25,742 research outputs found
Optimal Linear Precoding Strategies for Wideband Non-Cooperative Systems based on Game Theory-Part II: Algorithms
In this two-part paper, we address the problem of finding the optimal
precoding/multiplexing scheme for a set of non-cooperative links sharing the
same physical resources, e.g., time and bandwidth. We consider two alternative
optimization problems: P.1) the maximization of mutual information on each
link, given constraints on the transmit power and spectral mask; and P.2) the
maximization of the transmission rate on each link, using finite order
constellations, under the same constraints as in P.1, plus a constraint on the
maximum average error probability on each link. Aiming at finding decentralized
strategies, we adopted as optimality criterion the achievement of a Nash
equilibrium and thus we formulated both problems P.1 and P.2 as strategic
noncooperative (matrix-valued) games. In Part I of this two-part paper, after
deriving the optimal structure of the linear transceivers for both games, we
provided a unified set of sufficient conditions that guarantee the uniqueness
of the Nash equilibrium. In this Part II, we focus on the achievement of the
equilibrium and propose alternative distributed iterative algorithms that solve
both games. Specifically, the new proposed algorithms are the following: 1) the
sequential and simultaneous iterative waterfilling based algorithms,
incorporating spectral mask constraints; 2) the sequential and simultaneous
gradient projection based algorithms, establishing an interesting link with
variational inequality problems. Our main contribution is to provide sufficient
conditions for the global convergence of all the proposed algorithms which,
although derived under stronger constraints, incorporating for example spectral
mask constraints, have a broader validity than the convergence conditions known
in the current literature for the sequential iterative waterfilling algorithm.Comment: Paper submitted to IEEE Transactions on Signal Processing, February
22, 2006. Revised March 26, 2007. Accepted June 5, 2007. To appear on IEEE
Transactions on Signal Processing, 200
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The role of HG in the analysis of temporal iteration and interaural correlation
Decomposition by Partial Linearization: Parallel Optimization of Multi-Agent Systems
We propose a novel decomposition framework for the distributed optimization
of general nonconvex sum-utility functions arising naturally in the system
design of wireless multiuser interfering systems. Our main contributions are:
i) the development of the first class of (inexact) Jacobi best-response
algorithms with provable convergence, where all the users simultaneously and
iteratively solve a suitably convexified version of the original sum-utility
optimization problem; ii) the derivation of a general dynamic pricing mechanism
that provides a unified view of existing pricing schemes that are based,
instead, on heuristics; and iii) a framework that can be easily particularized
to well-known applications, giving rise to very efficient practical (Jacobi or
Gauss-Seidel) algorithms that outperform existing adhoc methods proposed for
very specific problems. Interestingly, our framework contains as special cases
well-known gradient algorithms for nonconvex sum-utility problems, and many
blockcoordinate descent schemes for convex functions.Comment: submitted to IEEE Transactions on Signal Processin
Distributed Power Allocation with Rate Constraints in Gaussian Parallel Interference Channels
This paper considers the minimization of transmit power in Gaussian parallel
interference channels, subject to a rate constraint for each user. To derive
decentralized solutions that do not require any cooperation among the users, we
formulate this power control problem as a (generalized) Nash equilibrium game.
We obtain sufficient conditions that guarantee the existence and nonemptiness
of the solution set to our problem. Then, to compute the solutions of the game,
we propose two distributed algorithms based on the single user waterfilling
solution: The \emph{sequential} and the \emph{simultaneous} iterative
waterfilling algorithms, wherein the users update their own strategies
sequentially and simultaneously, respectively. We derive a unified set of
sufficient conditions that guarantee the uniqueness of the solution and global
convergence of both algorithms. Our results are applicable to all practical
distributed multipoint-to-multipoint interference systems, either wired or
wireless, where a quality of service in terms of information rate must be
guaranteed for each link.Comment: Paper submitted to IEEE Transactions on Information Theory, February
17, 2007. Revised January 11, 200
Optimal design and optimal control of structures undergoing finite rotations and elastic deformations
In this work we deal with the optimal design and optimal control of
structures undergoing large rotations. In other words, we show how to find the
corresponding initial configuration and the corresponding set of multiple load
parameters in order to recover a desired deformed configuration or some
desirable features of the deformed configuration as specified more precisely by
the objective or cost function. The model problem chosen to illustrate the
proposed optimal design and optimal control methodologies is the one of
geometrically exact beam. First, we present a non-standard formulation of the
optimal design and optimal control problems, relying on the method of Lagrange
multipliers in order to make the mechanics state variables independent from
either design or control variables and thus provide the most general basis for
developing the best possible solution procedure. Two different solution
procedures are then explored, one based on the diffuse approximation of
response function and gradient method and the other one based on genetic
algorithm. A number of numerical examples are given in order to illustrate both
the advantages and potential drawbacks of each of the presented procedures.Comment: 35 pages, 11 figure
Stress management in composite biopolymer networks
Living tissues show an extraordinary adaptiveness to strain, which is crucial
for their proper biological functioning. The physical origin of this mechanical
behaviour has been widely investigated using reconstituted networks of collagen
fibres, the principal load-bearing component of tissues. However, collagen
fibres in tissues are embedded in a soft hydrated polysaccharide matrix which
generates substantial internal stresses whose effect on tissue mechanics is
unknown. Here, by combining mechanical measurements and computer simulations,
we show that networks composed of collagen fibres and a hyaluronan matrix
exhibit synergistic mechanics characterized by an enhanced stiffness and
delayed strain-stiffening. We demonstrate that the polysaccharide matrix has a
dual effect on the composite response involving both internal stress and
elastic reinforcement. Our findings elucidate how tissues can tune their
strain-sensitivity over a wide range and provide a novel design principle for
synthetic materials with programmable mechanical properties
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