61 research outputs found
Communicating over Filter-and-Forward Relay Networks with Channel Output Feedback
Relay networks aid in increasing the rate of communication from source to
destination. However, the capacity of even a three-terminal relay channel is an
open problem. In this work, we propose a new lower bound for the capacity of
the three-terminal relay channel with destination-to-source feedback in the
presence of correlated noise. Our lower bound improves on the existing bounds
in the literature. We then extend our lower bound to general relay network
configurations using an arbitrary number of filter-and-forward relay nodes.
Such network configurations are common in many multi-hop communication systems
where the intermediate nodes can only perform minimal processing due to limited
computational power. Simulation results show that significant improvements in
the achievable rate can be obtained through our approach. We next derive a
coding strategy (optimized using post processed signal-to-noise ratio as a
criterion) for the three-terminal relay channel with noisy channel output
feedback for two transmissions. This coding scheme can be used in conjunction
with open-loop codes for applications like automatic repeat request (ARQ) or
hybrid-ARQ.Comment: 15 pages, 8 figures, to appear in IEEE Transactions on Signal
Processin
Robust Constrained Model Predictive Control using Linear Matrix Inequalities
The primary disadvantage of current design techniques for model predictive control (MPC) is their inability to deal explicitly with plant model uncertainty. In this paper, we present a new approach for robust MPC synthesis which allows explicit incorporation of the description of plant uncertainty in the problem formulation. The uncertainty is expressed both in the time domain and the frequency domain. The goal is to design, at each time step, a state-feedback control law which minimizes a "worst-case" infinite horizon objective function, subject to constraints on the control input and plant output. Using standard techniques, the problem of minimizing an upper bound on the "worst-case" objective function, subject to input and output constraints, is reduced to a convex optimization involving linear matrix inequalities (LMIs). It is shown that the feasible receding horizon state-feedback control design robustly stabilizes the set of uncertain plants under consideration. Several extensions, such as application to systems with time-delays and problems involving constant set-point tracking, trajectory tracking and disturbance rejection, which follow naturally from our formulation, are discussed. The controller design procedure is illustrated with two examples. Finally, conclusions are presented
Using Channel Output Feedback to Increase Throughput in Hybrid-ARQ
Hybrid-ARQ protocols have become common in many packet transmission systems
due to their incorporation in various standards. Hybrid-ARQ combines the normal
automatic repeat request (ARQ) method with error correction codes to increase
reliability and throughput. In this paper, we look at improving upon this
performance using feedback information from the receiver, in particular, using
a powerful forward error correction (FEC) code in conjunction with a proposed
linear feedback code for the Rayleigh block fading channels. The new hybrid-ARQ
scheme is initially developed for full received packet feedback in a
point-to-point link. It is then extended to various different multiple-antenna
scenarios (MISO/MIMO) with varying amounts of packet feedback information.
Simulations illustrate gains in throughput.Comment: 30 page
Undetected locked-joint failures in kinematically redundant manipulators: a workspace analysis
Includes bibliographical references.Robots are frequently used for operations in hostile environments. The very nature of these environments, however, increases the likelihood of robot failures. Common failure tolerance techniques rely on effective failure detection. Since a failure may not always be successfully detected, or even if detected, may not be detected soon enough, it becomes important to consider the behavior of manipulators with undetected failures. This work focuses on developing techniques to analyze a manipulator's workspace and identify regions in which tasks, characterized by sequences of point-to-point moves, can be completed even with such failures. Measures of fault tolerance are formulated to allow for the evaluation of the workspace.This work was supported by Sandia National Labs under contract no. AL-3011 and by NSF under contract no. MIP-9708309
Analysis of the post-fault behavior of robotic manipulators, An
Includes bibliographical references.Operations in hazardous or remote environments are invariably performed by robots. The hostile nature of the environments, however, increase the likelihood of failures for robots used in such applications. The difficulty and delay in the detection and consequent correction of these faults makes the post-fault performance of the robots particularly important. This work investigates the behavior of robots experiencing undetected locked-joint failures in a general class of tasks characterized by point-to-point motion. The robot is considered to have "converged" to a task position and orientation if all its joints come to rest when the end-effector is at that position. It is seen that the post-fault behavior may be classified into three categories: 1) The robot converges to the task position; 2) the robot converges to a position other than the task position; or 3) the robot does not converge, but keeps moving forever. The specific conditions for convergence are identified, and the different behaviors illustrated with examples of simple planar manipulators.This work was supported by Sandia National Laboratories under contract number AL-3011
Fast eigenspace decomposition of correlated images
