1. Progress Report on OWDM-Based Cognitive Radio System
Presenter: Kuan-Hung Chen
Adviser: Tzi-Dar Chiueh
March 28, 2005
Professor, ladies and gentlemen, today, I would like to talk about the current progress of the proposed OWDM-based cognitive radio system.

2. Outline Why Cognitive Radios? Motivation
Orthogonal Wavelet Division Multiplexing (OWDM)
OWDM-Based Cognitive Radio System
Simulation Results
Conclusions
To begin with, I will talk about why we need the cognitive radios and the motivation of combining the OWDM modulation and the cognitive radio. Then, the orthogonal wavelet division multiplexing, abbreviated as OWDM, will be introduced. The architecture of the proposed OWDM-based cognitive radio system is shown. Some simulation results about CFO estimation and compensation are shown. And, finally, a brief conclusion is given.

3. Why Cognitive Radios?
In the near future, it is expected that the demand for bandwidth will increase substantially due to
more and more sophisticated wireless applications,
explosive increase of wireless LAN availability, and
growing demands on ubiquitous wireless access to Internet.
Scarcity of spectral resources reminds us spectrum should be used more efficiently.
Cognitive Radio draws lots of attention.
It is proposed to improve spectrum utilization.
It should be smart enough to find out free spectrum it can use.
Recently, the wireless LAN becomes more and more popular and the accessibility of wireless LAN is substantially increasing. Due to this trend, more and more wireless applications are developed and the demands on ubiquitous wireless access to Internet is growing. It is expected that the demand for bandwidth will increase substantially and the shortage of bandwidth may happen in the future. The scarce spectral resource should be used more efficiently to avoid the bandwidth shortage. Recently, cognitive radio has drawn much attention in that it can reuse the spectrum that is seldom used in time or space to enhance the spectrum utilization.

4. Inefficiency on Spectrum Utilization
This figure shows the measured power on different bands and different areas. We can see that current spectrum utilization is quite low in some bands. Moreover, some bands are seldom used in some geographic areas. The main target of the cognitive radios is to reuse the unused spectrum if there are demands on bandwidth.
[1]

5. Motivation Cognitive radio  OFDM
OFDM modulation has some disadvantages when only fragmentary spectrum is available.
Frequency T I M E …
Recently, the research about cognitive radio still focus on OFDM modulation. However, in the bands where the available spectrum is divided into pieces by the primary users as shown in this figure, the OFDM modulation has some disadvantages. When the subcarriers that can be fit into spectrum holes are enabled for data transmission, the sidelobes of these subcarriers may introduce harmful interference to primary users. In these bands, it is hard to reduce the interference by using guard band or bandpass filters. So, we may ask if there is any other possibilities for cognitive radio?
[2]

6. IEEE
In Dec. 2002, FCC begins to consider allowing unlicensed operation in licensed band [3][4].
TV bands below 900 MHz and in MHz band
It seems that the technology is not ready to support unlicensed operation in TV broadcast spectrum [5].
A new working group is created in Nov for cognitive wireless regional area network (WRAN) standardization.
Provide fixed, point to multi-point air interface
Prevent harmful interference to the licensed services
In December 2002, FCC adopted an Notice of Inquiry that is proposed to explore unlicensed sharing of spectrum in TV bands below 900MHz and in MHz band. However, some studies demonstrate that the current technology is not ready to support unlicensed operation in TV broadcast spectrum. Recently, a new working group, IEEE , is created in November 2004 to specify the air interface, including MAC and PHY, of a fixed, point-to-multipoint wireless regional area networks. It should be operated on a strict non-interference basis in spectrum assigned to, but unused by licensed TV services. The IEEE study group does not believe that any existing IEEE 802 PHY/MAC combination can meet these requirements without extensive modifications. So, they create a new working group to do this. These facts reveal that new technologies may be required for cognitive radios.

7. OWDM and Cognitive Radio
OWDM modulation has been studied extensively for xDSL applications or wireless communications.
Better sidelobes attenuation is achievable by OWDM.
A cognitive radio system applies the OWDM is proposed.
Target band: TV band, GSM band, etc.
The OWDM, like OFDM, is also a multichannel modulation scheme. Many efforts have been done to apply it on digital subscriber line systems or even wireless communication systems. The OWDM can provide higher sidelobes attenuation than OFDM and the enabled subchannels will introduce lower interference to primary users. Here, an OWDM-based cognitive radio system is proposed. It is suitable to operate in TV band, GSM band, or other bands, where the available spectrum is composed of small and non-contiguous subbands.

