Iterative Design Algorithm Research Articles

Functional quantizer design for source localization in sensor networks

In this paper, we address the problem of quantizer design optimized for a source localization application in acoustic sensor networks where physically separated sensors make measurements of acoustic signal energy, quantize them, and transmit the quantized data to a fusion node, which then produces an estimate of the source location. We propose an iterative regular quantizer design algorithm that minimizes the localization error. To construct regular quantization partitions, we suggest the average distance error as a metric in the functional quantization since the distance is monotonic in each sensor reading. Furthermore, to guarantee minimization of the localization error, we propose a new technique to update the codewords and prove that the localization error can be reduced at each iteration while the average distance error remains nonincreasing by applying our update technique. Our experiments show that our proposed algorithm yields significantly improved performance as compared with traditional quantizer designs.

Robust finite frequency range iterative learning control design and experimental verification

Iterative learning control is an application for two-dimensional control systems analysis where it is possible to simultaneously address error convergence and transient response specifications but there is a requirement to enforce frequency attenuation of the error between the output and reference over the complete spectrum. In common with other control algorithm design methods, this can be a very difficult specification to meet but often the control of physical/industrial systems is only required over a finite frequency range. This paper uses the generalized Kalman–Yakubovich–Popov lemma to develop a two-dimensional systems based iterative learning control law design algorithm where frequency attenuation is only imposed over a finite frequency range to be determined from knowledge of the application and its operation. An extension to robust control law design in the presence of norm-bounded uncertainty is also given and its applicability relative to alternative settings for design discussed. The resulting designs are experimentally tested on a gantry robot used for the same purpose with other iterative learning control algorithms.

Joint Source and Relay Design for MIMO Relaying Broadcast Channels

In this letter, we address the optimal source and relay matrices design for the multiple-input multiple-output (MIMO) relaying broadcast channels (BC) with direct links (DLs) based on weighted sum-rate criterion. This problem is nonlinear nonconvex and its optimal solution remains open. To develop an efficient way to solve this problem, we first set up an equivalent problem, and solve it by decoupling it into two tractable subproblems. Finally, we propose a general linear iterative design algorithm based on alternative optimization. This iterative design algorithm is convergent since the solution of each subproblem is optimal and unique. The advantage of the proposed iterative design scheme is demonstrated by numerical experiments.

간섭 채널을 위한 통합 궤환 정보 설계

In this paper, we study joint feedback design for interference channel (IC). We develop a simple iterative algorithm for the joint feedback design to maximize the expected rate when the transmitters use partial channel-state information (CSI) obtained by the feedback link. Also, from the simulation result, we show that the performance gain is obtained compared to the conventional scheme.

Outage Probability and Outage-Based Robust Beamforming for MIMO Interference Channels with Imperfect Channel State Information

In this paper, the outage probability and outage-based beam design for multiple-input multiple-output (MIMO) interference channels are considered. First, closed-form expressions for the outage probability in MIMO interference channels are derived under the assumption of Gaussian-distributed channel state information (CSI) error, and the asymptotic behavior of the outage probability as a function of several system parameters is examined by using the Chernoff bound. It is shown that the outage probability decreases exponentially with respect to the quality of CSI measured by the inverse of the mean square error of CSI. Second, based on the derived outage probability expressions, an iterative beam design algorithm for maximizing the sum outage rate is proposed. Numerical results show that the proposed beam design algorithm yields better sum outage rate performance than conventional algorithms such as interference alignment developed under the assumption of perfect CSI.

Iterative System Identification and Controller Design with an LMI‐Based Framework: Windsurfer‐Like Approach

An LMI‐based method for the integrated system identification and controller design is proposed in the paper. We use the fact that a class of a system identification problem results in an LMI optimization problem. By combining LMIs for the system identification and those to obtain a discrete time controller we propose a framework to integrate two steps for the model‐based control system design, that is, the system identification and the controller synthesis. The framework enables us to obtain a good model for control and a model‐based feedback controller simultaneously in the sense of the closed‐loop performance. An iterative design algorithm similar to so‐called Windsurfer Approach is presented.