Includes bibliographical references.We present a computationally efficient algorithm for the eigenspace decomposition of correlated images. Our approach is motivated by the fact that for a planar rotation of a two-dimensional image, analytical expressions can be given for the eigendecomposition, based on the theory of circulant matrices. These analytical expressions turn out to be good first approximations of the eigendecomposition, even for three-dimensional objects rotated about a single axis. We use this observation to automatically determine the dimension of the subspace required to represent an image with a guaranteed user-specified accuracy, as well as to quickly compute a basis for the subspace. Examples show that the algorithm performs very well on a range of test images composed of three-dimensional objects rotated about a single axis.This work was supported by the Sze Tsao Chang Memorial Engineering Fund and by the Office of Naval Research under contract no. N00014-97-1-0540
Fast eigenspace decomposition of correlated images
Includes bibliographical references.We present a computationally efficient algorithm for the eigenspace decomposition of correlated images. Our approach is motivated by the fact that for a planar rotation of a two-dimensional (2-D) image, analytical expressions can be given for the eigendecomposition, based on the theory of circulant matrices. These analytical expressions turn out to be good first approximations of the eigendecomposition, even for three-dimensional (3-D) objects rotated about a single axis. In addition, the theory of circulant matrices yields good approximations to the eigendecomposition for images that result when objects are translated and scaled. We use these observations to automatically determine the dimension of the subspace required to represent an image with a guaranteed user-specified accuracy, as well as to quickly compute a basis for the subspace. Examples show that the algorithm performs very well on a number of test cases ranging from images of 3-D objects rotated about a single axis to arbitrary video sequences.This work was supported by the Sze Tsao Chang Memorial Engineering Fund, the National Imagery and Mapping Agency under Contract NMA201-00-1-1003, and by the Office of Naval Research under Contract N00014-97-1-0640
Real-time failure-tolerant control of kinematically redundant manipulators
Includes bibliographical references.This work considers real-time fault-tolerant control of kinematically redundant manipulators to single locked-joint failures. The fault-tolerance measure used is a worst-case quantity, given by the minimum, over all single joint failures, of the minimum singular value of the post-failure Jacobians. Given any end-effector trajectory, the goal is to continuously follow this trajectory with the manipulator in configurations that maximize the fault-tolerance measure. The computation required to track these optimal configurations with brute-force methods is prohibitive for real-time implementation. We address this issue by presenting algorithms that quickly compute estimates of the worst-case fault-tolerance measure and its gradient. Real-time implementations are presented for all these techniques, and comparisons show that the performance of the best is indistinguishable from that of brute-force implementations.This work was supported by Sandia National Laboratories under contract number AL-3011
Real-time failure-tolerant control of kinematically redundant manipulators
Includes bibliographical references (pages 1115-1116).This work considers real-time fault-tolerant control of kinematically redundant manipulators to single locked-joint failures. The fault-tolerance measure used is a worst-case quantity, given by the minimum, over all single joint failures, of the minimum singular value of the post-failure Jacobians. Given any end-effector trajectory, the goal is to continuously follow this trajectory with the manipulator in configurations that maximize the fault-tolerance measure. The computation required to track these optimal configurations with brute-force methods is prohibitive for real-time implementation. We address this issue by presenting algorithms that quickly compute estimates of the worst-case fault-tolerance measure and its gradient. Comparisons show that the performance of the best method is indistinguishable from that of brute-force implementations. An example demonstrating the real-time performance of the algorithm on a commercially available seven degree-of-freedom manipulator is presented
Distributed NEGF Algorithms for the Simulation of Nanoelectronic Devices with Scattering
Through the Non-Equilibrium Green's Function (NEGF) formalism, quantum-scale
device simulation can be performed with the inclusion of electron-phonon
scattering. However, the simulation of realistically sized devices under the
NEGF formalism typically requires prohibitive amounts of memory and computation
time. Two of the most demanding computational problems for NEGF simulation
involve mathematical operations with structured matrices called semiseparable
matrices. In this work, we present parallel approaches for these computational
problems which allow for efficient distribution of both memory and computation
based upon the underlying device structure. This is critical when simulating
realistically sized devices due to the aforementioned computational burdens.
First, we consider determining a distributed compact representation for the
retarded Green's function matrix . This compact representation is exact
and allows for any entry in the matrix to be generated through the inherent
semiseparable structure. The second parallel operation allows for the
computation of electron density and current characteristics for the device.
Specifically, matrix products between the distributed representation for the
semiseparable matrix and the self-energy scattering terms in
produce the less-than Green's function . As an illustration
of the computational efficiency of our approach, we stably generate the
mobility for nanowires with cross-sectional sizes of up to 4.5nm, assuming an
atomistic model with scattering
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