382 research outputs found
Fundamental Limits in Correlated Fading MIMO Broadcast Channels: Benefits of Transmit Correlation Diversity
We investigate asymptotic capacity limits of the Gaussian MIMO broadcast
channel (BC) with spatially correlated fading to understand when and how much
transmit correlation helps the capacity. By imposing a structure on channel
covariances (equivalently, transmit correlations at the transmitter side) of
users, also referred to as \emph{transmit correlation diversity}, the impact of
transmit correlation on the power gain of MIMO BCs is characterized in several
regimes of system parameters, with a particular interest in the large-scale
array (or massive MIMO) regime. Taking the cost for downlink training into
account, we provide asymptotic capacity bounds of multiuser MIMO downlink
systems to see how transmit correlation diversity affects the system
multiplexing gain. We make use of the notion of joint spatial division and
multiplexing (JSDM) to derive the capacity bounds. It is advocated in this
paper that transmit correlation diversity may be of use to significantly
increase multiplexing gain as well as power gain in multiuser MIMO systems. In
particular, the new type of diversity in wireless communications is shown to
improve the system multiplexing gain up to by a factor of the number of degrees
of such diversity. Finally, performance limits of conventional large-scale MIMO
systems not exploiting transmit correlation are also characterized.Comment: 29 pages, 8 figure
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
AirSync: Enabling Distributed Multiuser MIMO with Full Spatial Multiplexing
The enormous success of advanced wireless devices is pushing the demand for
higher wireless data rates. Denser spectrum reuse through the deployment of
more access points per square mile has the potential to successfully meet the
increasing demand for more bandwidth. In theory, the best approach to density
increase is via distributed multiuser MIMO, where several access points are
connected to a central server and operate as a large distributed multi-antenna
access point, ensuring that all transmitted signal power serves the purpose of
data transmission, rather than creating "interference." In practice, while
enterprise networks offer a natural setup in which distributed MIMO might be
possible, there are serious implementation difficulties, the primary one being
the need to eliminate phase and timing offsets between the jointly coordinated
access points.
In this paper we propose AirSync, a novel scheme which provides not only time
but also phase synchronization, thus enabling distributed MIMO with full
spatial multiplexing gains. AirSync locks the phase of all access points using
a common reference broadcasted over the air in conjunction with a Kalman filter
which closely tracks the phase drift. We have implemented AirSync as a digital
circuit in the FPGA of the WARP radio platform. Our experimental testbed,
comprised of two access points and two clients, shows that AirSync is able to
achieve phase synchronization within a few degrees, and allows the system to
nearly achieve the theoretical optimal multiplexing gain. We also discuss MAC
and higher layer aspects of a practical deployment. To the best of our
knowledge, AirSync offers the first ever realization of the full multiuser MIMO
gain, namely the ability to increase the number of wireless clients linearly
with the number of jointly coordinated access points, without reducing the per
client rate.Comment: Submitted to Transactions on Networkin
Optimize Power Allocation Scheme to Maximize Sum Rate in CoMP with Limited Channel State Information
Extensive use of mobile applications throws many challenges in cellular systems like cell edge
throughput, inter cell interference and spectral e�ciency. Many of these challenges have been
resolved using Coordinated Multi-Point (CoMP), developed in the Third Generation Partnership
Project for LTE-Advanced) to a great extent. CoMP cooperatively process signals from base sta-
tions that are connected to various multiple terminals (user equipment (UEs)) at transmission and
reception. This CoMP improves throughput, reduces or even removes inter-cell interference and
increases spectral e�ciency in the downlink of multi-antenna coordinated multipoint systems.
Many researchers addressed these issues assuming that BSs have the knowledge of the common
control channels dedicated to all UEs and also about the full or partial channel state information
(CSI) of all the links. From the CSI available at the BSs, multiuser interference can be managed
at the BSs. To make this feasible, UEs are responsible for collecting downlink CSI. But, CSI
measurement (instantaneous and/or statistical) is imperfect in nature because of the randomly
varying nature of the channels at random times. These incorrect CSI values available at the BSs
may, in turn, create multi-user interference. There are many techniques to suppress the multi-user
interference, among which the feedback scheme is the one which is gaining a lot of attention. In
feedback schemes, CSI information needs to be fed back to the base station from UEs in the uplink.
It is obvious, the question arises on the type and amount of feedback need to be used. Research
has been progressing in this front and some feedback techniques have been proposed. Three basic
CoMP Feedback schemes are available. Explicit or statistical channel information feedback scheme
in which channel information like channels's covariance matrix of the channel are shared between the
transmitter and receiver. Next, implicit or statistical channel information feedback which contains
information such as Channel quality indication or Precoding matrix indicator or Rank indicator. 1st
applied to TDD LTE type structure and 2nd of feedback scheme can be applied in the FDD system.
Finally, we have UE which tranmit the sounding reference signal (CSI). This type of feedback scheme
is applied to exploit channel reciprocity and to reduce channel intercell interference and this can be
applied in the TDD system. We have analyzed the scenario of LTE TDD based system. After this,
optimization of power is also required because users at the cell edge required more attention than
the user locating at the center of the cell. In my work, it shows estimated power gives exponential
divercity for high SNR as low SNR too.
In this method, a compression feedback method is analyzed to provide multi-cell spatial channel
information. It improves the feedback e�ciency and throughput. The rows and columns of the
channel matrix are compressed using Eigenmode of the user and codebook based scheme speci�ed
in LTE speci�cation. The main drawback of this scheme is that spectral e�ciency is achieved with
the cost of increased overheads for feedback and evolved NodeB (eNB). Other factor is complexity
of eNodeB which is to be addressed in future work
Deterministic equivalent performance analysis of time-varying massive MIMO systems
© 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Delayed channel state information at the transmitter (CSIT) due to time variation of the channel, coming from the users' relative movement with regard to the BS antennas, is an inevitable degrading performance factor in practical systems. Despite its importance, little attention has been paid to the literature of multi-cellular multiple-input massive multiple-output (MIMO) system by investigating only the maximal ratio combining (MRC) receiver and the maximum ratio transmission (MRT) precoder. Hence, the contribution of this work is designated by the performance analysis/comparison of/with more sophisticated linear techniques, i.e., a minimum-mean-square-error (MMSE) detector for the uplink and a regularized zero-forcing (RZF) precoder for the downlink are assessed. In particular, we derive the deterministic equivalents of the signal-to-interference-plus-noise ratios (SINRs), which capture the effect of delayed CSIT, and make the use of lengthy Monte Carlo simulations unnecessary. Furthermore, prediction of the current CSIT after applying a Wiener filter allows to evaluate the mitigation capabilities of MMSE and RZF. Numerical results depict that the proposed achievable SINRs (MMSE/RZF) are more efficient than simpler solutions (MRC/MRT) in delayed CSIT conditions, and yield a higher prediction at no special computational cost due to their deterministic nature. Nevertheless, it is shown that massive MIMO are preferable even in time-varying channel conditions.Peer reviewe
- …