Sunday, April 28, 2019

My Book "Practical Microstrip and Printed Antenna Design" is published now!!!

My Book "Practical Microstrip and Printed Antenna Design" is published now and available for sale. With all of the functionality now integrated into wireless devices, antenna design and development are taking more and more time. But a reliable design process with the right capabilities, like phased array beamforming, antenna beam shaping, can help you improve design throughput and reduce cost.

Review the fundamental specifications of practical microstrip and printed antennas design and see what capabilities you should consider getting the right technique for your design. 


Practical Microstrip and Printed Antenna Design
Practical Microstrip and Printed Antenna Design

Saturday, March 16, 2019


Practical Microstrip and Printed Antenna Design
Practical Microstrip and Printed Antenna Design Book Cover
My new book: “Practical Microstrip and Printed Antenna Design”, is all set to be released by end of this month (March 2019). The book covers the topic of microstrip antennas from roughly three vantage points: printed antenna fundamentals, antenna design technique, and design of real-world application-based antennas. This comprehensive resource presents antenna fundamentals balanced with the practical design of printed antennas. Microstrip and printed antennas are used in radars, aerospace systems, internet of things (IoT), satellite systems, 5G networks, MIMO, automobiles, and mobile phones. Supported with essential equations and illustrations, this practical book helps evaluate various design aspect of the antenna. Based on several years of my research in antenna design and development for RF and microwave applications, this book offers in-depth coverage of microstrip and printed antenna design methodology for modern applications. This book not only contains the crucial elements required to know to design printed antennas but also helps with the following:
  • Many practical designed antenna projects covered in book, which can be used for practice and real-world projects
  • Latest antenna technologies covering 5G, automobiles, GPS, RFID, Radar, Phased array and many other applications
  • Incorporates the various antenna design techniques used by industries and academia

Friday, February 22, 2019


Over the past few year, machine learning has attracted the attention of antenna engineers. Generally, the process of antenna design requires to find out the EM characteristics of antenna by observing the current distributions through simulations. These EM properties are then used for the parameters optimization. Machine learning (ML) can be combined with simulations to design an antenna. The inclusion of artificial intelligence (AI) can give promising results in the field of antenna designing. In recent years, antenna synthesis or design optimization through evolutionary algorithms (EAs) has been applied widely. At present, differential evolution (DE) and particle swarm optimization (PSO) are top two popular algorithms in the antenna synthesis area.
In smart antenna array, the objective of the gracefully degradation of the beamforming and beamsteering performance, can be achieved by reconfiguring the array when an element is found to be defective. This reconfiguration can be obtained by optimization using Machine learning and Support Vector Machines (SVM). SVMs are a set of supervised learning algorithms used for classification and regression problems. SVMs are a good candidate for the solution of antenna array processing problems such as beamforming and the angle of arrival estimation, because these algorithms provide superior performance in generalization ability and computational complexity. The basic idea is to change the excitation coefficient for each array element (magnitude and phase) to optimize for changes due to the environment surrounding an array antenna. Using Support Vector Machines, the antenna array is trained to change its elements phase or excitation distribution to maintain a certain radiation pattern or to enhance its beam steering and nulling properties and solve the DOA problem as well.
Optimization technique based SVMs algorithm is also used to match the measured far field radiation intensity to the corresponding antenna array structure. The SVM classifier is firstly trained by a set of input feature vectors extracted from measured radiation data of different array structures in various scenarios. Then, it is tested and the SVM parameters are adjusted during the learning process to help approach the optimal classification result. Then the trained SVM classifier is used to locate malfunctioning antenna elements of the array in real-time.
Machine learning based methods are used for calculating the radar cross section (RCS) of the antenna-radome system. In this method, the back-propagation algorithm can be used to train the machine learning model. The machine leaning based RCS calculation becomes a promising area, especially for the industrial sector with large amount of measurement data. Compared to traditional methods, machine learning methods have the potential to handle complex.
Machine learning techniques are also efficient in shaped-beam array designs. Here, SVM is applied for the characterization of the reflection coefficient matrix, which provides an efficient way for deriving the scattering parameters associated with the unit cell dimensions. ML is one of the most promising and salient research areas in artificial intelligence, as it has become a powerful tool in a wide range of antenna designs and related applications.

Genetic algorithm (GA)

Genetic algorithm (GA) is one of the global optimization algorithms that is used widely by antenna designers for the optimization of the antenna shape and size to achieve better overall performance of the antenna. GA has been used to enhance the performance of microstrip patch antennas by optimizing the bandwidth, multi-frequency, directivity, gain, size etc. The concept of the GA, first formalized by Holland and extended to functional optimization by De Jong, involves the use of optimization search strategies patterned after the Darwinian notion of natural selection and evolution.
During a GA optimization, the parameters of each individual of the population are encoded as a string of bits (chromosomes). The first group of individuals (generation) is created randomly. The fitness of each individual is determined by the cost function. Mating these individuals forms a new generation. The more fit individuals are selected and given greater chance of reproducing. Crossover and mutation are used to allow global exploration of the cost function. The best individual may be passed unchanged to the next generation. This iterative process creates successive generations until a stop criterion is reached. A block diagram of a genetic algorithm optimizer is shown here.

