analysis of ofdm parameters using cyclostationary spectrum sensing
DESCRIPTION
Spectrum detection using Spectral Correlation Function explained for a cognitive radio environment . The slides briefly walks you through the signal generation for a DVB-T OFDM signal, cyclic prefix generation, passing over channel and receiver side approximations using SCF functionTRANSCRIPT
![Page 1: Analysis of OFDM Parameters Using Cyclostationary Spectrum Sensing](https://reader033.vdocuments.net/reader033/viewer/2022061106/5447ec46afaf9f41088b4661/html5/thumbnails/1.jpg)
Analysis of OFDM parameters using cyclostationary spectrum sensing in Cognitive
Radio
Presented by :Omer Ali
![Page 2: Analysis of OFDM Parameters Using Cyclostationary Spectrum Sensing](https://reader033.vdocuments.net/reader033/viewer/2022061106/5447ec46afaf9f41088b4661/html5/thumbnails/2.jpg)
What is a Cognitive Radio ?
• Cognitive Radio is built on the basis of a Software-defined Radios SDR
• Cognitive Radio can provide the spectral awareness technology to support FCC initiatives in Spectral Use
![Page 3: Analysis of OFDM Parameters Using Cyclostationary Spectrum Sensing](https://reader033.vdocuments.net/reader033/viewer/2022061106/5447ec46afaf9f41088b4661/html5/thumbnails/3.jpg)
Cognitive Radio - Continued
• Cognitive radio: A radio that can change its transmitter parameters based on interaction with the environment in which it operates.
![Page 4: Analysis of OFDM Parameters Using Cyclostationary Spectrum Sensing](https://reader033.vdocuments.net/reader033/viewer/2022061106/5447ec46afaf9f41088b4661/html5/thumbnails/4.jpg)
Is Cognitive Radio SMART ?• It knows where it is• It knows what services are
available, for example, it can identify then use empty spectrum to communicate more efficiently
• It knows what services interest the user, and knows how to find them
• It knows the current degree of needs and future likelihood of needs of its user
• Learns and recognizes usage patterns from the user
• Applies “Model Based Reasoning” about user needs, local content, environmental context
![Page 5: Analysis of OFDM Parameters Using Cyclostationary Spectrum Sensing](https://reader033.vdocuments.net/reader033/viewer/2022061106/5447ec46afaf9f41088b4661/html5/thumbnails/5.jpg)
Why Spectrum Sensing ?
• Spectrum awareness or spectrum sensing makes a radio environment cognitive i.e. to memorize the spectrum holes or voids that could be utilized by utilizing the available spectrum and adapting to it by changing its parameters
![Page 6: Analysis of OFDM Parameters Using Cyclostationary Spectrum Sensing](https://reader033.vdocuments.net/reader033/viewer/2022061106/5447ec46afaf9f41088b4661/html5/thumbnails/6.jpg)
Spectrum Holes
Power
Time
Frequency
Spectrum in use by Primary user
Spectrum Hole
• Main aspect: One main aspect of cognitive radio is related to autonomously exploiting locally unused spectrum to provide new paths to spectrum access.
![Page 7: Analysis of OFDM Parameters Using Cyclostationary Spectrum Sensing](https://reader033.vdocuments.net/reader033/viewer/2022061106/5447ec46afaf9f41088b4661/html5/thumbnails/7.jpg)
Why to sense Spectrum holes ?• As FCC agrees on utilizing the spectrum holes for DVB-T for unlicensed
users; it is vital to lease this unused spectrum to users in the vicinity.• Finding spectrum holes ? That means the spectrum should be dispersed ?• The answer is somewhat YES. Think about utilizing the primary spectrum
for DVB-T applications and the secondary spectrum for unlicensed users.
![Page 8: Analysis of OFDM Parameters Using Cyclostationary Spectrum Sensing](https://reader033.vdocuments.net/reader033/viewer/2022061106/5447ec46afaf9f41088b4661/html5/thumbnails/8.jpg)
Spectrum Utilization ?
Frequency
T
I
M
E
Spectral Adaptation Waveforms
![Page 9: Analysis of OFDM Parameters Using Cyclostationary Spectrum Sensing](https://reader033.vdocuments.net/reader033/viewer/2022061106/5447ec46afaf9f41088b4661/html5/thumbnails/9.jpg)
How to Sense the Spectrum?