8. Orthogonal Wavelet Division Multiplexing
Now, I will begin to introduce the orthogonal wavelet division multiplexing, abbreviated as OWDM.

9. Introduction on Wavelet
A wave is usually defined as an oscillating function of time, such as a sinusoid.
A wavelet is a “small wave”, which has its energy concentrated in time.
First, the definition of the wavelet is given here. A wave is usually defined as an oscillating function of time, for an example, the sinusoids. A wavelet is a small wave. Its energy is concentrated in time and can be used to analyze the transient, non-stationary, or time-varying phenomena.
[6]

10. Orthogonal Wavelet Division Multiplexing
Wavelet based multichannel modulation scheme.
Implemented via overlapped waveforms to preserve data rate.
Guard interval does not make sense in OWDM.
Symbol Duration: T
The orthogonal wavelet division multiplexing is a wavelet-based multichannel modulation scheme. It is realized by using a set of orthogonal wavelets as the basis functions and the information data is loaded on these wavelets for data transmission. These orthogonal wavelets are generated through a set of wavelet filters and the length of the wavelet filters is longer than that of Fourier filters. These wavelets have two important properties. One property is that a wavelet is mutually orthogonal to other wavelets because they occupy different orthogonal subspaces in frequency domain. The other property is that a wavelet is orthogonal to its time domain block-wise shifted versions. It means that if the symbol duration is capital T, a wavelet shifted by multiples of capital T is orthogonal to its un-shifted version. Since the length of the wavelet filters is longer than that of Fourier filters, the length of wavelets is longer than the symbol duration. This self orthogonality allows the wavelets to be overlapped in time to preserve the data rate. We can see that, in this figure, the waveform of the first symbol is overlapped with the waveforms of the second symbol and the third symbol, etc. T T

11. Subchannel Spectrum Property
The energy of each subchannel is much more concentrated in mainlobe than that in OFDM case.
OFDM Subchannel Spectrum
OWDM Subchannel Spectrum
The main advantage of OWDM modulation is that higher spectral containment can be achieved. It means that the energy of each subchannel is much more concentrated in mainlobe. The subchannel spectrums of OFDM and OWDM are shown in this slide. We can see that the OWDM can achieve 38dB attenuation of the first sidelobe while the OFDM can achieve only 13dB attenuation of the first sidelobe. Lower interference is introduced to primary users by using OWDM modulation.

12. OWDM-based Cognitive Radio System
Indoor low-mobility wireless communication system
Target band: TV band, GSM band, etc.
What we proposed is an OWDM-based cognitive radio system. The target is an indoor low-mobility wireless communication system. The access point should be powerful enough to provide accurate information about available spectrum while the mobile terminal should have basic spectrum sensing capability to solve hidden node problem. The control channel is supposed to be located in a specific licensed band for cognitive radio. The target bands include TV band, GSM band, or other bands, where only fragmentary spectrum is available.

13. Advantages and Drawbacks
Higher spectral containment
More robust to narrowband interference
Drawbacks
Higher complexity
More complex equalization
Challenges
Low-complexity architecture development
The main advantage of OWDM is its higher spectral containment. This property makes it possible to introduce lower interference to primary users. Moreover, it is more robust to narrowband interference due to this property. Only those subchannels having mainlobes overlapping with the narrowband interference are severely affected. Other subchannels suffer much fewer interference than that in OFDM case. We know that, there are many narrowband interferers existing in the operating environment of a cognitive radio system.
However, the OWDM modulation also has some drawbacks. Since the guard interval does not make sense in OWDM, more complex equalization scheme is required to mitigate ISI and ICI. Furthermore, higher complexity is required to realize the OWDM modulation. The development on low-complexity architecture is also necessary.

14. System Specification Modulation type 2-ary PAM, 4-ary PAM, 8-ary PAM
Subchannel number
256
Subchannels in use
< 244
Carrier frequency
TV band: 478+4*l MHz, l=0, 1, …
GSM band: MHz, MHz
Sampling Frequency
TV band: 24*n MHz, n=1, 2
GSM band: 25.6 MHz
Subchannel Spacing
TV band: 93.75*n kHz, n=1, 2
GSM band: 100 kHz
The packet format is shown here. The short preamble is used for CFO estimation while the long preamble is used for symbol timing estimation. The training symbol is used for channel estimation to initialize the FEQ coefficients. Then, data symbols are attached.