Sunday, April 22, 2018

Smartphone Antennas

A smartphone built on a mobile operating system, with more advanced computing capability connectivity than a feature phone. The smartphones combined the functions of a mobile phone, media players, low-end compact digital cameras, pocket video cameras, and GPS navigation, high-resolution touchscreens, and web browsers. With more operators announcing their LTE network coverage and plans, many smartphone manufacturers are switching to LTE based phones. Long Term Evolution (LTE) is a radio platform technology that will allow operators to achieve even higher peak throughputs than HSPA+ in higher spectrum bandwidth. The prime objective of LTE is to provide high data speed. A typical smartphone along with important electronics component is represented in Figure.

Sunday, December 3, 2017


RF/Microwave filters find wide application in communication systems, such as satellite links or wireless base stations. Microwave filters are passive devices employed to select a specific band of the frequency spectrum. Depending on the spectral region that is selected or rejected, they are classified in low-pass filters, high-pass filters, band-pass filters or band-stop filters. Passive devices at the output stage of the communication system must be able to deal with very high power signals. Because of that, waveguide technology is the ideal choice to implement these devices. This work presents the design of a different kind of waveguide-based filter.

Working Principle of Filter?

So, what is magic behind filter? How does it reject signals and pass others? In order to understand this, let us first go through the concept of mismatch. When there is perfect impedance match between the input impedance of system with output load impedance, maximum energy transferred from input to output otherwise there is always some energy loss. A measure of this transmission loss is the reflection coefficient and the related return loss. A frequency dependent mismatch exists in RF/uW devices, due to which signals at those frequencies where the mismatch exists will experience reflection caused by the mismatch. Extreme mismatches are caused by open and short circuits. Filters approach open or short circuit impedances in their stop bands – implying near total reflection. Passive non-resistive filters work by reflection caused by a mismatch condition introduced by the frequency dependent nature of the input impedance. In the bandpass filter (BPF), the resonators and the couplings are arranged in such a way, that the filter is transparent for passband signals. In the stop bands of the filter, the mismatch will cause reflection and thereby attenuation/rejection.

1. 8-Pole Interdigital Bandpass Filter

Interdigital filters are coupled-line structures to implement bandpass filter. The interdigital filter has compact size compared to other coupled line filter hence more popular.  Below figure shows one type of 8-pole waveguide based on the center frequency at 1.5 GHz. Each resonator element is a quarter-wavelength long at the mid-band frequency and is short-circuited at one end and open-circuited at the other end. Coupling is achieved by way of the fields fringing between adjacent resonator elements.
8-Pole Interdigital Bandpass Filter
In interdigital filter, the second passband is centered at three times the center frequent y of the first passband, and there is no possibility of spurious responses in between. The rates of cutoff and the strength of the stop bands are enhanced by multiple-order poles of attenuation at dc and at even multiples of the center frequency of the first passband.
8-Pole Interdigital Bandpass Filter Result
8-Pole Interdigital Bandpass Filter meshThe simulated frequency response of the filter determined using FEM solver is shows the variations of S-parameters with frequency for the  L-band interdigital BPF.  The unwanted harmonics are suppressed with stop band attenuation better than -14 dB everywhere. FEM mesh and simulated data is are shown in figures.
8-Pole Interdigital Bandpass Filter filed

2. Dielectric-filled Co-axial line Filter

Coaxial Dielectric filter filedThis is dielectric-filled coaxial cable low pass filter that is tuned with five annular rings (irises) that are added to the outer conductor wall in this design. To address the wideband frequency response with a fine frequency resolution, the model is simulated using fullwave 3D electromagnetic solver. The computed S-parameters show a low-pass frequency response with a cutoff frequency around 770 MHz.
coaxial line filter resultThis stepped-impedance low pass filter includes electrically conductive coaxial transmission line, at least one inductive element and at least one capacitive element. The capacitive elements and the inductive elements are disposed in an alternating manner along a length of the transmission line.
Coaxial Dielectric filter meshCoaxial Dielectric filter

3. Four-Resonator Comb Line Bandpass Filter

EM simulation is the key design tool for filter design and has reduced experimental comb Line Filterdesign work for distributed-element and waveguide resonator filters to a minimum or made it completely redundant. The EM simulation involves the calculation of the electromagnetic fields inside the filter structure. 3D EM simulation uses full wave analysis that is what actually exists in nature. 4-resonator combline filter fields at fc and port S-parameter response.
combline filter resultcombline filter filed
The design and dimensions of the model have been optimized to a point where great performance was significantly shown alongside with good matching around 535 MHz.

