Global optimization design of quasi-optics fower combiner of solid-state millimeter wave resonator

This paper describes a global optimization design of quasi-optics power combiner of solid-state millimeterwave resonator. It is operated in the frequency range from 50 to 300 GHz using GaAs Gunn diodes. It is shown that sourcearrays containing N² (N=3,5,...2K+1, where k is positive integer) individual elements. It is very efficient power transfer of energy from the source-array to the fractional power of the fundamental beam mode etc.. The RF output power exceeded the sum of the individual diodes to be threefold to sevenfold. And this data is the global optimization solution.     

New concedpts for high frequency and high power frequency multipliers and their impact on quasi-optical monolithic array design

Varactors have been extensively employed for harmonic generation, where high cut-off frequency is dependent upon small C _min , which is typically achieved using small device active area. However, small area limits the output power. Furthermore, the power and frequency dependences of the series resistance in the epitaxial region degrade the efficiency and cut-off frequency as well. As a result, currently utilized varactors are only officient for relatively low power generation and limited output frequency. Herein, we describe our new approach where by epitaxially stacking single quantum barrier structures, more than an order of magnitude improvement in cut-off frequency and power handling ability may be possible. Alternatively, by combining a Schottky barrier with stacked single quantum barriers, superior performance can also be achieved. These concepts can be readily employed for quasi-optical frequency multiplier arrays, and appear to result in simplified fabrication compared to other devices.The design of high performance quasi optical arrays requires optimization of the passive (metalization) grid as well as the embedded semiconductor devices. Recent work has resulted in an improved impedance model for the standard diode-loaded strip array, including a quantitative estimate of the shunt capacitance introduced across the diode by the discontinuity of the metal strip at the diode site (gap). The value of this capacitance exceeds the predictedC _min for these new devices. We discuss two grid design approaches that can suppress this capacitance.     

Ion flux's pressure dependence in an asymmetric capacitively coupled rf discharge in NF<Subscript>3</Subscript>

Starting from an analytical macroscopic/phenomenological model yielding the self-bias voltage as a function of the absorbed radio-frequency (rf) power of an asymmetric capacitively coupled discharge in NF₃ this paper studies the dependence of the ion flux onto the powered electrode on the gas pressure. An essential feature of the model is the assumption that the ions' drift velocity in the sheath near the powered electrode is proportional to E ^α, where E=−ΔU (U being the self-bias potential), and α is a coefficient depending on the gas pressure and cross section of elastic ion-neutral collisions. The model also considers the role of γ-electrons, stochastic heating as well as the contribution of the active electron current to the global discharge power balance. Numerically solving the model's basic equations one can extract the magnitude of the ion flux (at three different gas pressures) in a technological etching device (Alcatel GIR 220) by using easily measurable quantities, notably the self-bias voltage and absorbed rf power.     

A global optimization design for quasi-optics power combiner of 3mm wave solid-state sources

This paper describes a global optimization design for quasi-optics power combiner of solid-state millimeter-wave sources. The operating frequency is about 100 GHz and the oscillating sources are GaAs Gunn diodes. The source-array plane is a matrix consisting of NxN (N=3,5, ..., 2k+1, where k is positive integer) diodes. The radio frequency power of the combiner is from threefold to sevenfold larger than the sum total of the single diodes power. The global optimums of the array and the location in the cuvity of the suorce-array plane will be given by a global optimizition method.     

Mechanical characterization of hyperelastic materials with fringe projection and optimization techniques

This paper presents a new hybrid technique for mechanical characterization of hyperelastic materials. The research is motivated by the fact that standard identification procedures based on the fitting of strain–stress curves determined experimentally from planar biaxial tests may be inaccurate for non-uniform states of deformation. Therefore, we propose an alternative approach where the difference Ω between the displacement field measured with Projection Moiré and its counterpart predicted by FEM is minimized using non-linear optimization algorithms that finally find unknown material properties.In order to check the feasibility of the new procedure, we considered a thin latex membrane modelling it as a two-parameter Mooney–Rivlin (MR) hyperelastic material. The Ω function is minimized either using optimization routines available in a commercial finite element package and by implementing a global optimizer able to deal with non-linearity and non-convexity included in the identification process. In order to check accuracy of optimization results, target values of MR constants for the latex specimen tested have previously been determined by fitting experimental stress–strain data gathered from a standard planar biaxial tension test.Results indicate that the present hybrid identification procedure can determine accurately properties of the hyperelastic material under investigation. In fact, the average residual error on displacements was less than 1% while the difference between the MR constants found with optimization and their target values was less than 3.5%.     

