34 research outputs found
Robust Monotonic Optimization Framework for Multicell MISO Systems
The performance of multiuser systems is both difficult to measure fairly and
to optimize. Most resource allocation problems are non-convex and NP-hard, even
under simplifying assumptions such as perfect channel knowledge, homogeneous
channel properties among users, and simple power constraints. We establish a
general optimization framework that systematically solves these problems to
global optimality. The proposed branch-reduce-and-bound (BRB) algorithm handles
general multicell downlink systems with single-antenna users, multiantenna
transmitters, arbitrary quadratic power constraints, and robustness to channel
uncertainty. A robust fairness-profile optimization (RFO) problem is solved at
each iteration, which is a quasi-convex problem and a novel generalization of
max-min fairness. The BRB algorithm is computationally costly, but it shows
better convergence than the previously proposed outer polyblock approximation
algorithm. Our framework is suitable for computing benchmarks in general
multicell systems with or without channel uncertainty. We illustrate this by
deriving and evaluating a zero-forcing solution to the general problem.Comment: Published in IEEE Transactions on Signal Processing, 16 pages, 9
figures, 2 table
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
Interference Leakage Neutralization in Two-Hop Wiretap Channels with Partial CSI
In this paper, we analyze the four-node relay wiretap channel, where the relay performs amplify-and-forward. There is no direct link between transmitter and receiver available. The transmitter has multiple antennas, which assist in securing the transmission over both phases. In case of full channel state information (CSI), the transmitter can apply information leakage neutralization in order to prevent the eavesdropper from obtaining any information about the signal sent. This gets more challenging, if the transmitter has only an outdated estimate of the channel from the relay to the eavesdropper. For this case, we optimize the worst case secrecy rate by choosing intelligently the beamforming vectors and the power allocation at the transmitter and the relay
Pareto Characterization of the Multicell MIMO Performance Region With Simple Receivers
We study the performance region of a general multicell downlink scenario with
multiantenna transmitters, hardware impairments, and low-complexity receivers
that treat interference as noise. The Pareto boundary of this region describes
all efficient resource allocations, but is generally hard to compute. We
propose a novel explicit characterization that gives Pareto optimal transmit
strategies using a set of positive parameters---fewer than in prior work. We
also propose an implicit characterization that requires even fewer parameters
and guarantees to find the Pareto boundary for every choice of parameters, but
at the expense of solving quasi-convex optimization problems. The merits of the
two characterizations are illustrated for interference channels and ideal
network multiple-input multiple-output (MIMO).Comment: Published in IEEE Transactions on Signal Processing, 6 pages, 6
figure