Design and testing of a low-power 2.44 GHz oscillator for Wireless inter-body sensor networks

Design and testing of a low power 

2.44 GHz oscillator and of the related 

antenna, for Wireless inter‐body 

sensor networks

. 

Master’s Science Degree 

University of Pisa

Massimo Tenaglia 

UNIVERSITY OF PISA

Electronic Engineering

Master’s Degree in ELECTRONIC ENGINEERING

Design and testing of a low power 2.44 GHz

oscillator and of the related antenna, for

Wireless inter-body sensor networks

Candidate: Massimo Tenaglia 

1st. Supervisor: Prof. Massimo   Macucci

signature:_______________________

2nd. Supervisor: Prof. Bruno Neri

signature:________________________

3rd. Supervisor: Ing. Riccardo Massini

signature:________________________

Index

Introduction

This thesis work began at the University of Illinois Urbana-Champaign, in the Materials Research Laboratory under the supervision of Professor John A. Rogers.

Overall, the research aimed at creating a wireless transmitter able to ex-tract the needed power for operation through an RF-harvester, and whose signal was modulated by the value of a physiological parameter. The initial intention at the time was to transfer the entire system, consisting of an RF-scavenger, an oscillator and a TX-antenna, onto a flexible and biocompatible substrate, to make it suitable for a subsequent implantation in the human body.

In particular, the issue I was asked to address was to identify and analyze the possible causes of the non-operation of the previously realized circuit. This was probably the result of transferring the design from silicon to GaAs without any prior specific simulations.

In any case, the difference between the values of the same physical parame-ters in the two different semiconductors (Si and stretchable GaAs) had not been taken into account.

than those of semiconductors currently used by the industry.

This thesis was then completed at the Department of Electronic and Com-puter Engineering of the University of Pisa, under the supervision of Pro-fessor Massimo Macucci, obviously “mutatis mutandis”: the frequency band and the substrate.

Paying less attention to the implantability feature of the device, the present study focuses on the analysis and synthesis of a wireless transmitter in the 2.4-2.5 GHz ISM band, having as a main goal the low consumption of the entire system.

Indeed, the reduced power dissipation of modern circuits enables one to over-come the many difficulties related to limited battery life, that is critical espe-cially in long-term medical applications. Furthermore, in the case of a future implantable device, low power dissipation involves also reduced overheating of the surrounding body part.

The work of this thesis, presented below, can be divided into four key sections:

1) Oscillator analysis, simulation and synthesis 2) Antenna analysis, simulation and synthesis 3) Fabrication and testing

The analysis of the oscillator and its simulation were conducted by means of the Agilent electromagnetic simulator “Advanced Design System” (ADS). As far as the design of the transmitter and receiver antennas is concerned, a miniaturized version was studied, to better meet the portability require-ments, especially in a possible on-body or in-body medical application. For the antenna design the software CST MICROWAVE STUDIO was used in-stead of ADS. This software environment is more appropriate than ADS for that purpose.

Subsequently, the assembled oscillators were tested in order to check the actual correspondence of the measured parameters with the results of the simulations.

Finally, the behaviour of other material systems, such as conductive poly-mers and graphene was briefly analyzed, in order to evaluate the advantages for this particular application, in terms of a simulation performed with ADS.

Chapter 1

1.1

Introduction

A 1970s TV show named “The Six Million Dollar Man” was based on the story of a guy severely injured in a plane crash who was then “rebuilt” in a high-tech, clandestine medical procedure costing six million dollars. Back then it was practically all fiction, but today many of those “weird gadgets” and dreams have come true. Intelligent aids and prostheses such as cardiac and retinal implants, joint replacements, “bionic” limbs and so on, are readily available. Wireless communication links are of fundamental importance to enable the management of these wearable and implanted devices.

To come to the present day, everybody knows Alex Zanardi’s story, which is still making headlines after several years. In 2001 Alex Zanardi was involved in a terrible car accident during a race competition. It resulted in the amputation of his legs. Thanks to new-generation bionic limbs, doctors, engineers and physiotherapists aloowed him stand up again. He has only to use a special stick which not only serves to keep the balance, but also let him to “wirelessly motion control” himself. A wireless transmitter sends the control signals from the stick to a platform with an on-board Microcontroller Unit (MCU) that processes the signal giving in turn the right inputs to the motor driver.

The work of this thesis is an attempt to build and optimize a miniature circuit for wireless transfer of physiological signals from a sensor to a reader, aiming to minimize power consumption and heat dissipation in the body part. The proposed design focuses specifically on the “hardware level”, therefore no “signal conditioning issues” are addressed in this work. Previous-generation implanted-device interfaces were bulky, usually really power hungry and often lacked wireless capabilities.

In addition to the possibility of controlling remote devices and actuators for people with motor disabilities, very low-power transceivers are breaking barriers in the Healthcare world, making possible continuous remote moni-toring of long-term patients.

But why all these topics are of such great interest today? Who’s going to take advantage of these technical breakthroughs?

Currently the world is facing a situation without precedent: we soon will have more older people than children and more people at a extremely old age than ever before. As both the proportion of older people and the length of life increase throughout the world, it is expected that this increase will overload health care systems, significantly affecting the quality of life. Therefore a dramatic shift in current health care systems towards more af-fordable and scalable solutions is needed. On the other hand, millions of

people die from cancer, cardiovascular disease, Parkinson’s, asthma, obesity, diabetes and many more chronic or fatal diseases every year. The common problem with all current fatal diseases is that many people experience the symptoms and have the disease diagnosed when it is too late. Research has shown that most diseases can be prevented if they are detected in their early stages. Therefore, future health care systems should provide proactive wellness management and concentrate on early detection and prevention of diseases. One key solution to more affordable health care systems is through wearable monitoring systems capable of early detection of abnormal condi-tions resulting in major improvements in the quality of life. In this case, even monitoring vital signals such as the heart rate allows patients to engage in their normal activities instead of staying at home or close to a specialized medical service. This can only be achieved through a network consisting of in-telligent, low-power, micro and nanotechnology sensors and actuators, which can be placed on or implanted in the human body, providing timely data. Such networks are commonly referred to as Wireless Body Area Networks (WBANs). In addition to saving lives, prevalent use of WBANs will reduce health care costs by removing the need for costly in-hospital monitoring of patients [1].

Body area network (BAN) technology has emerged in recent years as a subcategory of wireless sensor network technology targeted at monitoring physiological and ambient conditions surrounding human beings and animals. However, BAN technology also introduces a number of challenges seldom seen before due to the scarcity of hardware and radio communication resources and the special properties of the radio environment under which they operate. In this chapter, the foundations of BANs along with the most relevant aspects relating to their design and deployment are presented. In addition state-of-the-art applications of BAN are described focusing on medical ones.

1.2.1

Characteristics of WBANs

Recent advances in Micro-Electro-Mechanical Systems (MEMS) tech-nology, integrated circuits, and wireless communication have allowed the re-alization of Wireless Body Area Networks (WBANs). They are widely used for ubiquitous healthcare, entertainment, and military applications.