Support Vector Driven Genetic Algorithm for the Design of Circular Polarized Microstrip Antenna

In this paper, a hybrid soft computing method for designing specific microstrip antenna is presented. Evolutionary algorithm such as genetic algorithm (GA) is one of the promising ways of finding global optimum solution from a multivariate nonlinear feature space. Being a stochastic iterative algorithm, it requires much computation power when the function to be optimized is complex and time consuming. Various meta-modelling techniques such as neural network, response surface methods, kriging, etc. can be used to model the process under optimization in order to reduce the computational expenses. In this paper, we investigate one such technique – support vector regression (SVR) – to model the complex analytical process. The model, thus obtained, is used for optimization using genetic algorithms. This approach is demonstrated for the design of circular polarized microstrip antenna at 2.6 GHz band. The results of SVR model are compared with other meta-models generated with neural network and response surface methodology.     

Experimental verification of the optimal tuning of a tunable vibration neutralizer for global vibration control

A theoretical method has been previously proposed by the authors to optimize a tunable vibration neutralizer for global vibration control. However, experimental verification of the tuning method has yet to be presented. This paper aims to do this. It is shown that by using the proposed optimization method, the tunable vibration neutralizer can be as effective as an active control device in reducing global vibration of a structure. One particularly interesting finding is that although the vibration neutralizer is a passive device which is incapable of supplying energy to a system, it appears to be as effective as active control in reducing the global vibration of a structure, even in the frequency range where the control device is required to supply energy.     

Adaptive extremal optimization by detrended fluctuation analysis

Global optimization is one of the key challenges in computational physics as several problems, e.g. protein structure prediction, the low-energy landscape of atomic clusters, detection of community structures in networks, or model-parameter fitting can be formulated as global optimization problems. Extremal optimization (EO) has become in recent years one particular, successful approach to the global optimization problem. As with almost all other global optimization approaches, EO is driven by an internal dynamics that depends crucially on one or more parameters. Recently, the existence of an optimal scheme for this internal parameter of EO was proven, so as to maximize the performance of the algorithm. However, this proof was not constructive, that is, one cannot use it to deduce the optimal parameter itself a priori. In this study we analyze the dynamics of EO for a test problem (spin glasses). Based on the results we propose an online measure of the performance of EO and a way to use this insight to reformulate the EO algorithm in order to construct optimal values of the internal parameter online without any input by the user. This approach will ultimately allow us to make EO parameter free and thus its application in general global optimization problems much more efficient.     

System throughput maximization in IRS-assisted phase cooperative NOMA networks

This work investigates performance of system throughput in intelligent reflecting surfaces (IRSs)-enabled phase cooperative non-orthogonal multiple access (NOMA) framework. By exploiting heterogeneous cognitive radio networks concept the aim is to maximize the sum rate of secondary users in the proposed phase cooperative downlink network configuration via optimization solutions. However, the optimization problem comes out to be NP-hard and precludes direct solution. Hence, an alternating optimization is applied at the primary network to solve the maximization problem by exploiting the transmit beamforming (BF) at the power station (PS) and phase shift optimization at the IRS. Later, sum rate maximization for secondary network is performed by utilizing phase shifts of primary network via phase cooperation. In order to find global optimal solutions for active beamformers at both PSs, a branch-reduce-and-bound (BRnB) method is used whereas, passive phase shift optimization at the primary PS is performed via a simple iterative solution, i.e., the element-wise block coordinate descent method. For the proposed framework, Monte-Carlo simulations are performed where the optimality of the global solution is compared with heuristic BF methods including minimum-mean-square-error/regularized zero-forcing-beamforming (ZFBF) and ZFBF. The BRnB algorithm sets an upper performance bound by improving the sum rate of users in comparison with the conventional heuristic BF schemes. This work signifies the utilization of phase cooperation in IRS-assisted NOMA networks for a multi-user environment.     