Sunday, September 10, 2017


The switching is required in many applications at low as well as at high frequency. RF MEMS switches are the specific micro mechanical switches that are designed to operate at RF to mm-wave frequencies. MEMS switches usages some mechanical movement to achieve a closed or open circuit in the Radio Frequency transmission lines. GaAs FET switches do not have sufficient isolations to minimize cross interference and signal jamming from channels is close proximity.  MEMS switches provide high isolation when open, low insertion loss when closed, and can be operated at low power consumption. Because of electromechanical isolation, RF circuit doesn’t leak or couple significantly to the actuation circuit. MEMS are small in size hence it occupies less space in circuit designs so that which was the most required device in the communicating world. Radio Frequency Micro Electro Mechanical Switches (RF MEMS) classification depends on the type of actuation, deflection axis, contact type, circuit configuration, and Structure configuration. The most used RF MEMS mechanical structures are the cantilever beam and the air bridge structures. The presented design here is electrostatically actuated capacitive fixed-to- fixed bridge base capacitive switch.
An air bridge base capacitive RF MEMS is shown here. Gold (Au) is used as a beam material, and Silicon Nitride (Si3N4) with dielectric constant 8.5 is used as a dielectric material. Silicon nitride thin film dielectrics are used in capacitive radio frequency micro-electromechanical systems (MEMS) switches since they provide a low insertion loss, good isolation, and low return loss. A capacitor is built up between the fixed electrode and movable electrode. Below are components of MEMS switch
  1. Wafer: This MEMS is fabricated on substrate as silicon, GaAs as active substrates
  2. Bridge: Gold (Au) is used as the membrane material.
  3. Dielectric: Silicon Dioxide(Sio2) is used as insulator
  4. Silicon as substrate
In air bridge type MEMS switch, the beam is fixed at both the ends and voltage is applied in the middle of the beam to note down the displacement of the beam towards the substrate. The displacement is maximum in the middle region when we go on increasing the applied voltage. The actuation voltage or applied voltage or pull in voltage is the maximum voltage at which the electrostatic force becomes superior over mechanical restoring force, causes MEMS device pull down towards the ground plane. Initially the input applied voltage is 1mv there is no deformation in the switch under this condition input is equal to output, but the second case, in addition, a 5v is added to 1mv then there is some electrostatic force is created between the electrodes then the cantilever will deform and touches to ground under this condition the output is zero. The switch closing time depends on the actuation voltage and the opening time depends on the mechanical properties of the switch.
off2.jpgThis RF MEMS Switch is designed and simulated using Finite Element Method (FEM) tool. Finite Element Method (FEM) tools are very helpful to design and simulate the RF MEMS Switch. S- Parameter results are obtained, and examine return loss (S11) and insertion loss (S12) of switches. During the OFF state, the insertion loss is less than zero and return loss is less than 40 dB. Vice versa output graph could be obtained during the ON state simulation of MEMS switches.
on2It is observed from the results that the MEMS switch circuit has an insertion loss (S21) of 0.4 dB and return loss (S11) of about less than 12 dB in the OFF state up to 20 GHz. The switch has an insertion loss (S21) of -25 dB and return loss (S11) of about -0.10 dB in the up state thus exhibiting good switch characteristics.
The simulated E-filed plot and FEM mesh are shown here.

Saturday, August 12, 2017

QFN Package Simulation

he Quad Flat No-lead (QFN) package is a CSP (plastic encapsulated package) with a copper lead frame substrate. QFN type package is one of the most cutting-edge IC packaging technologies in the electronics. The QFN is a leadless package where electrical contact to the PCB is made by soldering the leads on the bottom surface of the package to the PCB, instead of the conventional formed perimeter gull wing leads.
qfn1The QFN-type package is known for its small size, cost-effectiveness and good production yields. QFN also possess certain mechanical advantages for high-speed circuits including improved co-planarity and heat dissipation. The QFN has pins on 4 edges of the bottom surface of the package. The QFN can have either a square or rectangle body as well as symmetric or asymmetric terminal patterns. The QFN was introduced to replace the gull wing lead Quad Flat Package (QFP) because the component leads are embedded in the plastic and cannot be bent during handling to insure consistent assembly attachment.
qfn24×4 [mm] 16 Pin QFN
Design is shown below . This QFN package has 16 pin.  Metal thickness is 0.15 mm and  plastic encasement is 0.15 thick. Defining a substrate stack up  for QFN is pretty straightforward. The mold encapsulations are defined by dielectric bricks and the leads are defined by vias. The top side graphic shows the side view of package that is mounted on PCB. The bottom picture shows the details of leads, bondwires, and the chip, in this case, a thin film circuit.
QFN Electromagnetic simulation model and result
The input and output transmission lines on the PC board are connected to the package leads. On the top of die paddle, qfn3.jpga thin film circuit with a thru transmission line is attached to see the package performance. Double bonding with a compensated bond pads are used to improve the frequency performance here. With this typical interconnect scheme, the simulation results show that the package can be used up to qfn4.jpg15GHz when the required input and output return loss are around -20dB.
Package performance can be further improved by Increasing the width of input/output transmission lines to make 50ohm impedance  or use two lead frames instead of single to minimize the transitional impedance profile and split the double bonding to the two lead frames.