A BAN consists of multiple interconnected nodes on, near, or within a hu-man body, which together provide sensing, processing, and communication capabilities [2]. A node in a BAN is defined as an independent device with communication capability. Nodes can be classified into three different groups based on their functionality, implementation and role in the network.

The classification of nodes in BANs based on functionality is as follows: Personal Device (PD) - This device is in charge of collecting all the informa-tion received from sensors and actuators and handles interacinforma-tion with other users. The PD then informs the user through an external gateway, a dis-play/LEDs on the device or an actuator. This device may also be called bodygateway, Body Control Unit (BCU) or PDA in some applications. Sensor - Sensors in BANs measure certain parameters in one’s body either internally or externally. These nodes gather and respond to data on a phys-ical stimuli, process necessary data and provide wireless response to infor-mation. These sensors are either physiological sensors, ambient sensors or biokinetics [3, 4]. Some existing types of these sensors could be used in one’s wrist watch, mobile phone, or earphone and consequently, allow wire-less monitoring of a person anywhere, anytime and with anybody. A list of different types of commercially available sensors used in BANs are as follows: Electromyography (EMG) , Electroencephalography (EEG), Electrocardiog-raphy (ECG), Temperature, Humidity, Blood pressure, Blood glucose, Pulse

Oximetry (SpO₂), CO₂ Gas sensor, Thermistor, Spirometer, Plethysmogram,

DNA Sensor, Magnetic Biosensor, Transmission Plasmon Biosensor,Motion (Gyroscope/Accelerometer/Tri-Axial Accelerometer), etc.

sensors. Its role is to provide feedback in the network by acting on sensor data, for example pumping the correct dose of medicine into the body in ubiquitous health care applications.

Based on the way the devices are implemented within the body, a node may be classified as follows:

Implant Node - This type of node is implanted in the human body, either immediately underneath the skin or inside the body tissue.

Body Surface Node - This type of node is either placed on the surface of the human body or 2 centimeters away from it.

External Node - This type of node is not in contact with the human body and a few centimeters to 5 meters away from the human body.

The classification of nodes in BANs based on their role in the network is as follows:

Coordinator - The coordinator node is like a gateway to the outside world, another WBAN, a trust center or an access coordinator. The coordinator of a BAN is the PDA, through which all other nodes communicate.

End Nodes - The end nodes in BANs are limited to performing their embed-ded application. However, they are not capable of relaying messages from other nodes.

possess a child node and relay messages. In essence if a node is at an ex-tremity (e.g. a foot), any data sent is required to be relayed by other nodes before reaching the PDA. The relay nodes may also be capable of sensing data [1].

A body sensor node mainly consists of two parts: the

sen-sor(s)/actuator(s) and the radio platform, to which multiple body sensors can be connected. The general functionality of body sensors is to collect analog signals that correspond to human’s physiological activities or body actions. Such an analog signal can be acquired by the corresponding radio-equipped board in a wired fashion, where the analog signal is digitized. Finally, the digital signal is forwarded by the radio transceiver. This eliminates the need for wires to communicate with the coordinator node and transfer the collected data. The coordinator node is something like a server pc: it functions either as a gateway to transfer data to an external electronic healthcare (e-Health) monitoring system or as a self-contained hub for local monitoring and con-trol. As a matter of fact, some companies have recently introduced wireless Micro Controller Units (MCUs) to the open market. These newer devices are single-chip hardware solutions that provide a microcontroller and a radio transceiver in a single package requiring only a few external components.

Basically, sensor devices operate by preloading MCUs with program codes that access low-level hardware interfaces, which in turn obtain data from the actual sensor devices. Programs contain the necessary instructions for sensor devices to collect one or more readings in a particular time period. Raw sensor data can subsequently be processed in order to convert them to meaningful information that can be interpreted after transmission by the radio chip to an external device or system for further analysis. Moreover, two or more sensor devices in the vicinity of each other can establish wireless links in order to coordinate their joint operations, thus creating a networked system. Therefore, the existing literature often refers to BANs as wireless BAN (WBAN) or wireless body area sensor network (WBASN).

Figure 1 shows a typical sensor node with sensor, radio and memory modules. The sensor module consists of a sensor, a filter and an Analog-to-Digital Converter (ADC). The sensor converts some form of energy to analog electric signals, which are bandpass-filtered and digitized by the ADC for further processing [5].

Figure 2 illustrates the placement of WBAN nodes on a person.

An example is NASA’s attempt of developing a wearable physiological monitoring system for astronauts called LifeGuard system. IEEE 802.15.6 aims to provide low-power in-body and on-body wireless communication

Fig. 1.1 Typical modules on a sensor node (from [5])

Fig. 1.2 Placement of WBAN nodes (from [6])

work-ing towards a seven layers solution for wireless communication in WBAN. In-body sensor networks, especially, allow communication between implanted devices and remote monitoring equipments. They are capable of collecting information for instance from Implantable Cardioverter Defibrillators (ICDs) in order to detect and treat ventricular tachyarrhythmia and to prevent Sud-den Cardiac Death (SCD). A system architecture presented in [7] performs real-time analysis of sensor data, provides real-time feedback to the user, and forwards the user’s information to a telemedicine server [8].

Therefore, WBANs are an important step ahead in telemedicine, namely the use of telecommunication and information technologies in order to provide clinical health care at a distance. It helps eliminate distance barriers and can improve access to medical services that would often not be consistently available in distant rural communities. It is also used to save lives in critical care and emergency situations.

Although there were distant precursors to telemedicine, it is essentially a product of 20th century telecommunication and information technologies. These technologies permit communications between patient and medical staff with both convenience and fidelity, as well as the transmission of medical, imaging and health data from one site to another.

Early forms of telemedicine achieved with telephone and radio have been supplemented with videotelephony, advanced diagnostic methods supported by distributed client/server applications, and additionally with telemedical devices to support in-home care. Telemedicine can be intended at both pa-tient level and hospital-management level, and may consists of:

- Wireless telemetry of information from implanted circuitry WITHIN the body TO circuitry outside the body

- Wireless telemetry of programming parameters from outside the body to implanted circuitry within the body

- Wireless power source or battery recharging for some kind of implanted circuitry [6].

1.2.2

Channel model

Nodes in WBANs are scattered in and over the whole body, which creates multiple transmission channels between the nodes based on their location in/on the body. The channel models proposed by IEEE 802.15.6 SGBAN are shown in Table 1.1.

The scenarios are established based on the distance of the communi-cation nodes, which are on the body surface, implanted and external; and grouped in classes represented by the Channel Model (CM). External devices are considered to reach a maximum distance of up to 5 meters. In scenarios

Table 1.1 Scenarios and description of channel models in IEEE 802.15.

S1,S2 and S3 in cases where a hundred sensors are attached to a person’s body, the system becomes quite bulky to be carried around. Thus, the USA Federal Communications Commission (FCC) and communication authorities of other countries have allocated the MICS band at 402-405 MHz with 300 KHz channels to enable wireless communication with implanted medical de-vices. This leads to better penetration through the human tissue compared to higher frequencies, high level of mobility, comfort and better patient care in implant to implant (S1), implant to body surface (S2) and implant to exter-nal (S3) scenarios. Additioexter-nally, the 402-405 MHz frequencies have conducive propagation characteristics for the transmission of radio signals in the human body and do not cause severe interference for other radio operations in the same band. In fact, the MICS band is an unlicensed, ultra-low power, mo-bile radio service for transmitting data to support therapeutic or diagnostic operation related to implant medical devices and is internationally available.

