Distributed Convex Optimization: A Study on the Primal-Dual Method of Multipliers

The Primal-Dual Method of Multipliers (PDMM) is a new algorithm that solves convex optimization problems in a distributed manner. This study focuses on the convergence behavior of the PDMM. For a deeper understanding, the PDMM algorithm was applied to distributed averaging and distributed dictionary learning problems. The results were compared...

Radar networks performance analysis and topology optimization

The ultimate goal of any sensing system is to build situation awareness. Existing<br/>solutions for a single radar node that have to assure extended areas of coverage with<br/>high resolution measurements (in range, cross-range, and Doppler) are physically<br/>cumbersome (large antenna size) and typically require large operational resources ...

Sparse sensing for composite matched subspace detection

In this paper, we propose sensor selection strategies, based on convex and greedy approaches, for designing sparse samplers for composite detection. Particularly, we focus our attention on sparse samplers for matched subspace detectors. Differently from previous works, that mostly rely on random matrices to perform compression of the sub...

Synthesis of Multiple Beam Linear Arrays with Uniform Amplitudes

A convex iterative algorithm for the synthesis of uniform amplitude, space-tapered linear phased arrays with simultaneous multiple beam optimization for 5G applications is presented. The performance of the algorithm is demonstrated by the synthesis of two arrays having 16 and 24 elements with 60 and 90 degree scan range, respectively. The effect...

Heat source layout optimization for two-dimensional heat conduction using iterative reweighted L1-norm convex minimization

Optimization of heat source distribution in two dimensional heat conduction for electronic cooling problem is considered. Convex optimization is applied to this problem for the first time by reformulating the objective function and the non-convex constraints. Mathematical analysis is performed to describe the heat source equation and the...

A Convex Approximation of the Relaxed Binaural Beamfomring Optimization Problem

The recently proposed relaxed binaural beamforming (RBB) optimization problem provides a flexible tradeoff between noise suppression and binaural-cue preservation of the sound sources in the acoustic scene. It minimizes the output noise power, under the constraints, which guarantee that the target remains unchanged after processing and the...

Synthesis of Multi-Beam Space-Tapered Linear Arrays with Side Lobe Level Minimization in the Presence of Mutual Coupling

An iterative convex element position optimization algorithm is proposed for linear phased array synthesis with the aim of minimizing the side lobe level at multiple scan angles in the presence of mutual coupling. Embedded element patterns are obtained via full-wave simulations and integrated into the optimization procedure. A two-step...

Multiple Beam Synthesis of Passively Cooled 5G Planar Arrays Using Convex Optimization

An extended-feature, system-driven convex algorithm for the synthesis of uniform-amplitude, irregular planar phased arrays with simultaneous multi-beam optimization for mm-wave 5G base station applications in multi-user scenarios is presented. The inter-user interferences are suppressed by minimizing the maximum sidelobe level (SLL) for a...

Relative Acoustic Transfer Function Estimation in Wireless Acoustic Sensor Networks

In this paper, we present an algorithm to estimate the relative acoustic transfer function (RTF) of a target source in wireless acoustic sensor networks (WASNs). Two well-known methods to estimate the RTF are the covariance subtraction (CS) method and the covariance whitening (CW) approach, the latter based on the generalized eigenvalue...

Fast Dynamic Programming: A Numerical Method for Solving Dynamic Programming Problems

A well-established method for finding the optimal control policy for a given dynamical system is to solve the problem iteratively going from its terminal state "backwards" in time, known as Dynamic Programming Algorithm. For a generic problem with discrete state/action space, the algorithm has computational complexity of <i>O(NM)</i> for <i>N</i...

Synthesis of Optimal 5G Array Layouts With Wide-Angle Scanning and Zooming Ability for Efficient Link Setup and High-QoS Communication

An irregular antenna synthesis technique with jointly optimized array subset layouts has been proposed for efficient beam setup and reliable communication in 5G. The proposed approach addresses both the electromagnetic and thermal challenges in 5G arrays by integrating zooming and wide-angle scanning functionality into interleaved-shared layout...

Sparse Signal Bands Selection for Precise Time-based Ranging in Terrestrial Positioning

Time-based ranging accuracy is inversely proportional to the signal bandwidth. A larger the signal bandwidth leads to a higher accuracy of time delay estimation, but more complex hardware is needed. Alternatively, we explore the idea of using multiple narrow signal bands (e.g., 10 MHz of each) to create a large virtual signal bandwidth, which...

Convex optimization-based Privacy-Preserving Distributed Least Squares via Subspace Perturbation

Over the past decades, privacy-preservation has received considerable attention, not only as a consequence of regulations such as the General Data Protection Regulation in the EU, but also from the fact that people are more concerned about data abuse as the world is becoming increasingly digitized. In this paper we propose a convex optimization...

Concentric Ring Array Synthesis for Low Side Lobes: An Overview and a Tool for Optimizing Ring Radii and Angle of Rotation

A comprehensive review on the approaches for synthesizing low side lobe concentric ring array (CRA) antennas is given. An Iterative Convex Optimization (ICO) based array layout synthesis technique is proposed for peak side-lobe level (PSLL) minimization over a given circular field-of-view in steerable uniform-amplitude concentric ring array (UA...

Robust Locomotion Exploiting Multiple Balance Strategies: An Observer-Based Cascaded Model Predictive Control Approach

Robust locomotion is a challenging task for humanoid robots, especially when considering dynamic disturbances. This article proposes a disturbance observer-based cascaded model predictive control (MPC) approach for bipedal locomotion, with the capability of exploiting ankle, stepping, hip and height variation strategies. Specifically, based...

Multiple Faults Estimation in Dynamical Systems: Tractable Design and Performance Bounds

In this article, we propose a tractable nonlinear fault estimation filter along with explicit performance bounds for a class of linear dynamical systems in the presence of both additive and nonlinear multiplicative faults. We consider the case, where both faults may occur simultaneously and through an identical dynamical relationship, a...

Distributed Optimisation Using Stochastic PDMM: Convergence, transmission losses and privacy

In recent years, the large increase in connected devices and the data that is collected by these devices has caused a heightened interest in distributed processing. Many practical distributed networks are of heterogeneous nature. Because of this, algorithms operating within these networks need to be simple, robust against network dynamics and...