A Study on RF Signal Generator and Analyzer for Passive Surface Acoustic Wave based Wireless Sensors

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1 A Study on RF Signal Generator and Analyzer for Passive Surface Acoustic Wave based Wireless Sensors Sang Cheol Lee 1, Hee Kuk Kang 1, Jae Sung Choi 1, Dong Ha Lee 1, Hyun Lee 2 and Jeong Bae Lee 2, 1 Division of Robotics System, DGIST, Daegu, , Korea 2 Department of Computer Engineering, Sunmoon University, Asan, , Korea {sclee, comhero, jschoi, dhlee}@dgist.ac.kr, {mahyun91, jblee}@sunmoon.ac.kr Abstract. Sensor technologies are rapidly growing and wireless measurement systems with passive surface acoustic wave (SAW) sensors are broadly used in wide variety of sensor applications, even in harsh environments such as enemy base-station, human tissue and the inner wall of the building. To developing and validating batter-less wireless sensors, generally frequency characteristic of the sensor is analyzed by using an oscilloscope. However, the system only analyzes simple waveforms. Thus, we propose and develop a new SAW system analyzer and a SAW reader emulator based on NI Labview instruments for monitoring and emulating the RF signals. Finally, we compare our approach with existing approach to show the better performance of our approach. Keywords: SAW sensor, batter-less wireless sensor, RF signal, Generator, Analyzer, Emulator. 1 Introduction In recent, wireless sensor network technologies is utilized in wide variety of sensor applications such as Ubiquitous Sensor Network (USN), structural safety evaluation, and medical engineering, and so on [1], [2]. Sensor generally utilizes Complementary Metal Oxide Semiconductor (CMOS) circuits for converting sensed information into electrical signals then for transmitting the signals. However, CMOS has a limitation. A circuit should be supplied by using a wired power or a battery power. It is difficult to supply power into sensing systems in harsh environments where you cannot replace the power system or the battery such as the enemy base-station, the inner wall of the building, the area of radioactive contamination, and human tissue [3], [4]. Depending on an existence of built-in power source and type of communication, the sensors can be classified to active, semi-passive, and passive sensors. In the active sensor system, the sensor actively generates a signal using own built-in power source and communicates to other sensors or base-stations based on its pre-defined transmission schedule. The semi-passive sensor system passively communicates with other devices using its power source for the sensor s logical operations. In contrast with the active and semi-passive systems, the passive sensor system does not contain any power source, and it must harvest operation and communication power from the

2 outside. There are several types of passive sensors depended on power gathering and communication techniques such as Near-Field, Far-Field, and Surface Acoustic Wave (SAW). We mainly focus on SAW based battery-less sensors which provide maximal 3m~10m of communication range using ISM bands. For an application on Wireless Sensor Networks (WSN), the battery-less sensor has significant benefits such as cost efficiency, semi-permanent operation and communication, and easy deployment and maintenance. However, in order to develop SAW based wireless sensors, sensor evaluation tools and signal generators are required. But currently existing evaluation devices provide only functions of signal measurement and signal analysis. The rest of this paper is organized as follows: We review the existing SAW sensor s structure and operating method in Section 2. In Section 3 and 4, we represent a developed hardware and software system models for SAW sensor system. We present our conclusion in Section 5. 2 Related Work SAW stands for Surface Acoustic Wave, and this concept was introduced by Load Rayleigh in Then, during last decades, SAW technologies are applied on battery-less wireless sensors and Radio Frequency Identification systems (RFID). Figure 1 shows a basic architecture of SAW sensor. The sensor consists of a piezoelectric substrate, input and output inter-digital transducers (IDT), and sensing layer. For operation of SAW wireless sensor system, first, SAW reader transmits 300MHz~2.45GHz of operating frequency to a sensor. When SAW sensor receives the signal, the RF signal is transformed to acoustic wave through the input IDT. In this stage, electric energy on RF is transduced into mechanical energy in the acoustic wave on the piezoelectric substrate. The transformed input signal contains sensing information and the sensor s unique identification, and then the output IDT reconverts the acoustic signal into an electrical signal. Finally, the sensor transmits the electrical Figure 1. Architecture of SAW sensor system

3 Figure 2. Control system for SAW sensor system signal to SAW reader, and the reader sends the received data to an analyzer to study the collected data [5]. 3 System Modeling SAW wireless sensor analyzing system must be designed to perform signal measurement. Also, the analyzer connects to RF transmitter and receiver of the reader device for the entire monitoring about communication between the reader and sensors. The sensor analyzer, which is based on National Instrument PXIe-1075, prepared two communication channels such as Vector Signal Analyzer (VSA) CH1 and VSA CH2, these channels take care independent RF transmission and receiving. In this research, VSA CH1 is used for connection between SAW reader and the analyzer, and CH2 is assigned for connection between SAW sensor and the analyzer. However, in order to minimize interference between signals, we isolate the reader and the sensor with the use of a divider and a circulator as shown in Figure 2. The sensor analyzer equips two of PXIe-5663E slot, which are the left slots in Figure 3 (b), and a single PXIe-5673E slot, which places the right on the system as shown in Figure 3 (b), for SAW reader emulator. Also, it contains various type of RF connectors for further extension. For a normal operation of the NI LabView based analyzer, the latest version of NI LabView needs to be installed on the system. Additionally, we installed several NI toolkits such as Advanced Signal Processing Toolkit, Spectral Measurement toolkit, and Modulation toolkit. 4 SAW System Analyzer and Reader Emulator In this section, we address detail about SAW system analyzer and reader emulator for accurate and precise measurement of performances of SAW sensor devices. The analyzer provides simultaneous evaluations for two different signals from VSA CH