Table 1.2 List of frequency bands for IEEE 802.15.6

It is specifically chosen to provide low-power, small size, fast data transfer as well as a long communication range. The frequency range of the MICS band allows high-level integration with the radio frequency IC (RFIC) technology, which leads to miniaturization and low power consumption. In summary, high level integration is difficult at lower frequencies, and higher frequencies cause severe penetration loss (10 dB for 10 mm tissue penetration) [9]. Table 2 provides a list of different frequency bands based on which WBAN channel model can be adopted [10]. Another important approach is to differentiate electromagnetic wave propagation from devices in or around the body. How-ever, due to the complex structure of the body shape and human tissue, a simple path loss model cannot be easily modeled for WBANs. Moreover, as the node antenna is either placed in or on the body, the influence of the body on radio propagation also needs to be considered [10].

A WBAN INFRASTRUCTURE consists of in-body and on-body nodes that continuously monitor the patient’s vital information for diagnosis and prescription. A WBAN uses Wireless Medical Telemetry Services (WMTS), unlicensed Industrial, Scientific, and Medical (ISM), Ultra-wideband (UWB), and Medical Implant Communications Service (MICS) bands for data trans-mission. WMTS is a licensed band used for medical telemetry systems. The federal Communication Commission (FCC) urges the use of WMTS for med-ical applications due to fewer interfering sources.

The alternative spectrum for medical applications is the 2.4 GHz ISM band that includes guard bands to protect from adjacent channel interfer-ence. A licensed MICS band (402-405 MHz) is dedicated to the implant communications.

Fig. 3 shows a WBAN infrastructure for medical and non-medical ap-plications. As can be seen in the figure, the WBAN traffic is categorized into On-demand, Emergency, and Normal traffic. The wakeup circuit is used to accommodate on-demand and emergency traffic. The coordinator is further connected to telemedicine, game, and medical servers for relevant recommen-dations [8].

Fig. 1.3A WBAN infrastructure for medical and non-medical applications (from [8])

Why is issue of Low Power so important in circuit design?

con-stantly decreasing in size over the recent years. Most of us routinely carry or wear electronics every day. While VLSI (Very Large Scale Integration) tech-nology has enjoyed the rapid exponential growth characterized by Moore’s Law, energy storage technology (mainly batteries) has developed much more slowly.

That is why very low-power electronic systems, namely devices able to operate with little amount of input power, are of great technological interest. The growing research activity in the field of low power electronics is due to its several applications [6].

As all BAN nodes require an energy source for data collection, process-ing and transmission, development of suitable power supplies becomes of paramount importance. One solution to this problem is energy harvesting, e.g. based on body movements or temperature difference. Another solution recently reported is to utilize a wireless energy transmission over the short range, i.e., several meters, using evanescent waves. Both approaches require appropriate energy conversion and storage devices.

A wireless recharging circuit could exploit both an inductively-coupled power link and an RF-coupled link.

Inductively-coupled power links are often used in medical implants, Radio-Frequency IDentification (RFID) tags, and smart cards. Alternating

current through a large, external coil creates a magnetic field. The portable device has a small pickup coil that turns the magnetic field back into direct electric Current. Basically a transformer with a small secondary coil and a rectifier. To this end, in medical implants an externally-powered coil is placed on or near the skin. The internal coil in the implant can power elec-tronics directly (e.g., muscle stimulators) or recharge internal batteries (e.g., pacemaker).

RF-coupled Links are made possible by “rectennas”.

A rectenna is a rectifying antenna, a special type of antenna that is used to convert microwave energy into direct electric current. Rectennas are used in wireless power transmission systems that transmit power by radio waves. A simple rectenna element consists of a dipole antenna with an RF diode connected across the dipole elements. The diode rectifies the AC current induced in the antenna by the microwaves, to produce DC power, which is supplied to a load connected across the diode. Schottky diodes are usually adopted because they have the lowest voltage drop and highest speed and therefore the lowest power losses due to conduction and switching. Large rectennas consist of an array of many such dipole elements.

In recent years interest has turned to using rectennas as power sources for small wireless microelectronic devices. The largest current use of rectennas

is in RFID tags, proximity cards and contactless smart cards, which contain an Integrated Circuit (IC) powered by a small rectenna element. When the device is brought near an electronic reader unit, radio waves from the reader are received by the rectenna, powering up the IC, which transmits its data back to the reader. Obviously, the back transmission would occur at a different frequency in order to avoid any interferences. In fact, when dealing with ultra-low-power wireless telemetry circuits, noise and interferences can not be neglected.

Even though it might be not clear, the use of RF technologies in medicine stems from the cellular phone market and from the digital camera market. Many companies are using RF to establish their versions of a BAN. Bluetooth is being touted as the most likely solution. Most of the applications to date seem to involve syncing up your cellular phone or PDA with a computer. RF, using Bluetooth, has the largest range of any of the technologies. It is almost a mini-LAN. On the downside, RF applications operating at very busy frequency bands (such as 2400 MHz), are more expensive and have higher power consumption than other solutions.

All of the technologies have pros and cons associated with them. At the end of the day, the solution that wins will be the solution that the buying public will use the most. Although RF takes a relatively large amount of power, it

provides a large range and high data transfer rate. No doubt the market is making this feature desirable more and more [11].

From the user point of view a BAN can be defined as a one-to-many and many-to-one, non-wired connections between a user (one) and multiple devices (many) that are “nearby” in space. The term “nearby” is taken to mean within about 10 meters or less. The basic idea is that they have to be restricted to short range interactions.

BANs in the literature seem to be divided into two ranges: intra-body and inter-body. The first concern trasmissions under 1 meter while the second refers to ranges up to 10 meters. This work focuses on a transmitter de-signed for the inter-bodyBANs. In the near future, people may be carrying a number of electronic devices including a cell phone, pager, PDA, an en-tertainment device such as a MP3 player or Walkman, perhaps a notebook computer and of course a watch. Some of them may be coordinated so that a user does not have to manually transfer a phone number from a PDA to a cell phone for example. The reader can easily imagine what that means in terms of weight, power, memory, cost and user’s time. In fact, devices that automatically recognize the presence of each other on a user body and share data as needed could provide a less complicated interface for the user.

Of course if devices such as these can be networked, there are possible ap-plications for other devices as well. A miniature camera and a microphone embedded in a pair of glasses could record names and faces at a large meeting and download the data to a PDA located, for example in a shoe, for later retrieval to create an electronic Rolodex file of contacts. Limiting the signals to the user body has obvious advantages in security and privacy [12].

“Short range communication” is a very desirable feature, that makes a good trade-off between the technology and the related privacy issue possible. In recent years, privacy concerns have taken on a more significant role in so-cieties all over the world. Merchants, insurance companies and government agencies amass warehouses containing personal data.

