Hakan Bagci

A Multiplicative Calderon Preconditioner for the Electric Field Integral Equation

In this paper, a new technique for preconditioning electric field integral equations (EFIEs) by leveraging Calderon identities is presented. In contrast to all previous Calderon preconditioners, the proposed preconditioner is purely multiplicative in nature, applicable to open and closed structures, straightforward to implement, and easily interfaced with existing method of moments (MoM) code. Numerical results demonstrate that the MoM EFIE system obtained using the proposed preconditioning converges rapidly, independently of the discretization density.

An energy aware fuzzy approach to unequal clustering in wireless sensor networks

In order to gather information more efficiently in terms of energy consumption, wireless sensor networks (WSNs) are partitioned into clusters. In clustered WSNs, each sensor node sends its collected data to the head of the cluster that it belongs to. The cluster-heads are responsible for aggregating the collected data and forwarding it to the base station through other cluster-heads in the network. This leads to a situation known as the hot spots problem where cluster-heads that are closer to the base station tend to die earlier because of the heavy traffic they relay. In order to solve this problem, unequal clustering algorithms generate clusters of different sizes. In WSNs that are clustered with unequal clustering, the clusters close to the base station have smaller sizes than clusters far from the base station. In this paper, a fuzzy energy-aware unequal clustering algorithm (EAUCF), that addresses the hot spots problem, is introduced. EAUCF aims to decrease the intra-cluster work of the cluster-heads that are either close to the base station or have low remaining battery power. A fuzzy logic approach is adopted in order to handle uncertainties in cluster-head radius estimation. The proposed algorithm is compared with some popular clustering algorithms in the literature, namely Low Energy Adaptive Clustering Hierarchy, Cluster-Head Election Mechanism using Fuzzy Logic and Energy-Efficient Unequal Clustering. The experiment results show that EAUCF performs better than the other algorithms in terms of first node dies, half of the nodes alive and energy-efficiency metrics in all scenarios. Therefore, EAUCF is a stable and energy-efficient clustering algorithm to be utilized in any WSN application.

An ultra-broadband multilayered graphene absorber.

An ultra-broadband multilayered graphene absorber operating at terahertz (THz) frequencies is proposed. The absorber design makes use of three mechanisms: (i) The graphene layers are asymmetrically patterned to support higher order surface plasmon modes that destructively interfere with the dipolar mode and generate electromagnetically induced absorption. (ii) The patterned graphene layers biased at different gate voltages backed-up with dielectric substrates are stacked on top of each other. The resulting absorber is polarization dependent but has an ultra-broadband of operation. (iii) Graphenes damping factor is increased by lowering its electron mobility to 1000 cm²/Vs. Indeed, numerical experiments demonstrate that with only three layers, bandwidth of 90% absorption can be extended upto 7THz, which is drastically larger than only few THz of bandwidth that can be achieved with existing metallic/graphene absorbers.

An energy aware fuzzy unequal clustering algorithm for wireless sensor networks

In order to gather information more efficiently, wireless sensor networks (WSNs) are partitioned into clusters. The most of the proposed clustering algorithms do not consider the location of the base station. This situation causes hot spots problem in multi-hop WSNs. Unequal clustering mechanisms, which are designed by considering the base station location, solve this problem. In this paper, we introduce a fuzzy unequal clustering algorithm (EAUCF) which aims to prolong the lifetime of WSNs. EAUCF adjusts the cluster-head radius considering the residual energy and the distance to the base station parameters of the sensor nodes. This helps decreasing the intra-cluster work of the sensor nodes which are closer to the base station or have lower battery level. We utilize fuzzy logic for handling the uncertainties in cluster-head radius estimation. We compare our algorithm with some popular algorithms in literature, namely LEACH, CHEF and EEUC, according to First Node Dies (FND), Half of the Nodes Alive (HNA) and energy-efficiency metrics. Our simulation results show that EAUCF performs better than the other algorithms in most of the cases. Therefore, EAUCF is a stable and energy-efficient clustering algorithm to be utilized in any real time WSN application.

Fast and Rigorous Analysis of EMC/EMI Phenomena on Electrically Large and Complex Cable-Loaded Structures

A fast and comprehensive time-domain method for analyzing electromagnetic compatibility (EMC) and electromagnetic interference (EMI) phenomena on complex structures that involve electrically large platforms (e.g., vehicle shells) along with cable-interconnected antennas, shielding enclosures, and printed circuit boards is proposed. To efficiently simulate field interactions with such structures, three different solvers are hybridized: (1) a time-domain integral-equation (TDIE)-based field solver that computes fields on the exterior structure comprising platforms, antennas, enclosures, boards, and cable shields (external fields); (2) a modified nodal-analysis (MNA)-based circuit solver that computes currents and voltages on lumped circuits approximating cable connectors/loads; and (3) a TDIE-based transmission line solver that computes transmission line voltages and currents at cable terminations (guided fields). These three solvers are rigorously interfaced at the cable connectors/loads and along the cable shields; the resulting coupled system of equations is solved simultaneously at each time step. Computation of the external and guided fields, which constitutes the computational bottleneck of this approach, is accelerated using fast Fourier transform-based algorithms. Further acceleration is achieved by parallelizing the computation of external fields. The resulting hybrid solver permits the analysis of electrically large and geometrically intricate structures loaded with coaxial cables. The accuracy, efficiency, and versatility of the proposed solver are demonstrated by analyzing several EMC/EMI problems including interference between a log-periodic monopole array trailing an aircrafts wing and a monopole antenna mounted on its fuselage, coupling into coaxial cables connecting shielded printed circuit boards located inside a cockpit, and coupling into coaxial cables from a cell phone antenna located inside a fuselage.