15. Packet Format Short Preamble: CFO estimation
Long Preamble: Symbol timing estimation
Training Symbol: Channel estimation for FEQ initialization
The packet format is shown here. The short preamble is used for CFO estimation while the long preamble is used for symbol timing estimation. The training symbol is used for channel estimation to initialize the FEQ coefficients. Then, data symbols are attached.

16. System Architecture
Exponentially-modulated synthesis/analysis bank (EMSB/EMAB) are used to realize the OWDM modulation/demodulation.
The system architecture is shown in this slide. In the transmitter, the preamble generator is used to generate the preamble pattern for synchronization and the training pattern for FEQ according to the available spectrum information. The OWDM modulation is realized by exponentially-modulated synthesis bank, abbreviated as EMSB. The generated long preamble should be sent to symbol timing estimation block and stored in this block. In the receiver, CFO is first estimated using the short preamble and is compensated by the CFO de-rotator. A matched filter is used to perform the matched filtering between the received samples and the long preamble. The outputs of the matched filter are used to perform the symbol timing estimation and the maximum ratio combining. The OWDM de-modulation is realized by exponentially-modulated analysis bank, abbreviated as EMAB. The training pattern is extracted to perform channel estimation for FEQ coefficients initialization. FEQ is used to mitigate ISI and ICI. The pilots are inserted in the data symbols to estimate the residual CFO.

17. Channel Model Multipath Rayleigh fading, SCO, CFO, AWGN
The channel model considers multipath Rayleigh fading, sampling clock offset, carrier frequency offset, and AWGN.

18. CFO Estimator The length N used for moving average is adjustable.
The architecture of CFO estimator is shown in this slide. The delay correlator correlates the input sample and the complex conjugate of the sample received 128 clock cycles before. And 128 correlation results are accumulated. The output of the delay correlator is sent to the moving average block. The output with maximum power of the moving average block is found and the phase of the corresponding delay correlator’s output is then used to perform the CFO estimation.

19. Simulation Setups Parameters
Carrier frequency: 2.4 GHz
Sampling frequency: 80 MHz
CFO: 40 ppm
The CFO estimator is randomly enabled during the first 64 samples of the second symbol in the short preamble.
Three cases are simulated.
Case 1: CFO estimation is done using 256+N-1 samples.
Case 2: CFO estimation is done using 288+N-1 samples.
Case 3: CFO estimation is done using 320+N-1 samples.
5 schemes are done for each case.
10000 runs are simulated for each scheme.

20. Simulation Results
Case I
Case II
Case III

21. Histogram of Percentage CFO Estimation Error
Case I: Without moving average, SNR = 5dB

22. Bit Error Rates 100 symbols are transmitted for each run
300 runs are simulated for each SNR
2dB degradation under low SNR

23. Conclusions
An OWDM-based cognitive radio system is proposed to operate in the bands where only fragmentary spectrum is available.
Lower interference to primary systems can be achieved by OWDM modulation.
Moving average is useless to improve the accuracy of CFO estimation.
An OWDM-based cognitive radio is proposed and lower interference to primary systems can be achieved. Simulation results show that moving average is useless to improve the accuracy of CFO estimation.

24. Reference
[1] E. Tsui, “What are Adaptive, Cognitive Radios?” in BWRC Winter Retreat, Jan. 13, 2004.
[2] B. Fette, “SDR Technology Implementation for the Cognitive Radio,” in Workshop on Cognitive Radio Technologies, Washington, DC, May 19, 2003.
ftp://ftp.fcc.gov/pub/Bureaus/Engineering_Technology/Documents/cognitive_radio/fcc_cognitive_radio_fette_v8.ppt
[3] B. Lane, “Cognitive Radio Technologies in the Commercial Arena,” in Workshop on Cognitive Radio Technologies, Washington, DC, May 19, ftp://ftp.fcc.gov/pub/Bureaus/Engineering_Technology/Documents/cognitive_radio/lane_cognitive_radio_ ppt
[4] FCC, ET Docket
[5] Joint reply comments of the association for maximum service television, Inc., the national association of broadcasters, and the association of public television stations.
[6] C. S. Burrus, R. A. Gopinath, and H. Guo, Introduction to Wavelets and Wavelet Transforms, Prentice-Hall, Inc., 1998.