Hardware co-simulation configuration for the verification of the demodulation structure
1. Introduction
In this chapter, we present a demodulation structure suitable for a reader baseband receiver in a passive Radio Frequency IDentification (RFID) environment. RFID refers to a technology which uses radio communications to contactlessly identify a tagged physical object [1-2]. An RFID system may include a plurality of electronic tags on objects, animals, and other things having unique identification information and a reader for reading or writing information from or to the tags. RFID systems can be variously classified into the inductively coupled and electromagnetic schemes according to the communication method employed between an RFID reader and a tag, into an active type and a passive type according to whether the tag operates using its own power or not, and into long wave, medium wave, shortwave, ultrashort wave, and microwave depending on the frequency of the electric waves used for the communication [1-2]. Essentially, a passive RFID system consists of a reader and a passive tag without a battery. The International standard, ISO 18000-6C, defines the communication protocol and Ultra High Frequency (UHF) band between the reader and the passive tag [3]. Many studies have been conducted in the field of UHF RFID, as described in [4-14]. In the case of passive UHF RFID technology, the reader must provide the tag with continuous radio power, while the tag sends its information to the reader via a backscatter modulation. The tag encodes the backscattered signal as either FM0 (bi-phase space) or Miller modulation of subcarrier at the given data rate [3]. Recently, UHF Passive RFID has a trend of extending its domain to the application of an item-level-tagging (ILT) from that of a conventional pallet/case-level-tagging. In the ILT RFID environment, tags can be attached on the objects composed partially of a metal or liquid and can be placed at a nearby complicated surrounding in which the metallic objects exist. As a result, if undesired large signal reflected from the complicated surrounding is received at the reader receiver during receiving a desired backscattered tag signal, the performance of the identification for the reader can be easily degraded due to the reflected large signal which can leak to the reader receiver (Fig. 1(a)). In addition, if insufficient isolation is guaranteed between the transmitter and receiver, the transmission power (Tx power) created by the reader transmitter can leak to the receiver (Fig. 1(a)) [2]. A reflected power larger than the backscattered tag signal which is generated by the return loss (S11) of the antenna can also leak to the receiver via the circulator (Fig. 1(a)). Because of these unwanted leakage components in the reader receiver, the DC-offset phenomenon can occur in the baseband of the reader receiver.
As a result, the received baseband signal can be corrupted by the DC-offset phenomenon (Fig 1(b)). For example, Fig. 1(b) shows the Miller subcarrier signal highly affected by the DC offset phenomenon in our reader receiver measured using an Agilent Logic Analyzer. Due to the unwanted DC-offset phenomenon, the reader baseband receiver may not determine the valid bit data with sufficient reliability. There have been several researches to reduce the originally generated leakage components in advance, as reported in [4-6]. However, it may be difficult to perfectly and adaptively eliminate the leakage components in the ILT RFID field, in which the performance of the reader receiver can be adversely affected by the unwanted large reflected signals. Therefore, although the received baseband signal is contaminated with the DC-offset phenomenon, we attempt to further remove the DC-offset phenomenon from the distorted received signal in the baseband receiver. In the earlier study, we proposed a demodulation structure composed of an edge signal generator, an edge extractor and a signal reconstruction block for the FM0 signal distorted by the DC-offset phenomenon [14]. In this chapter, a similar concept is also applied to the reliable reconstruction of the Miller subcarrier signal not suffering from the DC-offset phenomenon by using the phase inversion information instead of the amplitude information. In order to accomplish this, we detect the valid information from the corrupted signals by making use of a demodulation structure composed of a peak signal generator, a peak detector, and a signal reconstruction block, in order to successfully decode the received baseband signal distorted by the DC-offset phenomenon. According to the proposed demodulation method, the peak signal is created at the position of phase inversion within the Miller subcarrier signal sequence using the phase inversion information. Therefore, although a certain amount of DC-offset noise can be appeared in the baseband of the reader receiver, the proposed method is allowed to supplementally deal with the DC-offset phenomenon once more in the baseband receiver.
This chapter is organized as follows. In Section 2, we describe in detail the demodulation structure and method used to extract meaningful information from the distorted Miller subcarrier signal suffering from the DC-offset phenomenon. In Section 3, we show the simulation and implementation results. Finally, we draw our conclusions in Section 4.
2. Demodulation algorithm
In this section, we introduce the demodulation structure and algorithm suitable for the reconstruction of the Miller subcarrier signal distorted by DC-offset noise.
