presented at GLOBECOM 2018, Abu Dhab
Performance Gains of Optimal Antenna Deployment for Massive MIMO Systems
We consider the uplink of a single-cell multi-user multiple-input
multiple-output (MIMO) system with several single antenna transmitters/users
and one base station with antennas in the regime. The
base station antennas are evenly distributed to admissable locations
throughout the cell.
First, we show that a reliable (per-user) rate of is achievable
through optimal locational optimization of base station antennas. We also prove
that an rate is the best possible. Therefore, in contrast to a
centralized or circular deployment, where the achievable rate is at most a
constant, the rate with a general deployment can grow logarithmically with ,
resulting in a certain form of "macromultiplexing gain."
Second, using tools from high-resolution quantization theory, we derive an
accurate formula for the best achievable rate given any and any user
density function. According to our formula, the dependence of the optimal rate
on the user density function is curiously only through the differential
entropy of . In fact, the optimal rate decreases linearly with the
differential entropy, and the worst-case scenario is a uniform user density.
Numerical simulations confirm our analytical findings.Comment: GLOBECOM 201
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
Performance Analysis of Millimeter Wave Massive MIMO Systems in Centralized and Distributed Schemes
This paper considers downlink multi-user millimeter-wave massive multiple-input multiple-output (MIMO) systems in both centralized and distributed configurations, referred to as C-MIMO and D-MIMO, respectively. Assuming the fading channel is composite and comprised of both large-scale fading and small-scale fading, a hybrid precoding algorithm leveraging antenna array response vectors is applied into both the C-MIMO system with fully connected structure and the D-MIMO system with partially connected structure. First, the asymptotic spectral efficiency (SE) of an arbitrary user and the asymptotic average SE of the cell for the C-MIMO system are analyzed. Then, two radio access unit (RAU) selection algorithms are proposed for the D-MIMO system, based on minimal distance (D-based) and maximal signal-to-interference-plus-noise-ratio (SINR) (SINR-based), respectively. For the D-MIMO system with circular layout and D-based RAU selection algorithm, the upper bounds on the asymptotic SE of an arbitrary user and the asymptotic average SE of the cell are also investigated. Finally, numerical results are provided to assess the analytical results and evaluate the effects of the numbers of total transmit antennas and users on system performance. It is shown that, from the perspective of the cell, the D-MIMO system with D-based scheme outperforms the C-MIMO system and achieves almost alike performance compared with the SINR-based solution while requiring less complexity.Peer reviewe
Massive MIMO Systems with Non-Ideal Hardware: Energy Efficiency, Estimation, and Capacity Limits
The use of large-scale antenna arrays can bring substantial improvements in
energy and/or spectral efficiency to wireless systems due to the greatly
improved spatial resolution and array gain. Recent works in the field of
massive multiple-input multiple-output (MIMO) show that the user channels
decorrelate when the number of antennas at the base stations (BSs) increases,
thus strong signal gains are achievable with little inter-user interference.
Since these results rely on asymptotics, it is important to investigate whether
the conventional system models are reasonable in this asymptotic regime. This
paper considers a new system model that incorporates general transceiver
hardware impairments at both the BSs (equipped with large antenna arrays) and
the single-antenna user equipments (UEs). As opposed to the conventional case
of ideal hardware, we show that hardware impairments create finite ceilings on
the channel estimation accuracy and on the downlink/uplink capacity of each UE.
Surprisingly, the capacity is mainly limited by the hardware at the UE, while
the impact of impairments in the large-scale arrays vanishes asymptotically and
inter-user interference (in particular, pilot contamination) becomes
negligible. Furthermore, we prove that the huge degrees of freedom offered by
massive MIMO can be used to reduce the transmit power and/or to tolerate larger
hardware impairments, which allows for the use of inexpensive and
energy-efficient antenna elements.Comment: To appear in IEEE Transactions on Information Theory, 28 pages, 15
figures. The results can be reproduced using the following Matlab code:
https://github.com/emilbjornson/massive-MIMO-hardware-impairment
Does Massive MIMO Fail in Ricean Channels?
Massive multiple-input multiple-output (MIMO) is now making its way to the
standardization exercise of future 5G networks. Yet, there are still
fundamental questions pertaining to the robustness of massive MIMO against
physically detrimental propagation conditions. On these grounds, we identify
scenarios under which massive MIMO can potentially fail in Ricean channels, and
characterize them physically, as well as, mathematically. Our analysis extends
and generalizes a stream of recent papers on this topic and articulates
emphatically that such harmful scenarios in Ricean fading conditions are
unlikely and can be compensated using any standard scheduling scheme. This
implies that massive MIMO is intrinsically effective at combating interuser
interference and, if needed, can avail of the base-station scheduler for
further robustness.Comment: IEEE Wireless Communications Letters, accepte
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