4 (a) Figure 3. The proposed SAW sensor analyzer (b) and CH2, which are connected to the reader and the sensor. The analyzer mainly furnishes IQ and spectrum measurement modes for RF signal analysis. For synchronization between from VSA CH1 and CH2, the system employs IQ measurement mode, and then NI Spectral Measurement toolkit transforms the captured data into spectrum data to display on the monitor. An initial interface of the SAW system analyzer is described in Figure 4. An initial stage, a user can configure 5 primary items as IQ configuration, Spectrum configuration, Operation, Graph, Graph control. In order to precise measurement of IQ data, the system initially configures a few conditions such as amplitude, IQ set-up, and trigger. Amplitude configuration relates on an input of reference level with dbm unit. IQ set-up is in charge to establish an initial value of carrier frequency for RF transmission and the number of measurement for RF analogdigital converter. The trigger configuration is related on a type of measurement provocations such as none, digital edge, and IQ power edge. In the case of IQ power edge, this type of trigger is used to initiate the analyzer with a power level of RF Figure 4. Initial interface of the proposed SAW system analyzer

5 (a) (b) (c) Figure 5. Types of displayed data by the SAW system analyzer (d) signal from two given channels. The spectrum configuration responses transformation between IQ data to spectrum data. The central frequency of IQ signal is the same as the defined carrier frequency, and a span is the range of sub-side frequency range. Moreover, an auto-resolution function allows inner-calculation of resolution bandwidth. A power spectrum unit handles expression of dbm unit based data to Hz unit based data using a power spectral density (PSD). The operation configuration is simply displayed on the top of right side in Figure 4. When the system starts, IQ and spectrum data are displayed on two dimensional graph based on IQ and spectrum configuration information. Figure 4 (b) shows a sample of IQ graph. Additionally, the analyzer provides selection of type of displayed data such as an I or Q graph, a power vs time graph for power consumption against operating time, a phase delta vs time graph, a spectrum graph for central frequency, and a spectrum ACP graph for comparison with power of adjacent channel. Figure 5 illustrates samples of displayed data by the SAW system analyzer. The graph control can configure bandwidth and spacing value for the spectrum ACP graph, and it can allow modifying time axis for a temporal section. Moreover, a synchronization graph provides synchronized data between the SAW reader and SAW sensor. SAW Reader Emulator conducts a virtual SAW reader using imitational RF signal from SAW reader. The imitational RF signals are transformed to a chirp wave form by the emulator, and the emulator transmits the signal to the sensor. Moreover, the emulator can generate analog RF signals with various spectrums, and it is available to test heterogeneous sensor devices which have a unique relative RF characteristic. Figure 6 illustrates the initial interface of the emulator

6 Figure 6. Initial interface of SAW reader emulator Additionally, the proposed SAW sensor analyzer and SAW emulator support a data exporting functions for maintain the measured RF data and graph to maximize availability and reliability. 5 Conclusion SAW sensor has significant benefit to measure environmental factors such as physical and chemical quantities, illumination, temperature, humidity, and level of background noise, using sensible surface technologies without any built-in power source for semipermanent operation of the sensing devices. For investigation of the SAW sensor, we propose a new SAW analyzer and emulator to overcome limitations of existing network analyzers, such as lack of customization of signals, exporting functions of measurement data and graphs, and these limitations disrupt collaboration for SAW sensor development and evaluation. In this research, proposed novel SAW sensor analyzer and reader emulator which are based on NI devices and Labview, and the analyzer and emulator guarantee more accurate observation and evaluation with intuitive and evincive interfaces

7 Acknowledgment This work was supported by the DGIST R&D Program of the Ministry of Education, Science and Technology of Korea (12-BD-0101) References 1. F. Akyildiz, W. Su, and Sankarasubramaniam, and E. Cayirci, ''Wireless Sensor Networks: A Survey,''Elservier Computer Networks, Vol. 38, No. 4, Mar.2002, pp K.G. Ong, C.A. Grimes, C.L. Robbins, R.S. Singh, Design and application of a wireless, passive, resonant-circuit environmental monitoring sensor, Sensors and Actuators A: Physical, Volume 93, Issue 1, 25 Aug 2001, Pages Stangel, K.; Kolnsberg, S.; Hammerschmidt, D.; Hosticka, B.J.; Trieu, H.K.; Mokwa, W.;, "A programmable intraocular CMOS pressure sensor system implant," Solid-State Circuits, IEEE Journal of, vol.36, no.7, pp , Jul Reindl, L.M.; Pohl, A.; Scholl, G.; Weigel, R.;, "SAW-based radio sensor systems," Sensors Journal, IEEE, vol.1, no.1, pp.69-78, June