2.1. Demodulation of the Miller subcarrier-encoded signal
The Miller modulated sequence contains exactly two, four, or eight subcarrier cycles per bit, depending on the
where
In order to generate the peak signal with respect to the received baseband signal
where
where,
In the second step, the created initial peak signal
In the next step, from the final peak signal,
2.2. Determination of the low pass filter specification
In our method for the demodulation of the Miller subcarrier signal, the difference signal between
Section 2.1. Fig. 6(a) shows the spectral response of the difference signal of the Miller subcarrier signal with
3. Simulation & experimental results
For the first example, we consider the operation of the proposed demodulation structure when the received baseband signal is the distorted Miller subcarrier-encoded signal with DC-offset noise (
For the second example, the Miller subcarrier signal with
Case 1: the output signal
Case 2: the output signal
Case 3: the difference signal between
Case 4: initial peak signal
Case 5: final peak signal
Case 6: Reconstructed Miller baseband signal without DC-offset noise
In the next example, we implemented the proposed demodulation structure as a hardware device FPGA (Field Programmable Gate Array) and then the operation of the demodulation structure is observed using the commercial DSP design tool, Xilinx System Generator which provides hardware co-simulation, making it possible to incorporate the demodulation design running in an FPGA directly into a MATLAB Simulink simulation [15]. Fig. 12 shows the designed hardware co-simulation model of the proposed demodulation structure using a Black Box and JTAG Co-Sim library block provided by the System Generator. The Black Box library block allows a designed HDL (hardware description language), such as VHDL and Verilog, to be brought into the Simulink design model and enables us to easily observe the corresponding simulation behaviour in MATLAB Simulink.
In order to execute the designed Simulink model of the demodulation structure in Fig. 12, the following hardware co-simulation environment should be considered as shown in Table 1.
Items | Descriptions |
MATLAB | MATALB 2008a |
System Generator | Xilinx System Generator 10.1 |
HDL design tool | Xilinx ISE 10.1 |
HDL simulation tool | ModelSim SE 6.2b |
FPGA (Digital hardware board) | Xilinx SPARTAN-3 XC3S4000FGG676-5G |
JTAG Cable | Xilinx USB cable |
Simulink system period [sec] | 3.90625e-7 (1/2.56MHz) |
Meanwhile, the Black Box HDL can be co-simulated with MATLAB Simulink using the System Generator interface to either ISE simulator or the ModelSim simulation software from Model Technology, Inc. Fig. 13 shows the operation result of the demodulation structure using the latter method through ModelSim when the measured Miller subcarrier signal (Fig. 2(b)) is considered. The operation result (Scope 2) using the former method through ISE simulator is also shown in Fig. 14
Next, Fig. 15 shows the hardware co-simulation result in Scope 3 when the same measured Miller subcarrier signal (Fig. 2(b)) is considered.
To obtain the JTAG Co-Sim library block (Fig. 12) for the demodulation structure, the hardware and software required to run the hardware co-simulation on the FPGA board (Table 1) should be installed and set up in advance [15]. Therefore, once the System Generator has successfully finished compiling the HDL design into the FPGA bitstream, it automatically creates the JTAG Co-Sim library block as shown in Fig. 12. As a result, in comparison with Fig. 14, we observe that the timing simulation result of Fig. 15 is nearly identical to the functional HDL simulation result of Fig. 14.
Finally, the measured operation results obtained using Agilent Logics Analyzer equipment are described in Fig. 16. From the results of Figs. 13, 14, 15, and 16, we observe that the proposed method can successfully reconstruct the Miller baseband signal, even though the received Miller subcarrier signal is distorted by the DC-offset phenomenon. Although we do not show the corresponding demodulation results, the demodulation structure and algorithm described in Section 2 can be directly used to reconstruct a distorted Miller subcarrier signal with
3. Conclusion
In this study, we propose a reader baseband receiver structure for the demodulation of the Miller subcarrier signal described in the international UHF RFID standard, 18000-6 Type C, under the DC-offset phenomenon. In order to perfectly remove the DC-offset noise caused by the leakage components in a passive RFID environment, the proposed structure for the passive RFID reader baseband receiver primarily includes the peak signal generator, the peak extractor, and the signal reconstruction block for demodulating Miller subcarrier signals. The phase inversion information is used to generate the peak signal and the resulting reconstructed signal is the Miller baseband signal removed both the DC-offset noise and the rectangular subcarrier signal simultaneously. To verify the operation and functionality of the proposed demodulation structure, we implemented both the HDL co-simulation using the Black Box library block and the hardware co-simulation using the JTAG Co-Sim one simultaneously. The results show that the proposed demodulation method can successfully extracts the valid information from the signal corrupted by the DC-offset noise which can occur in a passive RFID configuration.
Acknowledgments
This work was supported by the IT R&D program of MKE/IITA [Development of Next Generation RFID Technology for Item Level Applications], Rep. of Korea.
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