The Experts below are selected from a list of 9 Experts worldwide ranked by ideXlab platform

Wenjiang Feng - One of the best experts on this subject based on the ideXlab platform.

  • joint power allocation at the base station and the relay for untrusted relay cooperation ofdma network
    International Journal of Antennas and Propagation, 2015
    Co-Authors: Weiheng Jiang, Wenjiang Feng
    Abstract:

    The secure communication that multiple OFDMA-based cell-edge mobile stations (MS) can only transmit confidential messages to base station (BS) through an untrusted intermediate relay (UR) is discussed. Specifically, with the destination-based jamming (DBJ) scheme and fixed MS transmission power assumption, our focus is on the joint BS and US power allocation to maximize system sum secrecy rate. We first analyze the challenges in solving this Problem. The result indicates that our nonconvex joint power allocation is equivalent to a joint MS access control and power allocation. Then, by Problem Relaxation and the alternating optimization approach, two suboptimal joint MS access control and power allocation algorithms are proposed. These algorithms alternatively solve the subProblem of joint BS and UR power allocation and the subProblem of MS selection until system sum secrecy rate is nonincreasing. In addition, the convergence and computational complexity of the proposed algorithms are analyzed. Finally, simulations results are presented to demonstrate the performance of our proposed algorithms.

Weiheng Jiang - One of the best experts on this subject based on the ideXlab platform.

  • joint power allocation at the base station and the relay for untrusted relay cooperation ofdma network
    International Journal of Antennas and Propagation, 2015
    Co-Authors: Weiheng Jiang, Wenjiang Feng
    Abstract:

    The secure communication that multiple OFDMA-based cell-edge mobile stations (MS) can only transmit confidential messages to base station (BS) through an untrusted intermediate relay (UR) is discussed. Specifically, with the destination-based jamming (DBJ) scheme and fixed MS transmission power assumption, our focus is on the joint BS and US power allocation to maximize system sum secrecy rate. We first analyze the challenges in solving this Problem. The result indicates that our nonconvex joint power allocation is equivalent to a joint MS access control and power allocation. Then, by Problem Relaxation and the alternating optimization approach, two suboptimal joint MS access control and power allocation algorithms are proposed. These algorithms alternatively solve the subProblem of joint BS and UR power allocation and the subProblem of MS selection until system sum secrecy rate is nonincreasing. In addition, the convergence and computational complexity of the proposed algorithms are analyzed. Finally, simulations results are presented to demonstrate the performance of our proposed algorithms.

Quinzan Francesco - One of the best experts on this subject based on the ideXlab platform.

  • Non-Monotone Submodular Maximization with Multiple Knapsacks in Static and Dynamic Settings
    2020
    Co-Authors: Doskoč Vanja, Friedrich Tobias, Göbel Andreas, Neumann Frank, Neumann Aneta, Quinzan Francesco
    Abstract:

    We study the Problem of maximizing a non-monotone submodular function under multiple knapsack constraints. We propose a simple discrete greedy algorithm to approach this Problem, and prove that it yields strong approximation guarantees for functions with bounded curvature. In contrast to other heuristics, this requires no Problem Relaxation to continuous domains and it maintains a constant-factor approximation guarantee in the Problem size. In the case of a single knapsack, our analysis suggests that the standard greedy can be used in non-monotone settings. Additionally, we study this Problem in a dynamic setting, by which knapsacks change during the optimization process. We modify our greedy algorithm to avoid a complete restart at each constraint update. This modification retains the approximation guarantees of the static case. We evaluate our results experimentally on a video summarization and sensor placement task. We show that our proposed algorithm competes with the state-of-the-art in static settings. Furthermore, we show that in dynamic settings with tight computational time budget, our modified greedy yields significant improvements over starting the greedy from scratch, in terms of the solution quality achieved

Heczko Jan - One of the best experts on this subject based on the ideXlab platform.

  • Homogenization and numerical modelling of poroelastic materials with self-contact in the microstructure
    'Elsevier BV', 2020
    Co-Authors: Rohan Eduard, Heczko Jan
    Abstract:

    We present a two-scale homogenization-based computational model of porous elastic materials subject to external loads inducing the self-contact interaction at the pore level. Microstructures under consideration are constituted as periodic lattices generated by a representative cell consisting of a solid skeleton and a pore. On its surface, the unilateral frictionless contact appears when the porous material is deformed. We focus on microstructures with rigid inclusions whereby the contact process involves opposing surfaces on the rigid and the compliant skeleton parts. A macroscopic model is derived using the periodic unfolding homogenization and the method of oscillating test functions. An efficient algorithm for the two-scale computational analysis is proposed for the numerical model obtained using the finite element discretization of the homogenized model. For this, a sequential linearization of the two-scale elasticity Problem leads to the consistent effective elasticity tensor yielding consistent stiffness matrices of the macroscopic incremental formulation. The micro-level contact Problem attains the form of a nonsmooth equation solved using the semi-smooth Newton method without any regularization, or Problem Relaxation. Numerical examples of two-dimensional deforming structures are presented as a proof of the concept. The proposed modelling approach can be extended to treat self-contact in structures subject to finite deformation

Doskoč Vanja - One of the best experts on this subject based on the ideXlab platform.

  • Non-Monotone Submodular Maximization with Multiple Knapsacks in Static and Dynamic Settings
    2020
    Co-Authors: Doskoč Vanja, Friedrich Tobias, Göbel Andreas, Neumann Frank, Neumann Aneta, Quinzan Francesco
    Abstract:

    We study the Problem of maximizing a non-monotone submodular function under multiple knapsack constraints. We propose a simple discrete greedy algorithm to approach this Problem, and prove that it yields strong approximation guarantees for functions with bounded curvature. In contrast to other heuristics, this requires no Problem Relaxation to continuous domains and it maintains a constant-factor approximation guarantee in the Problem size. In the case of a single knapsack, our analysis suggests that the standard greedy can be used in non-monotone settings. Additionally, we study this Problem in a dynamic setting, by which knapsacks change during the optimization process. We modify our greedy algorithm to avoid a complete restart at each constraint update. This modification retains the approximation guarantees of the static case. We evaluate our results experimentally on a video summarization and sensor placement task. We show that our proposed algorithm competes with the state-of-the-art in static settings. Furthermore, we show that in dynamic settings with tight computational time budget, our modified greedy yields significant improvements over starting the greedy from scratch, in terms of the solution quality achieved