271 research outputs found
Secrecy Sum-Rates for Multi-User MIMO Regularized Channel Inversion Precoding
In this paper, we propose a linear precoder for the downlink of a multi-user
MIMO system with multiple users that potentially act as eavesdroppers. The
proposed precoder is based on regularized channel inversion (RCI) with a
regularization parameter and power allocation vector chosen in such a
way that the achievable secrecy sum-rate is maximized. We consider the
worst-case scenario for the multi-user MIMO system, where the transmitter
assumes users cooperate to eavesdrop on other users. We derive the achievable
secrecy sum-rate and obtain the closed-form expression for the optimal
regularization parameter of the precoder using
large-system analysis. We show that the RCI precoder with
outperforms several other linear precoding schemes, and
it achieves a secrecy sum-rate that has same scaling factor as the sum-rate
achieved by the optimum RCI precoder without secrecy requirements. We propose a
power allocation algorithm to maximize the secrecy sum-rate for fixed .
We then extend our algorithm to maximize the secrecy sum-rate by jointly
optimizing and the power allocation vector. The jointly optimized
precoder outperforms RCI with and equal power allocation
by up to 20 percent at practical values of the signal-to-noise ratio and for 4
users and 4 transmit antennas.Comment: IEEE Transactions on Communications, accepted for publicatio
Optimal Multiuser Transmit Beamforming: A Difficult Problem with a Simple Solution Structure
Transmit beamforming is a versatile technique for signal transmission from an
array of antennas to one or multiple users [1]. In wireless communications,
the goal is to increase the signal power at the intended user and reduce
interference to non-intended users. A high signal power is achieved by
transmitting the same data signal from all antennas, but with different
amplitudes and phases, such that the signal components add coherently at the
user. Low interference is accomplished by making the signal components add
destructively at non-intended users. This corresponds mathematically to
designing beamforming vectors (that describe the amplitudes and phases) to have
large inner products with the vectors describing the intended channels and
small inner products with non-intended user channels.
While it is fairly easy to design a beamforming vector that maximizes the
signal power at the intended user, it is difficult to strike a perfect balance
between maximizing the signal power and minimizing the interference leakage. In
fact, the optimization of multiuser transmit beamforming is generally a
nondeterministic polynomial-time (NP) hard problem [2]. Nevertheless, this
lecture shows that the optimal transmit beamforming has a simple structure with
very intuitive properties and interpretations. This structure provides a
theoretical foundation for practical low-complexity beamforming schemes.
(See this lecture note for the complete abstract/introduction)Comment: Accepted for publication as lecture note in IEEE Signal Processing
Magazine, 11 pages, 3 figures. The results can be reproduced using the
following Matlab code: https://github.com/emilbjornson/optimal-beamformin
Optimal Linear Precoding in Multi-User MIMO Systems: A Large System Analysis
We consider the downlink of a single-cell multi-user MIMO system in which the
base station makes use of antennas to communicate with single-antenna
user equipments (UEs) randomly positioned in the coverage area. In particular,
we focus on the problem of designing the optimal linear precoding for
minimizing the total power consumption while satisfying a set of target
signal-to-interference-plus-noise ratios (SINRs). To gain insights into the
structure of the optimal solution and reduce the computational complexity for
its evaluation, we analyze the asymptotic regime where and grow large
with a given ratio and make use of recent results from large system analysis to
compute the asymptotic solution. Then, we concentrate on the asymptotically
design of heuristic linear precoding techniques. Interestingly, it turns out
that the regularized zero-forcing (RZF) precoder is equivalent to the optimal
one when the ratio between the SINR requirement and the average channel
attenuation is the same for all UEs. If this condition does not hold true but
only the same SINR constraint is imposed for all UEs, then the RZF can be
modified to still achieve optimality if statistical information of the UE
positions is available at the BS. Numerical results are used to evaluate the
performance gap in the finite system regime and to make comparisons among the
precoding techniques.Comment: 6 pages, 2 figures, IEEE Global Communications Conference (GLOBECOM),
Austin, Texas, Dec. 2014. An extended version of this work is available at
http://arxiv.org/abs/1406.598
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