• Spectrum sensing is currently achieved dynamically using DSS
• Are there any trade-offs in terms of different sensing techniques ?
• The Answer is YES .– One might sense a empty spectrum easily but it
might be the one with very power SNR.– So, the goal is to sense the proper spectrum for
unlicensed users
![Page 10: Analysis of OFDM Parameters Using Cyclostationary Spectrum Sensing](https://reader033.vdocuments.net/reader033/viewer/2022061106/5447ec46afaf9f41088b4661/html5/thumbnails/10.jpg)
Spectrum sensing - Methods
• Energy Detector Based Sensing: The signal is detected by comparing the output of the energy detector
with a threshold which depends on the noise floor.• Inability to differentiate interference from
primary users and noise, and poor performance under low signal-to-noise ratio (SNR)values.
![Page 11: Analysis of OFDM Parameters Using Cyclostationary Spectrum Sensing](https://reader033.vdocuments.net/reader033/viewer/2022061106/5447ec46afaf9f41088b4661/html5/thumbnails/11.jpg)
Spectrum Sensing Methods
• Waveform-Based Sensing: Known patterns are usually utilized in wireless systems to assist synchronization or for other purposes. Such patterns include preambles, midambles, regularly transmitted pilot patterns, spreading sequences etc.
• Waveform-based sensing requires short measurement time.
![Page 12: Analysis of OFDM Parameters Using Cyclostationary Spectrum Sensing](https://reader033.vdocuments.net/reader033/viewer/2022061106/5447ec46afaf9f41088b4661/html5/thumbnails/12.jpg)
Spectrum Sensing Methods
• Cyclostationarity-Based Sensing: Cyclostationarity feature detection is a method for detecting primary user transmissions by exploiting the
cyclostationarity features of the received signals.
• The cyclostationarity based detection algorithms can differentiate noise from primary users’ signals.
![Page 13: Analysis of OFDM Parameters Using Cyclostationary Spectrum Sensing](https://reader033.vdocuments.net/reader033/viewer/2022061106/5447ec46afaf9f41088b4661/html5/thumbnails/13.jpg)
Why OFDM ?• OFDM symbols are used in this research because it
supports broader bandwidth and is normally utilized in current MIMO technologies.
• The modulation scheme can be varied and the corresponding spectrum efficiency and spectrum utilization varies per modulation scheme.
• Limitations – OFDM power leakages to adjacent channels
![Page 14: Analysis of OFDM Parameters Using Cyclostationary Spectrum Sensing](https://reader033.vdocuments.net/reader033/viewer/2022061106/5447ec46afaf9f41088b4661/html5/thumbnails/14.jpg)
OFDM – Advantages / Disadvantages ?
• Advantages– Simple implementation by means of FFT– High spectral efficiency considering (no. of sub-
carriers)– Anti ICI and ISI makes OFDM receiver less complex, as
almost no equalizer is needed.• Disadvantages– Requires highly linear amplifiers– Sensitive to Doppler Effect– Guard-time introduces overhead
![Page 15: Analysis of OFDM Parameters Using Cyclostationary Spectrum Sensing](https://reader033.vdocuments.net/reader033/viewer/2022061106/5447ec46afaf9f41088b4661/html5/thumbnails/15.jpg)
Research Goal ?
• Using OFDM for DVB-T applications calculate the primary and secondary users
• Improve bandwidth by removing guard-band , BUT , will it have any impact on ICI?
• If ICI increases, then we should come up with something for better utilization . Cyclic prefix maybe ….
• What to do with the received signal with lots of noise ? Maybe normalize the whole received spectrum and pick-up the most healthy spectrum ….
![Page 16: Analysis of OFDM Parameters Using Cyclostationary Spectrum Sensing](https://reader033.vdocuments.net/reader033/viewer/2022061106/5447ec46afaf9f41088b4661/html5/thumbnails/16.jpg)
How to generate signals that matches close to DVB-T Application ?
