241 research outputs found
Outage Probability for Multi-Cell Processing under Rayleigh Fading
Multi-cell processing, also called Coordinated Multiple Point (CoMP), is a
very promising distributed multi-antennas technique that uses neighbour cell's
antennas. This is expected to be part of next generation cellular networks
standards such as LTE-A. Small cell networks in dense urban environment are
mainly limited by interferences and CoMP can strongly take advantage of this
fact to improve cell-edge users' throughput. This paper provides an analytical
derivation of the capacity outage probability for CoMP experiencing fast
Rayleigh fading. Only the average received power (slow varying fading) has to
be known, and perfect Channel State Information (CSI) is not required. An
optimisation of the successfully received data-rate is then derived with
respect to the number of cooperating stations and the outage probability,
illustrated by numerical examples
Linear Beamforming for the Spatially Correlated MISO broadcast channel
A spatially correlated broadcast setting with M antennas at the base station
and M users (each with a single antenna) is considered. We assume that the
users have perfect channel information about their links and the base station
has only statistical information about each user's link. The base station
employs a linear beamforming strategy with one spatial eigen-mode allocated to
each user. The goal of this work is to understand the structure of the
beamforming vectors that maximize the ergodic sum-rate achieved by treating
interference as noise. In the M = 2 case, we first fix the beamforming vectors
and compute the ergodic sum-rate in closed-form as a function of the channel
statistics. We then show that the optimal beamforming vectors are the dominant
generalized eigenvectors of the covariance matrices of the two links. It is
difficult to obtain intuition on the structure of the optimal beamforming
vectors for M > 2 due to the complicated nature of the sum-rate expression.
Nevertheless, in the case of asymptotic M, we show that the optimal beamforming
vectors have to satisfy a set of fixed-point equations.Comment: Published in IEEE ISIT 2010, 5 page
Multi-User Diversity vs. Accurate Channel State Information in MIMO Downlink Channels
In a multiple transmit antenna, single antenna per receiver downlink channel
with limited channel state feedback, we consider the following question: given
a constraint on the total system-wide feedback load, is it preferable to get
low-rate/coarse channel feedback from a large number of receivers or
high-rate/high-quality feedback from a smaller number of receivers? Acquiring
feedback from many receivers allows multi-user diversity to be exploited, while
high-rate feedback allows for very precise selection of beamforming directions.
We show that there is a strong preference for obtaining high-quality feedback,
and that obtaining near-perfect channel information from as many receivers as
possible provides a significantly larger sum rate than collecting a few
feedback bits from a large number of users.Comment: Submitted to IEEE Transactions on Communications, July 200
Receive Combining vs. Multi-Stream Multiplexing in Downlink Systems with Multi-Antenna Users
In downlink multi-antenna systems with many users, the multiplexing gain is
strictly limited by the number of transmit antennas and the use of these
antennas. Assuming that the total number of receive antennas at the
multi-antenna users is much larger than , the maximal multiplexing gain can
be achieved with many different transmission/reception strategies. For example,
the excess number of receive antennas can be utilized to schedule users with
effective channels that are near-orthogonal, for multi-stream multiplexing to
users with well-conditioned channels, and/or to enable interference-aware
receive combining. In this paper, we try to answer the question if the data
streams should be divided among few users (many streams per user) or many users
(few streams per user, enabling receive combining). Analytic results are
derived to show how user selection, spatial correlation, heterogeneous user
conditions, and imperfect channel acquisition (quantization or estimation
errors) affect the performance when sending the maximal number of streams or
one stream per scheduled user---the two extremes in data stream allocation.
While contradicting observations on this topic have been reported in prior
works, we show that selecting many users and allocating one stream per user
(i.e., exploiting receive combining) is the best candidate under realistic
conditions. This is explained by the provably stronger resilience towards
spatial correlation and the larger benefit from multi-user diversity. This
fundamental result has positive implications for the design of downlink systems
as it reduces the hardware requirements at the user devices and simplifies the
throughput optimization.Comment: Published in IEEE Transactions on Signal Processing, 16 pages, 11
figures. The results can be reproduced using the following Matlab code:
https://github.com/emilbjornson/one-or-multiple-stream
How Much Multiuser Diversity is Required for Energy Limited Multiuser Systems?
Multiuser diversity (MUDiv) is one of the central concepts in multiuser (MU)
systems. In particular, MUDiv allows for scheduling among users in order to
eliminate the negative effects of unfavorable channel fading conditions of some
users on the system performance. Scheduling, however, consumes energy (e.g.,
for making users' channel state information available to the scheduler). This
extra usage of energy, which could potentially be used for data transmission,
can be very wasteful, especially if the number of users is large. In this
paper, we answer the question of how much MUDiv is required for energy limited
MU systems. Focusing on uplink MU wireless systems, we develop MU scheduling
algorithms which aim at maximizing the MUDiv gain. Toward this end, we
introduce a new realistic energy model which accounts for scheduling energy and
describes the distribution of the total energy between scheduling and data
transmission stages. Using the fact that such energy distribution can be
controlled by varying the number of active users, we optimize this number by
either (i) minimizing the overall system bit error rate (BER) for a fixed total
energy of all users in the system or (ii) minimizing the total energy of all
users for fixed BER requirements. We find that for a fixed number of available
users, the achievable MUDiv gain can be improved by activating only a subset of
users. Using asymptotic analysis and numerical simulations, we show that our
approach benefits from MUDiv gains higher than that achievable by generic
greedy access algorithm, which is the optimal scheduling method for energy
unlimited systems.Comment: 28 pages, 9 figures, submitted to IEEE Trans. Signal Processing in
Oct. 200
Outage Constrained Robust Secure Transmission for MISO Wiretap Channels
In this paper we consider the robust secure beamformer design for MISO
wiretap channels. Assume that the eavesdroppers' channels are only partially
available at the transmitter, we seek to maximize the secrecy rate under the
transmit power and secrecy rate outage probability constraint. The outage
probability constraint requires that the secrecy rate exceeds certain threshold
with high probability. Therefore including such constraint in the design
naturally ensures the desired robustness. Unfortunately, the presence of the
probabilistic constraints makes the problem non-convex and hence difficult to
solve. In this paper, we investigate the outage probability constrained secrecy
rate maximization problem using a novel two-step approach. Under a wide range
of uncertainty models, our developed algorithms can obtain high-quality
solutions, sometimes even exact global solutions, for the robust secure
beamformer design problem. Simulation results are presented to verify the
effectiveness and robustness of the proposed algorithms
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