21,912 research outputs found
Well-posedness and Robust Preconditioners for the Discretized Fluid-Structure Interaction Systems
In this paper we develop a family of preconditioners for the linear algebraic
systems arising from the arbitrary Lagrangian-Eulerian discretization of some
fluid-structure interaction models. After the time discretization, we formulate
the fluid-structure interaction equations as saddle point problems and prove
the uniform well-posedness. Then we discretize the space dimension by finite
element methods and prove their uniform well-posedness by two different
approaches under appropriate assumptions. The uniform well-posedness makes it
possible to design robust preconditioners for the discretized fluid-structure
interaction systems. Numerical examples are presented to show the robustness
and efficiency of these preconditioners.Comment: 1. Added two preconditioners into the analysis and implementation 2.
Rerun all the numerical tests 3. changed title, abstract and corrected lots
of typos and inconsistencies 4. added reference
Blind Demixing for Low-Latency Communication
In the next generation wireless networks, lowlatency communication is
critical to support emerging diversified applications, e.g., Tactile Internet
and Virtual Reality. In this paper, a novel blind demixing approach is
developed to reduce the channel signaling overhead, thereby supporting
low-latency communication. Specifically, we develop a low-rank approach to
recover the original information only based on a single observed vector without
any channel estimation. Unfortunately, this problem turns out to be a highly
intractable non-convex optimization problem due to the multiple non-convex
rankone constraints. To address the unique challenges, the quotient manifold
geometry of product of complex asymmetric rankone matrices is exploited by
equivalently reformulating original complex asymmetric matrices to the
Hermitian positive semidefinite matrices. We further generalize the geometric
concepts of the complex product manifolds via element-wise extension of the
geometric concepts of the individual manifolds. A scalable Riemannian
trust-region algorithm is then developed to solve the blind demixing problem
efficiently with fast convergence rates and low iteration cost. Numerical
results will demonstrate the algorithmic advantages and admirable performance
of the proposed algorithm compared with the state-of-art methods.Comment: 14 pages, accepted by IEEE Transaction on Wireless Communicatio
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