The short-range feature represents that one more reason which should defi-nitely cast out any fears about the data theft possibility. As a matter of fact, the main concern is that big companies might “sell one’s mother” in order to amass huge data warehouse for free, in totally defiance of rules. These data ware-houses are gold to them, as hey enable data mining on them.

When you shake hands with a similarly equipped person, your PDAs auto-matically exchange business cards. Of course if your PDA can “recognize” a person that you have met before, it can provide you with data you have col-lected about that person. As you shake hands with a previous contact, your

PDA could cue you, through a tiny earpiece, with the business affiliation of the other person, as well as relevant personal information. Similar concepts could provide a patient’s medical information to doctors.

In some applications, users will want to communicate to nearby objects with-out needing to touch them. Simple examples already exist today. Wireless headsets can connect a user to phones within a few feet without the need to handle the phone.

One imaginative application that has been proposed consists of a PDA that broadcasts a short-range signal containing a person’s dating preferences and monitors broadcasts from other PDAs. When two users with compatible datasets come within a few feet of each other, each user is cued. This may be the ultimate mixer idea for parties. The distance of the desired links will define the range of the desired connection. In some cases, links of around 1 meter will be sufficient and perhaps desirable because of security and privacy issues. Thus there are likely to be applications for short ranges around 1 me-ter and longer ranges around 10 meme-ters. These applications can be thought of as bubbles surrounding a user that provide a particular message, dataset or connectivity link depending on the desire of the user [11].

BAN-based monitoring applications normally involve both raw sensing and pre-processing of physiological signals. BAN-based control applications

are thought to work as Human-Computer Interfaces (HCI). After a sensor node has acquired a number of parameter readings, these are subsequently fed and forwarded to another subsystem for interpretation. In turn, all the outputs that control a device or a process are mapped.

BANs facilitate ambulatory health monitoring by functioning as proxies to medical practitioners in order to conveniently obtain continuous updates of the physiological readings from remote users.

As a consequence, clinics and/or hospitals may become less overwhelmed by the sheer number of patients that otherwise have to have their regular check-ups onsite. Moreover, BANs enable the deployment of automated eHealth systems for diagnostic, alarm and emergency response, while streamlining the provision of emergency services.

Added to this is the automated management of electronic patient record databases integrated into a single eHealth system. Nonetheless, a number of legal, ethical, and technical issues remain to be investigated, the latter of which is a matter of intense, state-of-the-art research.

A good example of an ambulatory system for health monitoring is the Wear-able Health Monitoring System (WHMS) developed by researchers at the University of Alabama. This investigation focuses on a large-scale system for ambulatory, health-status monitoring and telemedicine. WHMS employs

traditional WiFi wireless local area network (WLAN) technology and cellular networks to forward data from BANs to an external system, and facilitates data visualization and collection by using diverse types of devices, such as personal computers and smart phones.

Medical practitioners can access patient data via the Internet, which also serves to issue alerts when a health-related anomaly is detected.

Hospital environments can also benefit from the deployment of BANs, as exemplified by the CodeBlue project at Harvard University. CodeBlue targets hospital environments that can host several router nodes employing ZigBee radio technology. Their proposed system allows BAN users to con-nect to this network, whereby servers store all pertinent information in a database for on-demand dissemination.

The Disaster Aid Network (AID-N) is a system developed at Johns Hop-kins University, which targets medical condition monitoring for emergency responders during mass casualty events. Similar to WHMS, AID-N employs WiFi and cellular networks to establish communications between personal, smart phone-based servers and the system database servers. In addition to this, the system employs a web portal to facilitate the interactions among first-responders.

A BAN can be employed as an alternative input method to traditional com-puter interfaces (e.g., keyboards, joysticks, etc.) to control a device or a process according to the readings from inertial motion sensors. To this end, BAN sensor devices capture and digitize human motion and gestures for im-mediate interpretation.

Applications ranging from custom communication interfaces for disabled people and entertainment/gaming experience enhancements can be imple-mented.

BANs can be employed in a variety of ways to assist people with distinct handicaps. To this end, so-called intra-body communication applications enable spatiotemporal navigation, text display in eyeglasses and closed-captioned audio broadcasts by embedding a variety of sensor types to dif-ferent items worn by users. On the other hand, the MITHril project at the Massachusetts Institute of Technology employs sensors that read physio-logical signals (e.g., electrocardiography, skin temperature, galvanic skin re-sponse) in a wearable computing scheme that interacts with WiFi and smart phones to enable intelligent context-awareness in the user’s living space. European investigators have also developed state-of-the-art platforms based on wearable sensor technology. For instance, the Microsystems Platform for Mobile Services and Applications (MIMOSA) project is a large research

initiative that also promotes advances in ambient intelligence using BANs in conjunction with smart phones. Furthermore, European advancements in this area also take place at the embedded device level (e.g., Bluetooth Low Energy technology). In another effort, a group of researchers in Ital-ian universities has produced the Wireless Sensor Node for a Motion Capture system with Accelerometers (WiMoCA), which implements a distributed ges-ture recognition system [6].

1.2.4

Antenna design

One major challenge for antenna design in WBANs is related to alter-ations in the antenna topology based on the shape of the human body, which specifies the need for flexible and textile antennas. However, these types of antennas are not easily adjustable to body dynamics, as they are mainly built on top of substrates with little deformation capability [13]. One other major challenge is due to the electromagnetic interaction between the human body and the antenna. The human body is considered as a large inhomogeneous object with high loss and permittivity, which affects the properties of an antenna being placed in its close proximity. Additionally, the surrounding environment of an antenna must be accurately considered. Antenna design in BAN environments is also affected by the user’s posture, weight loss/gain, and even his/her aging. Also the limitations of shape, size, material and

the intrinsic environment need to be taken into account. In addition, the location of an antenna in the body has major control on the size and shape of the antenna being used, therefore restricting the designer. Moreover, the variation of characteristics of skin tissue, muscle and fat in response to the heating effects of the electric field should also be considered when designing WBAN antennas. Applicable antennas types for WBANs can be generally classified into two groups:

1) Magnetic antennas: Magnetic antennas, such as loop antennas, generate an E-field that is mostly tangential to the body tissue and, therefore are not capable of coupling as strongly as the electric antennas. Consequently, body fat does not heat up. Some antennas that are partially similar to the magnetic ones are the helical-coil antennas, which have the same heating characteristics as the electrical antennas. Tissue heating is mainly a result of the strong Electric Field (E-field) existing between the coils. Additionally, the Specific Absorption Rate (SAR) of the far field transmitting antenna is mainly related to the E-field, whereas the SAR of near field transmitting antennas is related to the Magnetic Field (H-field).

2) Electric antennas: Electric antennas such as dipole antennas generate a large E-field perpendicular to the body that is absorbed and increases the temperature of the human tissue. This is because the boundary requirement

Fig. 1.4

of the E-field is discontinuous by the ratio of its permittivities at the E-field. Since muscle has higher permittivity than fat, the E-field of the fat tissue is generally higher.

The human body is not considered as an ideal medium for electromag-netic wave transmission at radio frequencies. Muscle and fat have different

characteristic impedances Z(Ω), conductivities ρ and dielectric constants ǫr

that are shown in the diagram of Fig. 1.4.