• DVB-T systems can be used in either 2K or 8K mode. We choose 2K mode having :– 1705 sub-carriers are used to transmit the data
out of total 2048 sub-carriers – Inverse Fourier Transform (IFFT) of the QAM of the
data is taken and guard-band intervals are added at the start of OFDM frame for DVB-T applications
![Page 17: Analysis of OFDM Parameters Using Cyclostationary Spectrum Sensing](https://reader033.vdocuments.net/reader033/viewer/2022061106/5447ec46afaf9f41088b4661/html5/thumbnails/17.jpg)
How did we proceed ?
1. QAM modulation2. OFDM signal generation3. Cyclic Prefix addition at the guard-band
locations4. Incorporating AWGN channel5. Symbol Transmission through AWGN6. Signal Detection using DSS techniques7. Spectral Correlation Function of the received
function for better PSD and noise removal
![Page 18: Analysis of OFDM Parameters Using Cyclostationary Spectrum Sensing](https://reader033.vdocuments.net/reader033/viewer/2022061106/5447ec46afaf9f41088b4661/html5/thumbnails/18.jpg)
OFDM Signal Generation
QAM Mapping
Pilot Insertions
S-> P IFFT P -> S Cyclic Extension
Up conversionbitstream
Analog signal
QAM mapping is a block that groups these bits together as per modulation schemes:N=1 for BPSK, N=2 for QPSK and n-QAM for higher orders
![Page 19: Analysis of OFDM Parameters Using Cyclostationary Spectrum Sensing](https://reader033.vdocuments.net/reader033/viewer/2022061106/5447ec46afaf9f41088b4661/html5/thumbnails/19.jpg)
Some Maths behind OFDM signals• For a single carrier, the complex signal can be:• If we consider N samples, OFDM signal appears to be summation of these N
symbols
• During the symbol length, the amplitude and phase remains constant
• These carriers are centered around fo , the time domain representation becomes
Where T is the period of sampling frequency.• This can be represented in complex vector as
![Page 20: Analysis of OFDM Parameters Using Cyclostationary Spectrum Sensing](https://reader033.vdocuments.net/reader033/viewer/2022061106/5447ec46afaf9f41088b4661/html5/thumbnails/20.jpg)
Maths behind OFDM - continued• In last equation is the representation of complex components in
frequency domain• If we follow the IFFT transform, we can see that it is the summation of
orthogonal components in frequency domain
• The simplified complex form follows , where an and bn follows the modulation scheme, hence making:
• After complex vector multiplication, real signal part can be estimated as:
![Page 21: Analysis of OFDM Parameters Using Cyclostationary Spectrum Sensing](https://reader033.vdocuments.net/reader033/viewer/2022061106/5447ec46afaf9f41088b4661/html5/thumbnails/21.jpg)
Cyclic Extension
• Last serial samples are added to next OFDM frame by cyclic extension
• How its done ? Lets see some basics and maths behind cyclic extension and Spectral correlation function to see its significance
![Page 22: Analysis of OFDM Parameters Using Cyclostationary Spectrum Sensing](https://reader033.vdocuments.net/reader033/viewer/2022061106/5447ec46afaf9f41088b4661/html5/thumbnails/22.jpg)
Cyclostationary Features• A very simple periodic signal
• In terms of Fourier coefficients
• After modulation with a sine-wave
• Considering a is of random wide-sense spectrum nature, we can auto-correlate and can compute the power spectral density
• Auto-correlation of a • Power spectral density of a can be found by
• Keeping that in mind the Power Spectral Density of x(t) can be found by :
• Problem with the above equation ? No sine wave components presents
![Page 23: Analysis of OFDM Parameters Using Cyclostationary Spectrum Sensing](https://reader033.vdocuments.net/reader033/viewer/2022061106/5447ec46afaf9f41088b4661/html5/thumbnails/23.jpg)
Cyclostationary Feature - continued
• Lets use trigonometric identities in order to have:1. Some DC components2. Some higher order periodic components3. Simple depiction of modulated periodic symbol
A simple quadratic function
Which can be reduced to
Furthermore b(t) has a DC component that should appear at f=0
Also, the higher order components should also appear at
![Page 24: Analysis of OFDM Parameters Using Cyclostationary Spectrum Sensing](https://reader033.vdocuments.net/reader033/viewer/2022061106/5447ec46afaf9f41088b4661/html5/thumbnails/24.jpg)
Cyclostationary Feature - Continued
• So, if that is True, the PSD should appear as:
-fo foSy
-2fo 2fo
f
f
f
f
![Page 25: Analysis of OFDM Parameters Using Cyclostationary Spectrum Sensing](https://reader033.vdocuments.net/reader033/viewer/2022061106/5447ec46afaf9f41088b4661/html5/thumbnails/25.jpg)
Cyclostationary Feature - Continued
• Problem with previous depiction?– Not every symbol appears as a DC with some known higher order
components– In order to add random delays, we should come up with some pulse
modulation in order to have varying magnitudes.– So, we can only have a DC magnitude appearing at nth order but with no
varying magnitudes.
