376 research outputs found
Sectoring in Multi-cell Massive MIMO Systems
In this paper, the downlink of a typical massive MIMO system is studied when
each base station is composed of three antenna arrays with directional antenna
elements serving 120 degrees of the two-dimensional space. A lower bound for
the achievable rate is provided. Furthermore, a power optimization problem is
formulated and as a result, centralized and decentralized power allocation
schemes are proposed. The simulation results reveal that using directional
antennas at base stations along with sectoring can lead to a notable increase
in the achievable rates by increasing the received signal power and decreasing
'pilot contamination' interference in multicell massive MIMO systems. Moreover,
it is shown that using optimized power allocation can increase 0.95-likely rate
in the system significantly
Massive MIMO for Next Generation Wireless Systems
Multi-user Multiple-Input Multiple-Output (MIMO) offers big advantages over
conventional point-to-point MIMO: it works with cheap single-antenna terminals,
a rich scattering environment is not required, and resource allocation is
simplified because every active terminal utilizes all of the time-frequency
bins. However, multi-user MIMO, as originally envisioned with roughly equal
numbers of service-antennas and terminals and frequency division duplex
operation, is not a scalable technology. Massive MIMO (also known as
"Large-Scale Antenna Systems", "Very Large MIMO", "Hyper MIMO", "Full-Dimension
MIMO" & "ARGOS") makes a clean break with current practice through the use of a
large excess of service-antennas over active terminals and time division duplex
operation. Extra antennas help by focusing energy into ever-smaller regions of
space to bring huge improvements in throughput and radiated energy efficiency.
Other benefits of massive MIMO include the extensive use of inexpensive
low-power components, reduced latency, simplification of the media access
control (MAC) layer, and robustness to intentional jamming. The anticipated
throughput depend on the propagation environment providing asymptotically
orthogonal channels to the terminals, but so far experiments have not disclosed
any limitations in this regard. While massive MIMO renders many traditional
research problems irrelevant, it uncovers entirely new problems that urgently
need attention: the challenge of making many low-cost low-precision components
that work effectively together, acquisition and synchronization for
newly-joined terminals, the exploitation of extra degrees of freedom provided
by the excess of service-antennas, reducing internal power consumption to
achieve total energy efficiency reductions, and finding new deployment
scenarios. This paper presents an overview of the massive MIMO concept and
contemporary research.Comment: Final manuscript, to appear in IEEE Communications Magazin
Massive MIMO: How many antennas do we need?
We consider a multicell MIMO uplink channel where each base station (BS) is
equipped with a large number of antennas N. The BSs are assumed to estimate
their channels based on pilot sequences sent by the user terminals (UTs).
Recent work has shown that, as N grows infinitely large, (i) the simplest form
of user detection, i.e., the matched filter (MF), becomes optimal, (ii) the
transmit power per UT can be made arbitrarily small, (iii) the system
performance is limited by pilot contamination. The aim of this paper is to
assess to which extent the above conclusions hold true for large, but finite N.
In particular, we derive how many antennas per UT are needed to achieve \eta %
of the ultimate performance. We then study how much can be gained through more
sophisticated minimum-mean-square-error (MMSE) detection and how many more
antennas are needed with the MF to achieve the same performance. Our analysis
relies on novel results from random matrix theory which allow us to derive
tight approximations of achievable rates with a class of linear receivers.Comment: 6 pages, 3 figures, to be presented at the Allerton Conference on
Communication, Control and Computing, Urbana-Champaign, Illinois, US, Sep.
201
Massive MIMO for Internet of Things (IoT) Connectivity
Massive MIMO is considered to be one of the key technologies in the emerging
5G systems, but also a concept applicable to other wireless systems. Exploiting
the large number of degrees of freedom (DoFs) of massive MIMO essential for
achieving high spectral efficiency, high data rates and extreme spatial
multiplexing of densely distributed users. On the one hand, the benefits of
applying massive MIMO for broadband communication are well known and there has
been a large body of research on designing communication schemes to support
high rates. On the other hand, using massive MIMO for Internet-of-Things (IoT)
is still a developing topic, as IoT connectivity has requirements and
constraints that are significantly different from the broadband connections. In
this paper we investigate the applicability of massive MIMO to IoT
connectivity. Specifically, we treat the two generic types of IoT connections
envisioned in 5G: massive machine-type communication (mMTC) and ultra-reliable
low-latency communication (URLLC). This paper fills this important gap by
identifying the opportunities and challenges in exploiting massive MIMO for IoT
connectivity. We provide insights into the trade-offs that emerge when massive
MIMO is applied to mMTC or URLLC and present a number of suitable communication
schemes. The discussion continues to the questions of network slicing of the
wireless resources and the use of massive MIMO to simultaneously support IoT
connections with very heterogeneous requirements. The main conclusion is that
massive MIMO can bring benefits to the scenarios with IoT connectivity, but it
requires tight integration of the physical-layer techniques with the protocol
design.Comment: Submitted for publicatio
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