Consequently, based on the utilized frequency, high path loss occurs in the human body due to central frequency shift, power absorption and al-terations in the radiation pattern. Additionally, absorption effects differ in magnitude based on the characteristics of the tissue and the frequency of the applied field [14].

In general, propagation throughout the body is affected in numerous ways due to the electrical properties of the body, which are as follows:

(1) Body tissue is semi-conductive and therefore capable of absorbing some of the signal.

(2) Body tissue can react as a parasitic radiator.

(3) The electrical length of electric field antennas such as dipoles increase as the dielectric constant increases.

The antennas designed for WBANs are classified into two groups based on their location to be either placed on the body or in the body.

In-body Antenna Design - Since these antennas are implanted in the body, only specific types of materials such as titanium or platinum, can be used due to their bio-compatible and non-corrosive chemistry, whilst a copper antenna has better performance [5]. The MICS band which is from 402-405 MHz is allocated for in-body communication. The wavelength of this frequency is 744 mm and the half wave dipole is 372 mm. However, an antenna with such dimensions is not applicable to in-body operation and therefore these constraints lead to a much smaller size than the optimum.

On-body Antenna Desig - Two key requirements for on-body communication of antennas are the antenna radiation pattern and the sensitivity of anten-nas to the human body. In [61], a comparison of antenna combinations for

on-body communication is provided. Various antennas have been designed and constructed in the 2.5 GHz and ISM band, such as loop antennas, patch antennas, patch array antennas and monopole antennas. Amongst which, the monopole and monopole combinations provide the least link loss and the highest path gain (path gain is defined as the product of all transfer functions along a path). Whereas, patch antennas that do not require additional space are capable of reducing the spread of the path gain and therefore eliminating multi-path fading [15].

A. Dipole Antenna

For a dipole of length 10 mm, at 403 MHz, the radiation resistance is 45 m in air. The electrical length of the dipole is increased when surrounded by a material of high dielectric constant such as the body.

B. Loop Antenna

For a loop of 10 mm diameter the area is 78.5 mm2_{. This gives a radiation}

resistance of 626 Ohm. However, the loop acts as a magnetic dipole, produc-ing more magnetic field than a dipole. The loop is of use within the body as the magnetic field is less affected by the body tissue compared to a dipole or a patch and it can be readily integrated into existing structures.

C. Patch Antenna

Fig. 1.5 Patch antenna plan view,λ in the surrounding medium (from [8])

requiring much additional volume, the ideal patch will have dimensions as given in Fig. 5. It acts as a λ/2 parallel plate transmission line with an impedance inversely proportional to the width. The radiation occurs at the edges of the patch as shown in Fig. 6. For in-body use, a full size patch is not an option. However, as it is immersed into the body tissue that has a dielectric constant in the order of 50, the electrical size of the patch becomes larger than would be in air.

D. Impedance Measurement

The impedance of the patch and dipole is affected considerably by being surrounded by the body tissue. The doctor who fits it determines the position of an implant within a body. It may move within the body after fitting. Each body has a different shape with different proportions of fat and muscle that may change with time. This means that a definitive measurement of

Fig. 1.6Patch antenna side view (from [8])

antenna impedance is of little value. Measuring it immersed in a body model can yield an approximation of the impedance. Using this impedance, the antenna-matching network can be designed with the provision of software controlled trimming, that can be done with variable capacitors integrated into the transceiver.

1.2.5

WBANs applications

WBAN applications span a wide area such as military, ubiquitous health care, sport, entertainment and many other areas. IEEE 802.15.6 categorizes WBAN applications into medical and non-medical (Consumer Electronics) as can be seen in Table 3.

Medical applications

WBANs have a huge potential to revolutionize the future of health care monitoring by diagnosing many life threatening diseases and providing real

Table 1.3Applications of WBANs

time patient monitoring. Using WBANs in medical applications allows for continuous monitoring of physiological attributes such as blood pressure, heart beat and body temperature. In cases where abnormal conditions are detected, data being collected by the sensors can be sent to a gateway such as a cell phone. The gateway then delivers its data via a cellular network or the Internet to a remote location such as an emergency center or a doctor’s room based on which an action can be taken [16, 17]. Additionally, WBANs will be a key solution in early diagnosis, monitoring and treatment of patients with possibly fatal diseases of many types, including diabetes, hypertension and cardiovascular related diseases. Medical applications of WBANs can be further classified into three subcategories as follows:

1. Wearable WBAN. Wearable medical applications of WBANs can further be classified into the following two subcategories: a) Disability

Assis-tance, b) Human Performance Management. Some of these applications are:

- Sport training - The training schedules of athletes/soldiers can eas-ily be tuned via WBANs as they provide monitoring parameters, motion capture and rehabilitation. Moreover, the real-time feed-back provided to the user in these networks allows for performance improvement and prevents injuries related to incorrect training. - Wearable Health Monitoring - WBANs in conjunction with sensors

and other devices on the human body can provide real time health monitoring. For instance, a Gluecocellphone which is a cell phone with a glucose module can be used for patients with diabetes. The cellphone receives glucose diagnoses from the glucose module which may then be stored or sent to a doctor for analysis [18].

2. Implant WBAN. This class of applications is relative to nodes implanted in the human body either underneath the skin or in the blood stream. Frequent monitoring provided by WBAN can be used for diabetes con-trol or cardiovascular disease prevention.

3. Remote control of medical devices. The ubiquitous Internet connectiv-ity of WBANs allows for networking of the devices and services in home

care known as Ambient Assisted Living (AAL), where each WBAN wire-lessly communicates with a back-end medical network [19]. AAL aims to prolong the self-conducted care of patients that are assisted in their home, minimizing the dependency on intensive personal care, increasing quality of life and decreasing society costs.

- Patient Monitoring - One key application of WBANs is its use in monitoring vital signals, as well as providing real time feedback and information on the recovery process in health monitoring applica-tions. More specifically, they sense and wirelessly transmit vital sig-nal measurements such as heart rate, body temperature, respiration rate, blood pressure, body implant parameters and chest sounds. WBANs are also capable of administration of drugs in hospitals, remote monitoring of human physiological data, aid rehabilitation and provide an interface for diagnostics.

- Telemedicine Systems - Available telemedicine systems either use a power demanding protocol like Bluetooth, which is open to in-terference from other devices working in a similar frequency, or dedicated wireless channels for transferring information to remote stations. Therefore, they restrict prolonged monitoring. Whereas

integrating WBANs in a telemedicine system allows for long periods of unobtrusive ambulatory health monitoring.

Non-medical Applications

Some examples of non-medical applications of WBANs are:

- Interactive gaming: Body sensors enable game players to perform actual body movements, such as boxing and shooting, that can be fed back to the corresponding gaming console, thereby enhancing their entertain-ment experiences.

- Personal information sharing: Private or business information can be stored in body sensors for many daily life applications such as shopping and information exchange.

