Particle filtering based channel estimation in OFDM power line communication

Particle filtering （PF） algorithm has the powerful potential for coping with difficult non-linear and non-Gaussian problems. Aiming at non-linear, non-Gaussian and time-varying characteristics of power line channel, a time-varying channel estimation scheme combined PF algorithm with decision feedback method is proposed. In the proposed scheme, firstly the indoor power line channel is measured using the pseudo-noise （PN） correlation method, and a first-order dynamic autoregressive （AR） model is set up to describe the measured channel, then, the channel states are estimated dynamically from the received signals by exploiting the proposed scheme. Meanwhile, due to the complex noise distribution of power line channel, the performance of channel estimation based on the proposed scheme under the Middleton class A impulsive noise environment is analyzed. Comparisons are made with the channel estimation scheme respectively based on least square （LS）, Kalman filtering （KF） and the proposed algorithm. Simulation indicates that PF algorithm dealing with this power line channel estimation difficult non-linear and non-Gaussian problems performance is superior to those of LS and KF respectively, so the proposed scheme achieves higher estimation accuracy. Therefore, it is confirmed that PF algorithm has its own unique advantage for power line channel estimation.     

Compact arbitrary terminated power divider with bandwidth-enhanced negative group delay characteristics

A novel compact arbitrary terminated power divider with bandwidth-enhanced negative group delay (NGD) characteristics is proposed. The NGD characteristics are controlled by characteristic impedances of transmission lines and the coupled line between two output ports. Flat and wide NGD bandwidth is produced by using the combination of a series resistor and short-circuited coupled-line section. The complete closed-form equations are presented. For experimental demonstration, a prototype is designed and fabricated at f₀ of 2.14 GHz. The measured results indicate that the proposed power divider is able to realize wide NGD bandwidth and good NGD flatness.     

Balanced-evolution genetic algorithm for combinatorial optimization problems: the general outline and implementation of balanced-evolution strategy based on linear diversity index

How to rationally inject randomness to control population diversity is still a difficult problem in evolutionary algorithms. We propose balanced-evolution genetic algorithm (BEGA) as a case study of this problem. Similarity guide matrix (SGM) is a two-dimensional matrix to express the population (or subpopulation) distribution in coding space. Different from binary-coding similarity indexes, SGM is able to be suitable for binary-coding and symbol-coding problems, simultaneously. In BEGA, opposite-direction and forward-direction regions are defined by using two SGMs as reference points, respectively. In opposite-direction region, diversity subpopulation always tries to increase Hamming distances between themselves and the current population. In forward-direction region, intensification subpopulation always tries to decrease Hamming distances between themselves and the current elitism population. Thus, diversity subpopulation is more suitable for injecting randomness. Linear diversity index (LDI) measures the individual density around the center-point individual in coding space, which is characterized by itself linearity. According to LDI, we control the search-region ranges of diversity and intensification subpopulations by using negative and positive perturbations, respectively. Thus, the search efforts between exploration and exploitation are balanced. We compared BEGA with CHC, dual-population genetic algorithm, variable dissortative mating genetic algorithm, quantum-inspired evolutionary algorithm, and greedy genetic algorithm for 12 benchmarks. Experimental results were acceptable. In addition, it is worth noting that BEGA is able to directly solve bounded knapsack problem (i.e. symbol-coding problem) as one EA-based solver, and does not transform bounded knapsack problem into an equivalent binary knapsack problem.     

Impact of amplitude weights on power focusing for near‐field‐focused planar arrays

Near‐field‐focused (NFF) arrays have gained great interest owing to its ability to focus the electromagnetic power at a point near to the antenna. The power focusing can basically be reflected by the sidelobe level and the area of the ?3‐dB focal spot at the focal plane. For an ordinary NFF array with the given phase tapering, it would be an effective way to realize the changing of focused power by controlling the feeding‐current amplitude of the array element. In this article, the effects of the amplitude weights of array element rings on the power focusing with reference to an original NFF array are investigated to address this issue. The focus is on the power focusing changing introduced by amplitude weights changing of element rings, in which different cases of amplitude weights changing are considered. The results from amplitude weights changing are compared with that from an original amplitude weights combination, and compared among those from different cases of amplitude weights changing.     