Joint Source and Relay Precoding Designs for MIMO Two-Way Relaying Based on MSE Criterion

Properly designed precoders can significantly improve the spectral efficiency of multiple-input multiple-output (MIMO) relay systems. In this paper, we investigate joint source and relay precoding design based on the mean-square-error (MSE) criterion in MIMO two-way relay systems, where two multi-antenna source nodes exchange information via a multi-antenna amplify-and-forward relay node. This problem is non-convex and its optimal solution remains unsolved. Aiming to find an efficient way to solve the problem, we first decouple the primal problem into three tractable sub-problems, and then propose an iterative precoding design algorithm based on alternating optimization. The solution to each sub-problem is optimal and unique, thus the convergence of the iterative algorithm is guaranteed. Secondly, we propose a structured precoding design to lower the computational complexity. The proposed precoding structure is able to parallelize the channels in the multiple access (MAC) phase and broadcast (BC) phase. It thus reduces the precoding design to a simple power allocation problem. Lastly, for the special case where only a single data stream is transmitted from each source node, we present a source-antenna-selection (SAS) based precoding design algorithm. This algorithm selects only one antenna for transmission from each source and thus requires lower signalling overhead. Comprehensive simulation is conducted to evaluate the effectiveness of all the proposed precoding designs.

Quantizer Design for Energy-Based Source Localization in Sensor Networks

We consider energy-based source localization applications, where distributed sensors quantize acoustic signal energy readings and transmit quantized data to a fusion node, which then produces an estimate of the source location. We propose an iterative quantizer design algorithm that allows us to take into account localization accuracy for quantizer design in the framework of the generalized Lloyd algorithm. Since source coding methodologies based on the Lloyd algorithm suffer from the presence of numerous poor local optima depending on initialization of quantizers, we introduce an efficient initialization, the equally distance-divided quantizer (EDQ), designed so that quantizer partitions correspond to a uniform partitioning in terms of distance. Our simulations demonstrate that improved performance over traditional quantizer designs can be achieved by using our proposed application specific strategy.

Three-dimensional holographic lithography by an iterative algorithm

We have applied an iterative algorithm for hologram design with multiple output image planes arranged in close proximity to create continuous patterns within an imaging volume. These holograms have been designed for photolithography on three-dimensional surfaces. The influence of simulated image plane separation on the final image, and its suitability for lithography, is assessed. Results are presented and the most suitable case is demonstrated experimentally.

Topology design of three-dimensional continuum structures using isosurfaces

Isolines Topology Design (ITD) is an iterative algorithm for the topological design of two-dimensional continuum structures using isolines. This paper presents an extension to this algorithm for topology design of three-dimensional continuum structures. The topology and the shape of the design depend on an iterative algorithm, which continually adds and removes material depending on the shape and distribution of the contour isosurfaces for the required structural behaviour. In this study the von Mises stress was investigated. Several examples are presented to show the effectiveness of the algorithm, which produces final designs with very detailed surfaces without the need for interpretation. The results demonstrate how the ITD algorithm can produce realistic designs by using the design criteria contour isosurface.

Distortion-invariant pattern recognition with local correlations

Local adaptive correlations for distortion-invariant and robust pattern recognition are presented. An iterative training algorithm for design of adaptive filters is utilized. The recognition performance of the proposed filters in noisy environment is compared with that of linear composite filters in terms of noise robustness and discrimination capability. Computer simulation results are provided and discussed.