- Secure authentication: This application involves resorting to both phys-iological and behavioral biometrics schemes, such as facial patterns, fin-ger prints and iris recognition. The potential problems, e.g., proneness to forgery and duplicability, however, have motivated the investigations into new physical/behavioral characteristics of the human body, e.g., Electroencephalography (EEG) and gait, and multimodal biometric sys-tems [1].

BIBLIOGRAPHY

[1] S. Movassaghi, M. Abolhasan, et al.: “Wireless Body Area Networks: A Survey”, IEEE Communications surveys and tutorials (2014).

[2] S. Park and S. Jayaraman: “Enhancing the Quality of Life through

Wearable Technology”. IEEE Engineering in Medicine and Biology

Magazine, vol. 22 (3), pp. 41-48 (2003).

[3] B. Latr´e, B. Braem, et al.: “A survey on wireless body area networks”, Wireless Network, vol. 17, pp. 1-18 (2011).

[4] M. Hanson, H. Powell, et al.: “Body area sensor networks: Challenges and opportunities”, Computer, vol. 42, pp. 58-65 (2009).

[5] M. Chen, S. Gonzalez, et al.: “Body Area Networks: A Survey”, Mobile Netw. Appl., vol. 16, pp. 171-193 (2011).

[6] S. Gonzalez-Valenzuela, X. Liang, et al.: “Body Area Networks”, in D. Filippini (ed.), “Autonomous Sensor Networks: Collective Sensing Strategies for Analytical Purposes”, Springer Series on Chemical Sensors and Biosensors, vol. 13, pp. 17-38 (2013).

[7] E. Jovanov, A. Milenkovic, et al.: “A wireless body area network of intelligent motion sensors for computer assisted physical rehabilitation”,

Journal of Neuro Engineering and Rehabilitation, Vol. 2, art. no. 6 (2005).

[8] S. Ullah, P. Khan, et al.: “A Review of Wireless Body Area Networks for Medical Applications”, International J. of Communications, Network and System Sciences, vol. 2 (8), pp. 797-803 (2009).

[9] A. Saeed, M. Faezipour, et al.: “Plug-and-play sensor node for body area networks”, in Proceedings of the IEEE-NIH life science systems and applications workshop, pp. 104-107 (2009).

[10] S. Jiang, Y. Cao, et al.: “CareNet: an integrated wireless sensor net-working environment for remote healthcare”, in Proc. of international conference on body area networks (2008).

[11] H. Conn and B. Nerenberg: “Personal Area Networks - A Review of

the Technology and Possible Applications”,

http://faculty.washington.edu/sandeep/future/PAN.doc [12] KDD, http://www.thearling.com/text/dsstar/privacy.html

[13] A. Arriola, J. Sancho, et al.: “Stretchable dipole antenna for body area networks at 2.45 GHz”, IET Microwaves, antennas & propagation, vol. 15, p. 852-859 (2011).

[14] K. Y. Yazdandoost and K. Sayrafian-Pour: “Channel model for body area network (BAN)”, Report of the IEEE802.15.6 channel model-ing subcommittee (2009), https://mentor.ieee.org/802.15/dcn/08/15-08-0780-09-0006-tg6-channel-model.pdf

[15] Z. Hu, M. Gallo et al.: “Measurements and simulations for on-body antenna design and propagation studies”, in 2nd European Conf. on Antennas and Propagation (EuCAP), pp. 1-7 (2007).

[16] J. Xing and Y. Zhu: “A survey on body area network”, in 5th Int. Conf. on Wireless Communications, Networking and Mobile Computing (WiCom ’09), pp. 1-4 (2009).

[17] Y. Pei and B. Wang: “Body area networks”, in “Encyclopedia of Wire-less and Mobile Communications”, edited by Borko Furht, Taylor and Francis (2007).

[18] D. Lewis, “802.15.6 call for applications in body area networks - response summary” (2008),

http://nicta.com.au/ data/assets/pdf file/0006/17997/15-08-0407-05-0006-tg6-applications-summary.pdf

[19] M. Lipprandt, M. Eichelberg, et al.: “Osami-d: an open service platform for healthcare monitoring applications”, in 2nd Conf. on Human System Interactions, pp. 139-145, IEEE (2009)

Chapter 2

This thesis work began at the Material Science Lab, at the “University of Illinois of Urbana-Champaign” during an internship I had been granted by the University of Pisa.

At that time the issue to address was to import an existing RF design onto a stretchable substrate, in order to make it implantable into the human body. The colleague I was working with contact was then considering an RF cir-cuit borrowed from the “BAE Systems” company. BAE stands for “British Aerospace Engineering” and is a British multinational defence, security and aerospace company headquartered in London, and with operations and branches worldwide.

The design target was the realization of an “RF-Powered” and “implantable” “general purpose” oscillator for the interbody-2GHz communication of a mea-sured physiological parameter.

To this end, an extra MEMS-sensing part and an RF-scavenger had to be added to the transmitter, but the work focused on improving the power-efficiency of the oscillator and the quality of the “class C output signal” as much as possible.

Fig. 2.1

1) A “Scavenge Rectifier” and 2) An “Oscillator” with a built-in “Antenna” In Fig. 2.1 the first two blocks are briefly outlined. The system consists of two functional parts: a module that scavenges RF power from the environment (left) and a component that transmits a continuous RF signal, using power from the scavenger (right).

3) A parameter-sensing part, the output of which modulates the oscil-lator signal. MEMS sensor elements mostly based on a silicon structure, would in this case be combined with a low-power analog amplifier on the same micro-chip, to form the Bio-Sensor.

As a matter of fact, wireless BASN can include a number of physiologi-cal sensors depending on the end-user application. Information from several sensors can be combined to generate new information such as total energy expenditure. An extensive set of physiological sensors may include the fol-lowing:

- An ECG (electrocardiogram) sensor for monitoring heart activity - An EMG (electromyography) sensor for monitoring muscle activity - An EEG (electroencephalography) sensor for monitoring brain electrical

activity

- A blood pressure sensor

- A tilt sensor for monitoring trunk position - A breathing sensor for monitoring respiration

- movement sensors used to estimate the user’s activity

- A “smart sock” sensor or a sensor equipped shoe insole used to delineate phases of individual steps

However, as it was previously stated, the present thesis is not going to deal with the MEMS-sensor topic, that is taken for granted. Also the RF-scavenger design is not part of this work, though its design should require less effort.

In its turn, the RF part has been divided into two different design steps: the “Oscillator design” and the “Antenna” design.

Let me begin with a short introduction on what oscillators are.

Wave generators play a prominent role in the field of electronics. They generate signals from a few hertz to several gigahertz. Modern wave gener-ators use many different circuits and generate such sinusoidal, square,

rect-angular, sawtooth, and trapezoidal outputs. One type of wave generator is known as an OSCILLATOR. An oscillator can be regarded as an ampli-fier which provides its own input signal. Oscillators are classified according to the waveshapes they produce and the requirements needed for them to produce oscillations. An oscillator can be thought of as an amplifier that provides itself (through feedback) with an input signal. By definition, it is a non-rotating device for producing alternating current, the output frequency of which is determined by the characteristics of the device. The primary purpose of an oscillator is to generate a given waveform at a constant peak amplitude and specific frequency and to maintain this waveform within cer-tain limits of amplitude and frequency.