• Speculating that into consideration, the basic function becomes:
• Where spectral lines should appear at m.fo , where m is integer multiplier• If we equate m.fo as ἀ , we can define our approximation equation:• ἀt = m.fo for periodic
Time intervals
![Page 26: Analysis of OFDM Parameters Using Cyclostationary Spectrum Sensing](https://reader033.vdocuments.net/reader033/viewer/2022061106/5447ec46afaf9f41088b4661/html5/thumbnails/26.jpg)
Cyclostationary Feature - Continued
• Now with the assumptions we can say that the function is periodic if the delay product contains spectral lines; which can roughly be modeled as:
• The cyclic auto-correlation function can then proceed with the complex vector:
• Now the basic idea of Spectral Correlation function is to find average power in frequency domain
• The last approximations were to concentrate on the received signals at the center frequency as if they were passed through a narrowband filter
Where B is modeled as the bandwidth of the function for filtering
![Page 27: Analysis of OFDM Parameters Using Cyclostationary Spectrum Sensing](https://reader033.vdocuments.net/reader033/viewer/2022061106/5447ec46afaf9f41088b4661/html5/thumbnails/27.jpg)
f
x
u
v
f + ἀ/2 f + ἀ/2
+ ἀ/2
-ἀ/2
Spectral Correlation Density
• The spectral correlation density was computed by the Fourier Transform of the cyclic autocorrelation
BPF
BPF
X(t)
e-j2πἀt
j2πἀte
U(t)
v(t)
![Page 28: Analysis of OFDM Parameters Using Cyclostationary Spectrum Sensing](https://reader033.vdocuments.net/reader033/viewer/2022061106/5447ec46afaf9f41088b4661/html5/thumbnails/28.jpg)
Coding behind the project
Signal Generation
Serial Conversion
![Page 29: Analysis of OFDM Parameters Using Cyclostationary Spectrum Sensing](https://reader033.vdocuments.net/reader033/viewer/2022061106/5447ec46afaf9f41088b4661/html5/thumbnails/29.jpg)
Coding - Continued
Cyclic Prefix addition
Up-sampling for carrier
![Page 30: Analysis of OFDM Parameters Using Cyclostationary Spectrum Sensing](https://reader033.vdocuments.net/reader033/viewer/2022061106/5447ec46afaf9f41088b4661/html5/thumbnails/30.jpg)
Coding Continued
SCF Function
The Plots
![Page 31: Analysis of OFDM Parameters Using Cyclostationary Spectrum Sensing](https://reader033.vdocuments.net/reader033/viewer/2022061106/5447ec46afaf9f41088b4661/html5/thumbnails/31.jpg)
The Outcomes
The PSD of generic symbol received
![Page 32: Analysis of OFDM Parameters Using Cyclostationary Spectrum Sensing](https://reader033.vdocuments.net/reader033/viewer/2022061106/5447ec46afaf9f41088b4661/html5/thumbnails/32.jpg)
Outcomes - Continued
PSD while utilizing SCF
PSD without SCF
![Page 33: Analysis of OFDM Parameters Using Cyclostationary Spectrum Sensing](https://reader033.vdocuments.net/reader033/viewer/2022061106/5447ec46afaf9f41088b4661/html5/thumbnails/33.jpg)
Outcomes -Continued
Reduced noise-bed and detected primary and
secondary users around center frequency in the
presence of SCF
Detected primary and secondary users around centre frequency in the
absence of SCF