A Fast Stroud-Based Collocation Method for Statistically Characterizing EMI/EMC Phenomena on Complex Platforms

A fast stochastic collocation method for statistically characterizing electromagnetic interference and compatibility (EMI/EMC) phenomena on electrically large and loaded platforms is presented. Uncertainties in electromagnetic excitations and/or system geometries and configurations are parameterized in terms of random variables having normal or beta probability density functions. A fast time-domain integral-equation-based field-cable-circuit simulator is used to perform deterministic EMI/EMC simulations for excitations and/or system geometries and configurations specified by Stroud integration rules. Outputs of these simulations then are processed to compute averages and standard deviations of pertinent observables. The proposed Stroud-based collocation method requires far fewer deterministic simulations than Monte Carlo or tensor-product integrators. To demonstrate the accuracy, efficiency, and practicality of the proposed method, it is used to statistically characterize coupled voltages at the feed pins of cable-interconnected and shielded computer cards as well as the terminals of cables situated inside the bay of an airplane cockpit.

An FFT-Accelerated FDTD Scheme with Exact Absorbing Conditions for Characterizing Axially Symmetric Resonant Structures

An accurate and e-cient flnite-difierence time-domain (FDTD) method for characterizing transient waves interactions on axially symmetric structures is presented. The method achieves its accuracy and e-ciency by employing localized and/or fast Fourier transform (FFT) accelerated exact absorbing conditions (EACs). The paper details the derivation of the EACs, discusses their implementation and discretization in an FDTD method, and proposes utilization of a blocked-FFT based algorithm for accelerating the computation of temporal convolutions present in nonlocal EACs. The proposed method allows transient analyses to be carried for long time intervals without any loss of accuracy and provides reliable numerical data pertinent to physical processes under resonant conditions. This renders the method highly useful in characterization of high-Q microwave radiators and energy compressors. Numerical results that demonstrate the accuracy and e-ciency of the method are presented.

A CalderÓn Multiplicative Preconditioner for the Combined Field Integral Equation

A Calderon multiplicative preconditioner (CMP) for the combined field integral equation (CFIE) is developed. Just like with previously proposed Calderon-preconditioned CFIEs, a localization procedure is employed to ensure that the equation is resonance-free. The iterative solution of the linear system of equations obtained via the CMP-based discretization of the CFIE converges rapidly regardless of the discretization density and the frequency of excitation.

MOFCA: Multi-objective fuzzy clustering algorithm for wireless sensor networks

Abstract This study introduces a new clustering approach which is not only energy-efficient but also distribution-independent for wireless sensor networks (WSNs). Clustering is used as a means of efficient data gathering technique in terms of energy consumption. In clustered networks, each node transmits acquired data to a cluster-head which the nodes belong to. After a cluster-head collects all the data from all member nodes, it transmits the data to the base station (sink) either in a compressed or uncompressed manner. This data transmission occurs via other cluster-heads in a multi-hop network environment. As a result of this situation, cluster-heads close to the sink tend to die earlier because of the heavy inter-cluster relay. This problem is named as the hotspots problem. To solve this problem, some unequal clustering approaches have already been introduced in the literature. Unequal clustering techniques generate clusters in smaller sizes when approaching the sink in order to decrease intra-cluster relay. In addition to the hotspots problem, the energy hole problem may also occur because of the changes in the node deployment locations. Although a number of previous studies have focused on energy-efficiency in clustering, to the best of our knowledge, none considers both problems in uniformly and non-uniformly distributed networks. Therefore, we propose a multi-objective solution for these problems. In this study, we introduce a multi-objective fuzzy clustering algorithm (MOFCA) that addresses both hotspots and energy hole problems in stationary and evolving networks. Performance analysis and evaluations are done with popular clustering algorithms and obtained experimental results show that MOFCA outperforms the existing algorithms in the same set up in terms of efficiency metrics, which are First Node Dies (FND), Half of the Nodes Alive (HNA), and Total Remaining Energy (TRE) used for estimating the lifetime of the WSNs and efficiency of protocols.

Fast solution of mixed-potential time-domain integral equations for half-space environments

A fast Fourier transform-accelerated integral-equation based algorithm to efficiently analyze transient scattering from planar perfect electrically conducting objects residing above or inside a potentially lossy dielectric half-space is presented. The algorithm requires O(N/sub t/N/sub s/(logN/sub s/+log/sup 2/N/sub t/)) CPU and O(N/sub t/N/sub s/) memory resources when analyzing electromagnetic wave interactions with uniformly meshed planar structures. Here, N/sub t/ and N/sub s/ are the numbers of simulation time steps and spatial unknowns, respectively. The proposed scheme is therefore far more efficient than classical time-marching solvers, the CPU and memory requirements of which scale as O(N/sub t//sup 2/N/sub s//sup 2/) and O(N/sub t/N/sub s//sup 2/). In the proposed scheme, all pertinent time-domain half-space Green functions are (pre) computed from their frequency-domain counterparts via inverse discrete Fourier transformation. In this process, in-band aliasing is avoided through the application of a smooth and interpolatory window. Numerical results demonstrate the accuracy and efficiency of the proposed algorithm.