An oscillator must provide amplification. Amplification of signal power oc-curs from input to output.

In an oscillator, a portion of the output is fed back to sustain the input, as shown in Fig. 2.2. Enough power must be fed back to the input circuit for the oscillator to drive itself. To cause the oscillator to be self-driven, the feedback signal must also be regenerative (positive).

In phase with the input signal that has produced it, feedback signal must have enough power to compensate for circuit losses and to maintain oscillations.

Fig. 2.2

Since a practical oscillator must oscillate at a predetermined frequency, a determining device (fdd), sometimes referred to as a frequency-determining network (fdn), is needed. This device acts as a filter, allowing only the desired frequency to pass.

Without a frequency-determining device, the stage will oscillate in a random manner, and a constant frequency will not be maintained.

The basic oscillator requirements, in addition to the application, determine the type of oscillator to be used. In any case there are two essential stability requirements, the amplitude and frequency stability of the output waveform. A constant frequency and amplitude can be achieved by taking extreme care to prevent variations in load, bias, and component characteristics.

As far as biasing is concerned, bias variations affect the operating point of the transistor. These variations may alter the amplification characteristics of the oscillator circuits as well.

A well-regulated power supply and a bias-stabilizing circuit are required to ensure a constant, uniform signal output. To this end, a π-filter was designed and placed between the DC power supply (cold node) and the oscillator RF-node (hot RF-node). Without a π-filter, simulations showed RF leakage into the power supply.

As a result of changing temperature and humidity conditions, the value or characteristics of components such as capacitors, resistors, and transistors can change. Such changes cause changes in amplitude and frequency.

The output power is another consideration in the use of oscillators. Generally speaking, high power is obtained with some sacrifice of stability. When both requirements are to be met, a low-power, stable oscillator can be followed by a higher-power buffer amplifier. The buffer provides isolation between the oscillator and the load to prevent changes in the load from affecting the oscillator. In applicatios such as the ones we have discussed efficienty reptesents a very important issue to address. That is why many oscillators use “class C bias” to increase efficiency, even though it means sacrificing linearity.

Other types of oscillators may use class A bias when a high efficiency is not required, but distortion must be kept at a minimum. Other classes of bias may also be used with certain oscillators.

Fig. 2.3

It would now be appropriate to consider a few aspects of the feedback theory. Feedback is the process of transferring energy from a down stream point in a system to an upstream point in the same system. In many cases, it means transferring energy from the output of an amplifier back to its in-put. If the output feedback signal opposes the input signal, the feedback is degenerative or negative. However, if the feedback aids the input signal, the feedback is “regenerative” or “positive”.

Regenerative/positive feedback is one of the requirements to sustain oscilla-tions in an oscillator. This feedback can be applied in several ways to produce a practical oscillator circuit.

2.1

Types of Feedback

The first method to transfer energy, as previously said, is to take some of the energy from the inductor. This can be done in any one of the three ways shown in the panels (A), (B), and (C) of Fig. 2.3.

When an oscillator uses a tickler coil, as shown in view (A), it is re-ferred to as an Armstrong oscillator. When an oscillator uses a “tapped coil” (view (B)) or a split coil (view (C)), it is referred to as a HARTLEY OSCILLATOR. The second method of coupling the feedback signal is to use two capacitors in the tank circuit and tap the feedback signal from the node between them. This is shown in figure (D). An oscillator using this method is referred to as a “Colpitts Oscillator”. Each of these particular oscillators is named after the person who originally designed it.

The design considered in this thesis is a Common Drain version of the Col-pitts oscillator. The transistor used is a HEMT GaAs FET. The circuit considered at the beginning was one taken from a BAE Systems design. Basically, there was a problem, a big one: no oscillation occurred in the oscillator fabricated in the Material Research Labs’ cleanroom. The main problem, in my opinion, was that the circuit had simply been “copied and pasted” from the schematic provided by BAE (a silicon chip) to the GaAs-stretchable substrate, without any previous feasibility study that could take into account different electron mobility, different parasitics, different tech-nology and fabrication issues. As a matter of fact, no simulation was car-ried out before fabrication, in part due to the fact that neither a model of the stretchable-GaAs fabricated MESFET nor of the other components were

readily available at the time.

When I came back from the USA, I asked my advisor here if I could carry out this study, in order to obtain in Pisa those results that were still missing at the end of my stay in America.

The schematic originally considered came from the BAE company. It is shown below. It is a “common drain Colpitts oscillator”. In the following I repeat a description of a brief procedure for designing microwave oscillators using a simplified model for the active device to obtain a zero-order circuit design. That circuit can then be further refined by performing a nonlinear (transient) simulation with SPICE or ADS to estimate the output frequency and power delivered to a given load.

All practical 3-terminal active devices capable of gain can be reduced to the simple equivalent circuit shown in Fig.2.4(a), which, when feedback elements

X1 and X2 are added, becomes a small signal negative resistance device,

shown in Fig.2.4(b). Bipolar transistors can also be modeled this way, the terminal interchange being obvious (D-C, G-B, and S-E).

The circuit in Fig.2.4(b) can be analyzed considering an impedance

VIN/IIN = ZIN, which equals

(b) (a)

Fig. 2.4(a) Simplified device model. (b) Device with feedback elementsX1 andX2.

Fig. 2.5

Note that X1 and X2 should be of the same sign for ZIN to have a

negative real part. When X1 and X2 are capacitive, the oscillator is defined

a “Colpitts” oscillator; when inductive, a “Hartley” oscillator. The position of the ground node in Fig.1(b) is arbitrary; as shown, the circuit is called a “common drain” oscillator. In the BAE version, the RF power is extracted from the gate circuit, as shown in Fig. 2.5.

In Fig. 2.5, the load resistance and a resonating inductor are added. The position of the load resistance was changed the second time. The purpose

of XRES is to make the net reactance looking into the gate of the

feedback-loaded transistor equal to zero at only one frequency, so that oscillation will occur at that frequency. The value of XRES is equal to the imaginary part

of ZIN. Power is delivered to the load resistance RLOAD, which in the BAE

circuit is chosen to be less than the modulus of the real part of ZIN for

oscil-lations to start. The steady state value of ZIN is difficult to determine due

to nonlinear effects and, according to BAE document we were provided with,

typically the RLOAD is to be chosen between 30% and 50% of Re(ZIN).

After prolonged research and after having looked through many RF books, the solution put forward by Randal Reha in the book “Discrete Oscillator Design”, was adopted. A modern Common Drain Colpitts JFET oscilla-tor topology is shown in Fig. 2.6, where the resonant frequency is easily determined as:

f0 =

1 2πqL C1C2

C₁+C₂

Since a random combination of 1) a “Resonator” and 2) a “Sustain-ing/Amplification Stage” does not necessarily satisfy the required initial conditions, historically, when a successful design was found, the topology became a “standard design” and it was named after the discoverer. Because

Fig. 2.6

a successful oscillator design requires satisfying multiple goals, the habit of designing oscillators by starting with a named topology persists to this day, as in this case.