GA-based optimization of a MIMO ANC system considering coupling of secondary sources in a telephone kiosk

In this paper a multi-input, multi-output (MIMO) active noise control system with the aim of global reduction of broadband noise in a telephone kiosk is addressed. The model selected for this optimization problem is the acoustic environment of an enclosure taking into account the effect of coupling of secondary sources used for control purpose. This optimization involves finding the best locations for loudspeakers and microphones inside the enclosure as well as optimizing the control signals considering secondary source coupling.Previous results show that in order to be able to reduce acoustic noise globally inside the enclosure, the frequency range of 50-300 Hz must be selected for control purpose. The mean of acoustic potential energy of the enclosure, when excited in this frequency range, is adopted as a performance measure. This performance index is penalized with the power of the signal required to excite secondary loudspeakers, in order to avoid placements that may need high voltage power amplifier for a desired performance. To find the solution of this problem, i.e. the global minimum of the performance index, several genetic algorithms are proposed and compared. In order to attain the best achievable performance in reaching the global minimum, the parameters of these genetic algorithms are tuned, and used for optimization purpose. Numerical simulations of the acoustical potential energy as well as the sound pressure at different heights of the kiosk, when active noise control (ANC) system operates, confirm the optimality of the locations proposed by the genetic algorithm.     

Numerical study of local and global persistence in directed percolation

The local persistence probability P _l (t) that a site never becomes active up to time t, and the global persistence probability P _g (t) that the deviation of the global density from its mean value does not change its sign up to time t are studied in a (1+1)-dimensional directed percolation process by Monte-Carlo simulations. At criticality, starting from random initial conditions, P _l (t) decays algebraically with the exponent . The value is found to be independent of the initial density and the microscopic details of the dynamics, suggesting is an universal exponent. The global persistence exponent is found to be equal or larger than . This contrasts with previously known cases where . It is shown that in the special case of directed-bond percolation, P _l (t) can be related to a certain return probability of a directed percolation process with an active source (wet wall). Received: 15 December 1997 / Revised: 6 April 1998 / Accepted: 29 May 1998     

Multiple Diodes Quasi-Optical Oscillater

This paper presents quasi-optics techniques, millimeter techniques and a global optimization method etc techniques. It is a structure of quasi-optics power combiner, that includes a spherical reflection, that the radius of the curvature is R and another one is a hybrid reflector that is called input reflector. The space of the both reflectors is LL. The monolithic source-array is made up of 25 Gunn diodes that are mounted of parallel brass bars that have low thermal resistance. And the bars are fixed on the inner plane surface of the hybrid reflector. The hybrid reflector made up of a plane and a spherical, that the radius of the curvature are R. It is designed that higher fundamental mode power, larger fractional power of fundamental mode power and more combining efficiency of the quasi-optics power combiner.This paper describes an algorithm, which can determine the global optima of the power combiner of solid-state millimeter wave resonator. The global optimization method can determine a neighborhood of the global optima of an objective function and an estimation of the global optima. In the quasi-optical resonator, the objective functions are the fundamental mode power, the fractional power of fundamental mode and the combining efficiency respectively.     

无线携能通信系统中基于能量获取比例公平的波束成形设计

针对无线携能通信系统中存在能量获取不均衡的问题, 提出了一种基于能量获取比例公平的波束成形设计方案. 该方案在满足信息接收者的信干噪比以及发送端的最大发送功率等约束条件的基础上, 通过优化波束矢量实现能量获取的比例公平. 此设计在数学上是一个很难直接求解的非凸优化问题.为此, 本文首先利用半定松弛技术将其转换为半定规划问题, 然后结合二分法提出了可以获得最优波束矢量的迭代算法.此外, 在发送端仅知道部分信道状态信息且知道信道误差范围的情况下, 采用最差性能最优的方法对原优化问题进行了鲁棒波束成形设计, 并提出了相应的迭代算法. 仿真结果表明所提算法均可实现能量获取的比例公平且性能达到全局最优.     

Power efficiency of a semiconductor laser with an external cavity

Optical feedback modifies the power vs. current diagram of a laser diode as well as its spectrum. Though optimization of the spectral characteristics is usually the main goal in the design of an external cavity source, power efficiency is also important, especially with relatively high power devices, where temperature variations due to dissipation can have an impact on the wavelength stability and on the laser lifetime. A useful parameter to describe the total power efficiency of the stabilized laser, relative to that of the solitary laser, is proposed in this paper. The dependence of this parameter on the characteristics of the active device, and of the external cavity, is investigated.     