Modeling of data acquisition systems using the queueing theory

This paper describes the features of a data acquisition system modeling based on queueing theory method. The main elements of the studied data acquisition system structure are sample hold amplifiers and dual-slope analogue digital converters. In case of the threshold control of technological facilities parameters, alarm signals in the system input are presented as a flow of customers with the Poisson intensity distribution. A converting time of these alarms in analogue digital converters depends on signal levels and is described by an exponential distribution. In this case we present the data acquisition system as the Markov model of the multichannel queueing system with a limited queue. This modeling method may help the data acquisition system structure to adapt to characteristics of input signals and features of communication lines in an output of system.     

A survey on fault diagnosis of analog circuits: Taxonomy and state of the art

Due to the wide range of applications of electronic circuits in the recent years, the fault diagnosis in electronic circuits is a foremost problem. The main purpose of the fault diagnosis technique is isolating the faults present in the electronic circuits and also, detecting the fault which affects the safety and performance of the system. For various real-time applications of fault diagnosis, literature presents several techniques for detecting the faults in electronic circuits. In this paper, reviews on the research based on the fault diagnosis techniques which are all gained much attention are comprehended. Accordingly, 114 research papers related to the fault diagnosis are reviewed and analyzed based on the various objectives. In this review, we present the taxonomy of the fault detection in analog circuits and discuss the state of the art algorithms with various advantages and major drawbacks. The comprehensive analysis is carried out on finding the coverage of the publishers, faults, circuits, methods, simulation tools, and metrics. This critical review finally discusses the research challenges that are still available in the existing techniques and the way to extend the current research is also examined.     

Current mode single-input multi-output MOSFET-only filter

In this paper, a very simple topology of a current mode MOSFET-only filter with single-input and multi-output is proposed. It is very important to emphasize that it is possible to obtain five of the filter functions, namely low-pass (LP), band-pass (BP), high-pass (HP), band-stop (BS) and all-pass (AP) using the proposed topology without using external passive elements. The core circuit of the proposed filter employs only four MOS transistors; therefore, it occupies very small chip area. It is also possible to adjust the filter gain with the biasing voltage. In addition, the circuit exhibits a very low input impedance and also high output impedances which make it possible for cascading. The MOSFET capacitances which determine the transfer functions are all grounded, so physical capacitances can be used instead of MOSFET parasitic capacitances to operate the filter at very low frequencies. Moreover, proposed filter structure has low supply voltage as 1 V in order to be applicable to low voltage operations. Detailed simulation results, including noise and Monte Carlo analysis, are provided using 0.18 µm TSMC technology parameters to verify the feasibility of the filter circuit.     

Smart antenna‐assisted spectrum sensing for robust detection in cognitive radio networks

In this paper, we consider the problem of multiband spectrum sensing by employing smart antenna arrays at the cognitive receiver. Although energy detection is widely used for spectrum sensing in cognitive radio networks because of its simplicity and accuracy, it is severely deteriorated by the noise uncertainty. This paper introduces robust spectrum sensing techniques to circumvent this difficulty, which operate simultaneously over the total frequency channels rather than a single channel each time. To enhance the detection performance, the proposed schemes jointly utilize the information of eigenvalues and eigenvectors, signal and noise subspace components in conjunction with the likelihood functions and Gerschgorin radii. Neither subjective decision threshold setting nor the estimation of noise power is required in our schemes, making them robust to noise uncertainty. Simulations are presented to validate the performance of the proposed schemes, and the results show that our schemes can outperform other existing spectrum sensing methods. Copyright © 2014 John Wiley & Sons, Ltd.     

Modeling of the Ostwald ripening of extrinsic defects and transient enhanced diffusion in silicon

We present an atomistic simulation of the Ostwald ripening of extrinsic defects (clusters, {1 1 3}s and dislocation loops) which occurs during annealing of ion implanted silicon. The model describes the capture and emission of Si interstitial atoms to and from extrinsic defects of sizes up to thousands of atoms and includes a loss term due to the flux of interstitials to the recombining surface. Key input parameters of the simulation are the variations of the formation energy and of the capture efficiency with the size of the different defects. This model shows that the kinetics of the well-known dissolution of {1 1 3} defects is only driven by the recombination efficiency at the surface and the distance from the defects to the sample surface. We have subsequently used this model to study defect evolution in low and ultra low energy (ULE) B implanted Si during annealing. Defect dissolution occurs earlier and at smaller sizes in the ULE regime. Consequently, TED is mostly characterized by its “pulse” component which occurs at the very beginning of the anneal.