A few decades ago, the analysis was mathematically tedious and required over simplified models for both the active and the passive devices. This en-couraged an approach based on standard designs. Modern simulation tools offer convenient analysis of the open-loop chain including excellent models or measured data for active and passive devices. This facilitates the explo-ration of design alternatives, the optimization of initial conditions, and even

the discovery of new or modified topologies that achieve the required oscilla-tor performance with fewer components. The presentation of the open-loop chain as an oscillator design methodology may be disconcerting to the de-signer accustomed to working with named standard designs. While names are a convenient way to describe and categorize topologies, this habit is often abused and misleading.

In the modern Colpitts the signal is fed from the source to the gate through a

capacitive tapped parallel bandpass resonator with C2 in shunt, C1 in series,

and L0 in shunt with the signal path.

The Colpitts is realized using a variety of active devices. In our case we used a HEMT transistor, the NE3504m08. However, it is the resonator that defines whether an oscillator is Colpitts, Hartley or other named type. The classification of types by name is primarily a study of resonator topologies. As was previously pointed out, according to the modern convention for the Colpitts resonator, the signal path passes through a shunt capacitor, series capacitor, and shunt inductor. The shunt inductor and series capacitor are highpass and the shunt capacitor is lowpass. Therefore in the stopband, the Colpitts includes two transmission zeros at DC and one transmission zero at infinite frequency. With zeros above and below the passband, the Colpitts is a bandpass resonator.

The primary features of the Colpitts resonator are a transmission phase shift near 0 at resonance and dissimilar input and output impedances. The Com-mon Source devices are inverting and have approximately equal input and output impedance. Therefore, Colpitts oscillators use Common Collector and Common Base confgurations if using BJT transistors, or Common Drain and Common Gate confgurations if usng FET devices.

The Colpitts resonator is economic and a properly designed oscillator, pro-vides good performance as well. The Colpitts is arguably the most common oscillator topology.

As far as the “Colpitts Common Drain FET topology” is concerned, the figure below shows a 100-MHz common drain FET oscillator using a J309

N-type junction field-effect transistor. This FET has a moderately high Idss,

18 mA typical. Resistor R3 reduces and stabilizes the drain current. It has

to be noted that the very high input impedance of the FET is an advantage with the Colpitts resonator.

Figure 2.8 shows the output spectrum (left) and the starting waveform (right) for this oscillator.

The topology chosen for this research differs from both the BAE and Rhea ones. In fact, if on the one hand the BAE network had a resistor load in series with the resonant inductor (which made things more complicate),

Fig. 2.7

Fig. 2.8

low-power purposes. In other words the choice made in this work aimed at solving the two key points:

- Satisfying the initial conditions that let the oscillation start

- Decreasing the power consumption as much as possible, trying to maxi-mize the efficiency of the oscillator and at one and the same time ensuring that enough power is delivered to the antenna.

Eventually, because of the medical purposesand the high rate transmis-sion purposes the “Instrumentation Scientific and Medical” band (ISM) at 2.44 GHz frequency was chosen. At the end of the day, a Common drain Colpitts oscillator at 2.440 GHz (ISM Band) was realized. The active device is a NEC NE3508M04, GaAs HEMT.

From the data sheet the transconductance “gm” is 100 mS minimum, but

this is at 10 mA. The Agilent ADS AC simulation showed at the start up a transconductance of about 52 mS, namely almost half. Anyway, even a a lower value of 10 mS would be enough for the initial condition and appropri-ate for lower currents. This number could also be extrapolappropri-ated from some of the static, DC curves shown on the data sheet. Agilent Advanced Design System software has been used as the Computer Assisted Design environ-ment.

Fig. 2.9

The design flow followed in this work consists of five steps: 1) Schematic-level Design and simulation

2) Microstrip-level Design and and simulation 3) Layout Design and electromagnetic simulation 4) Cosimulation (or Postlayout simulation)

5) PCB realization and soldering of the components

2.2.1

Schematic-level Design and simulation

Figure 2.9 shows the final schematic circuit and the used simulations: As can easily be seen, this schematic differs from the BAE one because 1) The load has been moved from being in series to the inductor to being in parallel to the source resistor.

At the same time it differs from the Rhea one because 2) The power supply has been decreased from 9V to 1Volt.

As far as simulations are concerned, three different simulations on the same schematic have been run at this step:

- AC simulation

- Harmonic Balance Simulation - Transient Simulation

These simulations are coordinated by the tab “Parameter Sweep” that controls the order in which the indicated variables are swept.

Simulation can be run by clicking on the gear button or pressing F7. During any simulation, a Simulation/Synthesis Message window appears whenever a simulator is launched and displays messages about the status of the current process, as well as warning and error messages. Each simulation generates its own set of messages which are stored in memory during the current session. The window contains two information panels: the “Simulation/Synthesis Messages” and the “Status/Summary”.

The Simulation/Synthesis Messages portion of the window displays detailed messages about problems encountered during a simulation or synthesis.

With the aim of giving the reader a deeper insight into the tools and analysis methods used, a brief description of each simulation carried out in this work is provided in the following.

When an AC small-signal simulation is run, the system first computes the DC operating point of the circuit. Whenever a linear simulation such as a linear AC simulation requires a single-point DC bias evaluation to be run first, it is referred to as a bias-dependent linear simulation. The most common example is the case of a linear amplifier that uses a biased transistor as the active element. The DC bias simulation is executed automatically and transparently (unless an error causes the DC simulation to fail to converge). Following the DC bias simulation, the simulator linearizes all nonlinear devices about their bias points. A linearized model captures the small incre-mental changes of current due to small increincre-mental changes of voltage. These are the derivatives of the transistor model equations, which are evaluated at the DC bias point. Nonlinear resistors and current sources are replaced by linear resistors whose values are set by the small signal conductance dI/dV . Current sources that depend on voltages other than the voltage across the

source are replaced by linear dependent current sources dI1/dV2. Nonlinear

capacitors are replaced by linear capacitors of value dQ/dV . Harmonic balance description

Harmonic Balance is a frequency-domain analysis technique for simu-lating in nonlinear circuits and systems. It is usually the method chosen to treat analog RF and microwave problems, since these are most naturally

handled in the frequency domain. Within the context of high-frequency cir-cuit and system simulation, harmonic balance “often, but not always”, offers several benefits over conventional time-domain transient analysis. Harmonic balance simulation obtains frequency-domain voltages and currents, directly calculating the steady-state spectral content of voltages or currents in the cir-cuit. The frequency integration required for transient analysis is prohibitive in many practical cases, even though it turns out to be indispensable. A full professor coming from Sweden, with a long and successful experience in RF electronics, pointed out how nothing can be as time-consuming as RF-Simulations. It is due to the “chaos-related phenomena”, that sometimes make many algorithms fail. In short, given a data-processing-time step, if the simulator does not encounter any variations, it automatically increases the processing time step, assuming that no relevant variations are likely to occur in the next time span. Unfortunately this assumption is not always true in the presence of “Chaos Phenomena”. For these reasons we added the “Transient Tab” analysis, in order to compare its output results with those of Harmonic-Balance.

After recurrent and strange circuit simulation results were registered, the idea of comparing different operating simulation tabs was followed.