A Novel Matching Technique for Microstrip Feeds usingOptimized Tapering

The establishment and development of Radio frequency (RF) and Microwave Engineering (ME) from its inception in Electrical and Electronics Engineering to having its own distinct identity in the 21st century has been explored in this paper. Overview of contributions by India to the field of RF and Microwave Engineering have been mentioned. Present paper deals with the field of RF and Microwave Engineering, especially the standard of its education in India. This paper explores the multidisciplinary nature of a RF and Microwave engineer and analyses how an RF and a Microwave engineer can contribute to the industry. Hierarchy and structure of Indian education system concerned with Engineering and Technology have been reviewed along with options and incentive available to aspiring researchers in the field of RF and Microwave Engineering. Nuances of dual degree program have been discussed. Job opportunities in government sector and private sector have been analyzed. A RF and Microwave engineer can find employment opportunities in premier government bodies such as Indian Space Research Organisation (ISRO) and Defence Research and Development Organisation (DRDO) along with private corporations in the rapidly growing telecom sector of India. Handheld device-based apps and web-based database programs initiated by the Government of India have been discussed. It has been concluded that RF and Microwave engineers will play a decisive role in the development of India. Performance of a RF and Microwave engineer will be a major factor in deciding the magnitude of performance of the Indian Defence Forces. The authors of this paper have suggested some steps to the Government of India which can help RF and Microwave Engineering education reach its maximum potential

An RNN-MCDA method to support efficient and stable matching under uncertain preferences in large-scale sharing platforms

Python is a powerful programming language for handling engineering and scientific computational tasks efficiently [1]-[5]. Used by companies such as Google and Intel and by organizations including NASA and Los Alamos National Laboratory, it offers an extremely wide selection of tools for tasks such as scientific computing, signal processing, Web site construction, database programming, and graphical user interface (GUI) design. The language is platform independent with most programs running on Linux, Microsoft Windows, or MAC OS virtually unchanged. Python has been distributed as a part of Open Source Initiative, and most versions are General Public License (GPL) compatible. In microwave and radio frequency (RF) engineering, it can be used for numerical programming, automated RF testing, automated monolithic microwave integrated-circuit (MMIC) layout generation, automated netlist generation and simulator sequencing, and other tasks. In this article, we are going to provide examples demonstrating the application areas of Python in microwave and RF engineering. We are also going to give a brief introduction to the language highlighting its salient features.

In all areas of electronics, impedance matching is a key aspect of the success of an electronic device. Thus, to further develop nanoelectronics and molecular electronics, it is highly important that the impedance of the wire matches the impedance of the CNT to minimize signal reflection and maximize power transfer. Thus, several considerations are needed for achieving matching, such as (1) The characteristic impedance of both the metallic and the CNT must be determined. (2) The complex conjugate matching to maximize power transfer, thus the impedance of the CNT should be the complex conjugate of the impedance of the metallic wire. (3) Frequency Considerations since impedance matching is often frequency dependent, the matching network must be designed to work effectively at the operating frequency of the system. This is particularly important for high-frequency applications where the impedance can vary significantly with frequency. (4) Use of Matching Networks, such as L-networks, pi-networks, or T-networks, can help achieving the desired impedance match. These networks typically consist of inductors and capacitors arranged to transform the impedance of the load (CNT) to match the source (metallic wire). (5) Intrinsic Material Properties, such as the conductivity of the metallic wire and the electronic properties of the CNT, play a crucial role. (6) Simulation and optimization are needed to model the impedance matching and to optimize the design before physical implementation.However, when dealing with impedance matching at the nanoscale (10 nm or less), where atomistic effects become significant, several modifications and additional considerations are necessary. (1) Characteristic Impedance: At the nanoscale, the characteristic impedance of both the metallic wire and the CNT must account for quantum effects and discrete energy levels. The impedance is no longer a simple bulk property but depends on the atomic structure and electronic states. Use quantum mechanical models to calculate the impedance, considering the specific atomic arrangements and electronic properties of the materials involved. (2) Complex Conjugate Matching: The concept of complex conjugate matching still applies, but the impedance values must be derived from atomistic simulations or quantum transport calculations rather than classical models, such that we are able to incorporate the effects of electron-phonon interactions and other quantum phenomena that can influence impedance at the atomic scale (3) Frequency Considerations: At the nanoscale, impedance matching must consider the discrete vibrational modes (phonons) and electronic transitions. The frequency response can be highly non-linear and dependent on the specific atomic configuration. Therefore, perform detailed frequency-dependent simulations to understand how impedance varies with frequency at the atomic level (4) Matching Networks: Traditional matching networks (L-networks, pi-networks) may not be feasible at the nanoscale due to the difficulty in fabricating inductors and capacitors at such small dimensions. Instead, we need to explore alternative matching techniques, such as using molecular junctions or engineered nanostructures that can provide the necessary impedance transformation (5) Material Properties: Material properties at the nanoscale can differ significantly from their bulk counterparts. For instance, surface effects, quantum confinement, and atomic-scale defects can all influence impedance. Therefore, atomistic simulations to accurately determine the material properties, including the effects of surface states and defects are needed. (6) Simulation and Optimization: Atomistic simulations, such as density functional theory (DFT) and ab initio molecular dynamics (AIMD), become essential tools for predicting impedance at the nanoscale. We need tocombine ab initio atomistic simulations with experimental results for a mutual validation to ensure the accuracy of the findings. This iterative approach can help refine the models and experiments, improving impedance matching. In addition, new criteria need to be aggregated: (7) Quantum Effects: Quantum tunneling, discrete energy levels, and electron coherence must be considered. These effects can significantly alter the impedance and must be included in the matching process. (8) Thermal Effects: At the nanoscale, thermal effects such as Joule heating and phonon scattering can impact impedance. These effects need to be modeled and mitigated to ensure stable impedance matching. By incorporating these modifications and additional criteria, impedance matching at the nanoscale can be effectively achieved, accounting for the unique challenges and phenomena present at this scale. We will be presenting our progress using ab initio molecular dynamics that have been adapted to address some of the above considerations. These include, among several others, connecting a few types of metallic and semiconducting CNT to metal wires of Cu and Au.