Optimal Selection of sigma-Cycle for Optical Networks. An approach based on Genetic Algorithm

The study of prevention and protection against failures is a central problem in Optical Networks due to the growth of capacity demand for data transmission, especially with the Internet traffic. Without protection, failures of links or nodes cause huge losses of data. The ρ-Cycle protection is a novel approach based on pre-configured protection cycles to provide a fast recovery for single link failure. This work proposes a Genetic Algorithm to solve the ρ-Cycle protection question. Experimental tests carried out on different topologies have shown that this new proposal is a promising approach to achieve better results when compared to a well-known state-of-the-art alternative called Capacitated Iterative Design Algorithm - CIDA.

Topology design for multiple loading conditions of continuum structures using isolines and isosurfaces

Isolines topology design (ITD) is an iterative algorithm for the topological design of two-dimensional continuum structures using isolines. This paper presents an extension to this algorithm for topology design under multiple load cases of two/three-dimensional continuum structures. The topology and the shape of the design depend on an iterative algorithm, which continually adds and removes material depending on the shape and distribution of the contour isolines/isosurfaces of the required structural behaviour. In this study the von Mises stress was investigated. Several examples are presented to show the effectiveness of the algorithm, which provides very detailed contours without the need to interpret the topology in order to obtain a final design. The ITD algorithm demonstrates how the use the multiple loading conditions can produces more stable and realistic designs with a little additional complexity.

Data-based Optimal Control for Discrete-time Zero-sum Games of 2-D Systems Using Adaptive Critic Designs

In this paper, an iterative adaptive critic design (ACD) algorithm is proposed to solve a class of discrete-time two-person zero-sum games for Roesser type 2-D system. The idea is to use adaptive critic technique to obtain the optimal control pair iteratively to make the performance index function reach the saddle point of the zero-sum games. The proposed iterative ACD algorithm can be implemented based on the input and state data without the system model. Stability analysis of the 2-D system is presented and the convergence property of the performance index function is also proved. Neural networks are used to approximate the performance index function and compute the optimal control policies, respectively, for facilitating the implementation of the iterative ACD algorithm. The optimal control scheme of the air drying process is given to illustrate the performance of the proposed method.

An iterative algorithm for optimal design of non-frequency-selective FIR digital filters

This paper proposes a novel iterative algorithm for optimal design of non-frequency-selective Finite Impulse Response (FIR) digital filters based on the windowing method. Different from the traditional optimization concept of adjusting the window or the filter order in the windowing design of an FIR digital filter, the key idea of the algorithm is minimizing the approximation error by successively modifying the design result through an iterative procedure under the condition of a fixed window length. In the iterative procedure, the known deviation of the designed frequency response in each iteration from the ideal frequency response is used as a reference for the next iteration. Because the approximation error can be specified variably, the algorithm is applicable for the design of FIR digital filters with different technical requirements in the frequency domain. A design example is employed to illustrate the efficiency of the algorithm.

On Designing Fuzzy Controllers for a Class of Nonlinear Networked Control Systems

This paper is concerned with controller design for a class of nonlinear networked control systems. These systems are approximated by uncertain linear networked Takagi-Sugeno (T-S) models with both network-induced delay and data packet dropout. Sufficient conditions are derived for the existence of a fuzzy controllers. Then, an iterative algorithm for the controller design is proposed. A control problem of a flexible-joint robot arm system is studied to show the effectiveness of the iterative algorithm.

On the Design of Linear Transceivers for Multiuser Systems with Channel Uncertainty