Scheduling and Power Control for Wireless Multicast Systems via Deep Reinforcement Learning

Multicasting in wireless systems is a natural way to exploit the redundancy in user requests in a content centric network. Power control and optimal scheduling can significantly improve the wireless multicast network’s performance under fading. However, the model-based approaches for power control and scheduling studied earlier are not scalable to large state spaces or changing system dynamics. In this paper, we use deep reinforcement learning, where we use function approximation of the Q-function via a deep neural network to obtain a power control policy that matches the optimal policy for a small network. We show that power control policy can be learned for reasonably large systems via this approach. Further, we use multi-timescale stochastic optimization to maintain the average power constraint. We demonstrate that a slight modification of the learning algorithm allows tracking of time varying system statistics. Finally, we extend the multi-time scale approach to simultaneously learn the optimal queuing strategy along with power control. We demonstrate the scalability, tracking and cross-layer optimization capabilities of our algorithms via simulations. The proposed multi-time scale approach can be used in general large state-space dynamical systems with multiple objectives and constraints, and may be of independent interest.     

A global optimization method for quasi-optics power combiner

This paper describes an algorithm which can determine a neighborhood of the global optimum of an objective function and an estimate of the global optimum.This method wasemployed to determine global optimum of the fundamental mode power, the fractional power of the fundamental mode and the combining efficiency. Given this information, a local optimization procedure can be employed to local the global optimum.Work supported by natural science fund of China.     

Effects of the Quenched Random Crystal Field on the Dynamic Spin-1 Blume-Capel Model

In this study, we have analyzed the dynamical phase transitions of spin-1 Blume-Capel model with quenched random crystal field under the effect of a time dependent oscillating magnetic field. We have obtained the magnetic field, temperature (h,T) cross sections of the global phase diagram for constant values of the concentration and the amplitude of the single-ion anisotropy within mean field approximation. There are regions of the phase space where both ordered and disordered phases coexist. In addition, the dynamic phase transition from one regime to the other can be a first- or a second-order depending on the region in the phase diagram. Hence, the system exhibits a number of interesting phenomena and a rich variety of phase diagrams with type being according to the concentration p of active local crystal fields.     

Energy-efficient beamforming optimization for MISO communication based on reconfigurable intelligent surface

Reconfigurable intelligent surface (RIS), a planar metasurface consisting of a large number of low-cost reflecting elements, has received much attention due to its ability to improve both the spectrum and energy efficiency (EE) by reconfiguring the wireless propagation environment. In this paper, we propose a base station (BS) beamforming and RIS phase shift optimization technique that maximizes the EE of a RIS-aided multiple-input–single-output system. In particular, considering the system circuits’ energy consumption, an EE maximization problem is formulated by jointly optimizing the active beamforming at the BS and the passive beamforming at the RIS, under the constraints of each user’ rate requirement, the BS’s maximal transmit power budget and unit-modulus constraint of the RIS phase shifts. Due to the coupling of optimization variables, this problem is a complex non-convex optimization problem, and it is challenging to solve it directly. To overcome this obstacle, we divide the problem into active and passive beamforming optimization subproblems. For the first subproblem, the active beamforming is given by the maximum ratio transmission optimal strategy. For the second subproblem, the optimal phase shift matrix at the RIS is obtained by exploiting sine cosine algorithm (SCA). Moreover, for this case where each reflection element’s working state is controlled by a circuit switch, each reflection element’s switch value is optimized with the aid of particle swarm optimization algorithm. Finally, numerical results verify the effectiveness of our proposed algorithm compared to other algorithms.     

Global optimization method in millimeter wave combiner

This paper describes an algorithm which can determine the global optima of the power combiner of solid-state millimeter wave resonator. The global optimization mehtod can determine a neighborhood of the global optima of an objective function and an estimation of the global optima. In this paper the objective function as follow: In the quasi-optical resonator, the objective function are the fundamental mode power, the fractional power of fundamental mode and the combining dfficiecy were done the objective functiona respectively, to calculate the global optima respectively. In the power combiner of solid-state millimeter wave source in rectangular waveguide cavity. the performance parameter are presentes by combining efficiency, tuning range, frequency drift, and FM noise were done the objective functions respectively. And to calculate the global optima respectively.     

Global Optimization CAD in MM Wave Waveguide Cavity

This paper describes a global optimization design for power combiner of solid-state millimeter wave source in rectangular wave- guide cavity. The algorithm can determine a neighborhood of the global optimum of an objective function. In this paper, the performance parameter are presents by combining efficiency, tuning range, frequency drift, and FM noise were done the objective functions respectively. And it is to calculate the global optima respectively.