On the number of employed in the matching model

Recently, the growing advances in communication systems has led to urgent demand for low power, low cost, and highly integrated circuit topologies for transceiver designs, as key components of nearly every wireless application. Regarding to the usually weak input signal of such systems, the primary purpose of the wireless transceivers is consequently amplifying the signal without adding additional noise as much as possible. As a result, the performance of the low noise amplifier (LNA), measured in terms of features like gain, noise figure, dynamic range, return loss and stability, can highly determine the system’s achievement. Along with the evolution in wireless technologies, people get closer to the global seamless communication, which means people can unlimitedly communicates with each other under any circumstances. This achievement, as a result, paves the way for realizing wireless body area network (WBAN), the required applications for wireless sensor network, healthcare technology, and continuous health monitoring. This thesis suggests a number of LNA designs that can meet a wide range of requirements viz gain, noise figure, impedance matching, and power dissipation at 2.4Ghz frequency based on 0.13μm and 65nm CMOS technologies. This dissertation focused on the low power, high gain, CMOS reused current (CICR) LNA with noise optimization for on-body wireless body area networks (WBAN). A new design methodology is introduced for optimization of the LNA to attain gain and noise match concurrently. The designed LNA achieves a 28.5 dB gain, 2.4 dB noise figure, -18 dB impedance matching, while dissipating 1mW from a 1.2V power supply at 2.4 GHz frequency which is intended for WBAN applications. The tests and simulations of LNA are utilized in Cadence IC6.15 with IBM 130nm CMRF-8-SF library. The provided CICR LNA results inclusively prove the advantages of our design over other recorded structures. In the second step, a new linearization method is proposed based on Cascade LNA structure (CC-LNA). The proposed negative feedback intermodulation sink (NF-IMS) method benefits from the feedback to improve the linearity of CC-LNA. It proves that the additional negative feedback enhances the linearity of LNA despite the previous research. Furthermore, the heavily mathematical calculations of NF-IMS technique are carried on with the proposed modified Volterra series method. The NF-IMS method demonstrates more than 9.5dBm improvement in IIP3. Comparing to the previous techniques like: MDS and IMS, the improvement in the linearity aspect of the CC-LNA with is significant while it achieves a sufficient gain and noise performance of 16.7dB and 1.26db, respectively. Besides, the NF-IMS method presents a noise cancellation behavior as well. To increase the practical reliability of simulation, the real element model from TSMC 65nm CRN65GP library is applied. The CC-LNA that employed NF-IMS method is an excellent match with the market demands in WBAN’s gateway applications.