We consider the design of linear transceivers for multiuser communication systems in the presence of uncertain channel state information (CSI), with an emphasis on downlink systems with a single antenna at each receiver. For systems with uplink-downlink reciprocity, we consider a stochastic model for the channel uncertainty, and we propose an efficient algorithm for the joint design of the linear preceding matrix at the base station and the equalizing gains at the receivers so as to minimize the average mean-square-error (MSE) over the channel uncertainty. The design is based on a generalization, derived herein, of the MSE duality between the broadcast and multiple access channels (MAC) to scenarios with uncertain CSI, and on a convex formulation for the design of robust transceivers for the dual MAC. For systems in which quantized channel feedback is employed, we consider a deterministically-bounded model for the channel uncertainty, and we study the design of robust downlink transceivers that minimize the worst- case MSE over all admissible channels. While we show that the design problem is NP-hard, we also propose an iterative local optimization algorithm that is based on efficiently-solvable convex conic formulations. Our framework is quite flexible, and can incorporate different bounded uncertainty models as well as a variety of power constraints. In particular, we study a "system-wide" uncertainty model, and although the resulting design problem is still NP hard, it does result in a significantly simpler iterative local design algorithm than the "per-user" uncertainty model. Our approaches to the minimax design for the downlink can be extended to the uplink, and we provide explicit formulations for the resulting uplink designs. Simulation results indicate that the proposed approaches to robust linear transceiver design can significantly reduce the sensitivity of the downlink to uncertain CSI, and can provide improved performance over that of existing robust designs.

Quantization for Maximin ARE in Distributed Estimation

We consider the design of optimal quantizers for the distributed estimation of a deterministic parameter. In particular, we design deterministic scalar quantizers to maximize the minimum asymptotic relative efficiency (ARE) between quantized and unquantized ML estimators. We first design identical quantizers using the class of score-function quantizers (SFQ). We show that the structure of SFQs generally depend on the parameter value, but can be expressed as thresholds on the sufficient statistic for a large class of distributions. We provide a convergent iterative algorithm to obtain the best SFQ that maximizes the minimum ARE for distributions of that class. We compare the performance of the optimal SFQ with a general quantizer designed without making any restrictions on the structure. This general quantizer is hard to implement due to lack of structure, but is optimal if the iterative design algorithm does not encounter local minima. Through numerical simulations, we illustrate that the two quantizers designed are identical. In other words, the optimal quantizer structure is that of an SFQ. For a distributed estimation setup, designing identical quantizers is shown to be suboptimal. We, therefore, propose a joint multiple quantizer design algorithm based on a person-by-person optimization technique employing the SFQ structure. Using numerical examples, we illustrate the gain in performance due to designing nonidentical quantizers.

An iterative algorithm for optimal mould design in high-precision compression moulding

The mould design for the manufacturing of high-precision glass parts remains a challenging task. This motivates the present study which proposes an optimization technique to identify the mould design that yields the desired glass piece profile at the end of the compression moulding process with an accuracy of the order of 1 μm. The intuitive, yet very efficient method consists in computing at each optimization loop the mismatch between the deformed and desired glass piece geometries and using this information to update the mould design. The deformed glass piece geometry is computed using the commercial finite element package ABAQUS. This package is well suited to model the multistage forming process, the complex rheology of the glass, and the varying mechanical contact between the parts involved. The feasibility of the method is demonstrated in theory by designing the required mould for a convex-concave lens, where an accuracy of the order of 1 μm is achieved.

Design and Analysis of MIMO Spatial Multiplexing Systems With Quantized Feedback

This paper investigates the problem of transmit beamforming in multiple-antenna spatial multiplexing (SM) systems employing a finite-rate feedback channel. Assuming a fixed number of spatial channels and equal power allocation, we propose a new criterion for designing the codebook of beamforming matrices that is based on minimizing an approximation to the capacity loss resulting from the limited rate in the feedback channel. Using the criterion, we develop an iterative design algorithm that converges to a locally optimum codebook. Under the independent identically distributed channel and high signal-to-noise ratio (SNR) assumption, the effect on channel capacity of the finite-bit representation of the beamforming matrix is analyzed. Central to this analysis is the complex multivariate beta distribution and tractable approximations to the Voronoi regions associated with the code points. Furthermore, to compensate for the degradation due to the equal power allocation assumption, we propose a multimode SM transmission strategy wherein the number of data streams is determined based on the average SNR. This approach is shown to allow for effective utilization of the feedback bits resulting in a practical and efficient multiple-input multiple-output system design