Recently, the growing advances in communication systems has led to urgent demand for low power, low cost, and highly integrated circuit topologies for transceiver designs, as key components of nearly every wireless application. Regarding to the usually weak input signal of such systems, the primary purpose of the wireless transceivers is consequently amplifying the signal without adding additional noise as much as possible. As a result, the performance of the low noise amplifier (LNA), measured in terms of features like gain, noise figure, dynamic range, return loss and stability, can highly determine the system’s achievement. Along with the evolution in wireless technologies, people get closer to the global seamless communication, which means people can unlimitedly communicates with each other under any circumstances. This achievement, as a result, paves the way for realizing wireless body area network (WBAN), the required applications for wireless sensor network, healthcare technology, and continuous health monitoring. This thesis suggests a number of LNA designs that can meet a wide range of requirements viz gain, noise figure, impedance matching, and power dissipation at 2.4Ghz frequency based on 0.13μm and 65nm CMOS technologies. This dissertation focused on the low power, high gain, CMOS reused current (CICR) LNA with noise optimization for on-body wireless body area networks (WBAN). A new design methodology is introduced for optimization of the LNA to attain gain and noise match concurrently. The designed LNA achieves a 28.5 dB gain, 2.4 dB noise figure, -18 dB impedance matching, while dissipating 1mW from a 1.2V power supply at 2.4 GHz frequency which is intended for WBAN applications. The tests and simulations of LNA are utilized in Cadence IC6.15 with IBM 130nm CMRF-8-SF library. The provided CICR LNA results inclusively prove the advantages of our design over other recorded structures. In the second step, a new linearization method is proposed based on Cascade LNA structure (CC-LNA). The proposed negative feedback intermodulation sink (NF-IMS) method benefits from the feedback to improve the linearity of CC-LNA. It proves that the additional negative feedback enhances the linearity of LNA despite the previous research. Furthermore, the heavily mathematical calculations of NF-IMS technique are carried on with the proposed modified Volterra series method. The NF-IMS method demonstrates more than 9.5dBm improvement in IIP3. Comparing to the previous techniques like: MDS and IMS, the improvement in the linearity aspect of the CC-LNA with is significant while it achieves a sufficient gain and noise performance of 16.7dB and 1.26db, respectively. Besides, the NF-IMS method presents a noise cancellation behavior as well. To increase the practical reliability of simulation, the real element model from TSMC 65nm CRN65GP library is applied. The CC-LNA that employed NF-IMS method is an excellent match with the market demands in WBAN’s gateway applications.

Recent advances in communication systems and the proliferation of plug-in electric vehicles (PEVs) hold a promise to support power systems operations with vehicle-togrid (V2G) applications. However, such ancillary services have tight communication requirements (low-latency, high reliability) as the aggregated PEVs need to respond to market signals within seconds and bad communication system performance lead to financial losses. In this paper, we consider a frequency regulation application in which PEVs are charged and discharged according to actual market signals. We assume that a market operator sends signals through 4G/LTE network to an aggregator located at a parking lot, who, as a next step, delivers data packets to electric vehicle supply equipments (EVSEs) via a local Wi-Fi network. In the final phase, each EVSE communicates with PEV battery management unit via power line communications. By adopting communication delay and packet loss profiles from measurement and simulation studies, we examine the impacts of communication system performance on V2G performance. The results show that packet losses significantly lowers precision score, while there is a need for faster networks if multiple aggregators participate at the same time.

The numerical approximation of Maxwell's equations, Computational Electromagnetics (CEM), has emerged as a crucial enabling technology for radio-frequency, microwave and wireless engineering. The three most popular 'full-wave' methods - the Finite Difference Time Domain Method, the Method of Moments and the Finite Element Method - are introduced in this book by way of one or two-dimensional problems. Commercial or public domain codes implementing these methods are then applied to complex, real-world engineering problems, and a careful analysis of the reliability of the results obtained is performed, along with a discussion of the many pitfalls which can result in inaccurate and misleading solutions. The book will empower readers to become discerning users of CEM software, with an understanding of the underlying methods, and confidence in the results obtained. It also introduces readers to the art of code development. Aimed at senior undergraduate/graduate students taking CEM courses and practising engineers in the industry.

The three main full-wave methods used in RF and microwave engineering - the Finite Difference The D* main (FDTD) method, the Method of Moments (MOM) and the Finite Element Method (FEW -are reviewed, and some key aspects of theoretical advances in these methods over the last decade are discussed. The impact of these developments, and the rapid improvement in computer technology, are seen as the core technology drivers for the widespread availability and adoption of commercial packages for industrial use. Some challenges which this brings are outlined.

Since last few years, there is a significant advancement in the field of RF and microwave engineering. This Paper proposes undergraduate course structure for effective classroom teaching and laboratory practices in RF and Microwave Engineering. Many Defense and Space research Organizations demand experts in RF and Communication Engineering for which many Universities provide Post graduation Degree into the field of Advanced Microwave Engineering, So this work propose a effective course structure at Undergraduate level to prepare students for the same.

In RF and Microwave Engineering course, usually students struggle to build connections between the theory they have learned and practical applications in the laboratory. The laboratory applications are usually very limited for hands on experience since the high cost and maintenance requirements of the equipment. Additionally, new engineers need to know how to use at least one engineering design tool in order to practice designing RF components, circuits, or antennas. In this study, a curriculum model including recent developments and technologies in the RF and Microwave Engineering field by addressing above problems of the course is proposed. This study covers the description of the content of theoretical and hands on applications, the integration model of the technological tools into the proposed curriculum, and the instructional approaches used in the new course design which covers the use of a remote laboratory environment, Concept Maps and an engineering design tool. The course is structured with a balance between theory and laboratory, including remote and in lab measurement experiments as well as modeling and designing microwave components by means of computer tools and design fabrication. The newly designed course is implemented at the Atilim University. The first semester implementation shows promising results.

This paper is concerned with the performance of a Communications system which utilizes frequency-hop spread spectrum, diversity transmission, Reed-Solomon coding, and parallel error-correction and erasure-correction decoding. Both binary signaling and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">M</tex> -ary orthogonal signaling are considered. The goals are twofold. First, it is desirable to provide good performance in partial-band Gaussian noise interference by use of coding and diversity with an efficient error-correction algorithm. Second, it is necessary to totally neutralize narrow-band interference (regardless of the power level or statistical distribution of the interference) in order to have an effective spread-spectrum system. Through an analysis of the effects of partial-band interference on a frequency-hop spread-spectrum system with diversity, it is shown that the use of ReedSolomon coding with a parallel errors and erasures decoding algorithm accomplishes these goals. The paper also investigates the accuracy of the Chernoff bound as an approximation to the true performance of a frequency-hop spreadspectrum communication system with diversity; side information, <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">M</tex> -ary orthogonal signaling, and Reed-Solomon coding. The performance results presented in the paper are based on analysis and computer evaluation. Approximate results based on the Chernoff bound are also given. It is shown that the Chernoff bound for <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">M</tex> -ary orthogonal signaling gives a very poor approximation for many cases of interest. This is largely due to the looseness of the union bound.

This paper considers the performance of a communication system which transmits for T seconds the real part of a sample function of one of M stationary complex Gaussian processes whose spectral densities are all frequency translations of the function S_{\xi (f) . At the receiver white Gaussian noise of one-sided density N_{0} is added. The center frequencies of the processes are assumed to be sufficiently separated that the M covariance functions are orthogonal over T . Exponently tight bounds are obtained for the error probability of the maximum likelihood receiver. It is shown that the error probability approaches zero exponentially with T for all rates R = (\ln M)/T up to C= \int_{-\infty}^{\infty} [S_{\xi (f)/N_{0}] df - \int_{- \infty}^{\infty} \ln [1 + S_{\xi}(f)/N_{0}] df which is shown to be the channel capacity. Similar results are obtained for the case of stochastic signals with specular components.

The most important numerical tools needed in the analysis of chaotic systems performing chaos synchronization and chaotic communications are discussed in this chapter. Basic concepts, theoretical framework, and computer algorithms are reviewed. The subjects covered include the concepts and numerical simulations of stochastic nonlinear systems, the complexity of a chaotic attractor measured by Lyapunov exponents and correlation dimension, the robustness of synchronization measured by the transverse Lyapunov exponents in parameter-matched systems and parameter-mismatched systems, the quality of synchronization measured by the correlation coefficient and the synchronization error, and the treatment of channel noise for quantifying the performance of a chaotic communication system. For a dynamical system described by stochastic differential equations, the integral of a stochastic term is very different from that of a deterministic term. The difference and connection between two different stochastic integrals in the Ito and Stratonovich senses, respectively, are discussed. Numerical algorithms for the simulation of stochastic differential equations are developed. Two quantitative measures, namely, the Lyapunov exponents and the correlation dimension, for a chaotic attractor are discussed. Numerical methods for calculating these parameters are outlined. The robustness of synchronization is measured by the transverse Lyapunov exponents. Because perfect parameter matching between a transmitter and a receiver is generally not possible in a real system, a new concept of measuring the robustness of synchronization by comparing the unperturbed and perturbed receiver attractors is introduced for a system with parameter mismatch. For the examination of the quality of synchronization, the correlation coefficient and the synchronization error obtained by comparing the transmitter and the receiver outputs are used. The performance of a communication system is commonly measured by the bit-error rate as a function of signal-to-noise ratio. In addition to the noise in the transmitter and the receiver, the noise of the communication channel has to be considered in evaluating the bit-error rate and signal-to-noise ratio of the system. An approach to integrating the linear and nonlinear effects of the channel noise into the system consistently is addressed. Optically injected single-mode semiconductor lasers are used as examples to demonstrate the use of these numerical tools.