here concept of spectrum sensing in cognitive radio have been described.

1. COGINITIVE RADIO
PRESENTED BY:
Neha Singh
Roll No.-1405627503
M.TECH 2nd Year
UNDER THE GUIDANCE OF:
Dr. Himanshu Katiyar , Asso. Professor
Mr. Sanjay Sharma, Asso. Professor
ECE Department BBDNIIT
Dr. A.P.J. ABDUL KALAM TECHNICAL UNIVERSITY
LUCKNOW

2. CONTENT
 INTRODUCTION
 FUNCTION OF CRN
 LITERATURE SURVEY
 PROBLEM STATEMENT
 RESULT AND WORKDONE
 VALIDATION
 CONCLUSION AND FUTURE SCOPE
 REFERENCES

3. INTRODUCTION
 The fast growth of new wireless applications and services has resulted in increased
demand of radio spectrum access.
 But most of the radio spectrum is already allocated by fixed allocation policy and it
becomes difficult to find unallocated spectrum for these new upcoming applications
and services.
 As per the survey of Federal Communications Commission (FCC) up to 85% of the
assigned spectrum is underutilized.
 Cognitive radio (CR) has improve spectrum efficiency through intelligent spectrum
management technologies by allowing secondary users to temporarily access primary
users’ unutilized licensed spectrum.

4. FUNCTIONS OF CRN
 Spectrum sensing: Cognitive radio user has the ability to sense the unused spectrum at any
time and location.
 Spectrum management: Based on the availability of the spectrum and other policies, CR user
allocates the best available spectrum band.
 Spectrum mobility: CR user shall vacate the spectrum in the presence of any primary user
and move to next best available spectrum band
 Spectrum sharing: CR network has to provide a fair and optimal spectrum allocation method
among multiple CR users.

5. COGNITIVE RADIO CYCLE
Radio
Environment
Sensing
Awareness
Learning
Adaption
Response
Fig(1):-cycle of cognitive radio

6. LITERATURE SURVEY
 Cognitive radio is the key technology that enables next generation communication networks,
also known as dynamic spectrum access networks, to utilize the spectrum more efficiently in
an opportunistic fashion without interfering with the licensed users.
 Spectrum sensing is fundamental for the successful deployment of CRs.
 Sensing scheme is divided into two parts:-
• Improve local sensing
• Cooperative sensing between SU
 In CSS, SUs perform local sensing and send their sensed information to the fusion centre,
and a final cooperative decision is taken at the fusion centre.

7. LITERATURE SURVEY CONTINUED........
[2] Rahul Tandra , Shridhar Mubaraq Mishra and Anant Sahai, "What is spectrum hole and
what does it take to recognise one?? ", Dept. of Electrical Engineering and Computer
Sciences, U C Berkeley.
Inference: In this paper the concept of spectrum hole has been described.
 Spectrum holes” represent the potential opportunities for non-interfering (safe) use of
spectrum and can be considered as multidimensional regions within frequency, time, and
space.
 The main challenges arises for secondary radio systems is to be able to robustly sense when
they are within such a spectrum.

8. CONTI....
 Decision is taken on the basis of three parameters
 Probability of detection
 Probability of miss detection
 Probability of false alarm

9. VARIOUS SENSING TECHNIQUES
 Energy detection
 Matched filter detection
 Cyclostationary detection

10. LITERATURE SURVEY CONTINUED........
[3] Pooja Anand," OFDM Based Cooperative Sequential Spectrum Sensing'".
Interferenc: This paper defines the concept of local sensing schemes.
 When secondary user has a priori knowledge of primary user signal, matched filter detection is applied.
 Main purpose of this filter is to raise the signal component and decrease the noise component at the
same time .
Figure(2):-Block diagram of matched filter

11. LITERATURE SURVEY CONTINUED........
Figure(3):-block diagram of ED
[4]Waleed Ejaz, Najam ul Hasan and Hyung Seok Kim, "SNR-based Adaptive Spectrum
Sensing For Cognitive Radio Networks".
Inference: This paper deeply describe the concept of energy detection
The elementary approach behind this detector is the estimation of the power of the received
signal.
This is a simple technique that has short sensing time, but its performance is poor under low
Signal to Noise Ratio

12. LITERATURE SURVEY CONTINUED........
[5]Waleed Ejaz, Najam ulHasan, Muhammad Awais Azam, Hyung Seok Kim,"Improved local
spectrum sensing for cognitive radio networks".
Inference: SU can detect a random signal with a specific modulation type in the presence of
random stochastic noise by exploiting periodic statistics like the mean and the
autocorrelation of the PU waveform.
Figure(4):-block diagram of Cyclostationary detection

13. LITERATURE SURVEY CONTINUED........
[6]Waleed Ejaz1, Najam ul Hasan1, Seok Lee2 and Hyung Seok Kim1*,"I3S: Intelligent
spectrum sensing scheme for cognitive radio networks".
This paper define short concept of the available local spectrum sensing schemes.
 A two stage fuzzy logic detection
 A low power discrete Fourier transform (DFT) filter bank-based two-stage spectrum sensing
 SNR-based two-stage adaptive spectrum sensing
 A novel high-speed two-stage detector
 another two-stage sensing scheme
 An improved version of another two stage sensing time

14. LOCAL SENSING IMPROVEMENT
Reference[4]
 To improve cooperative performance, it is necessary to improve local sensing.
 Among no. Of methods to improve local sensing "a two-stage fuzzy logic-based detection (FLD)"
is shown .
Figure(5) :- Fuzzy Logic Detection

15. PROBLEM STATEMENT
 This scheme is used to improve the utilization efficiency of the radio spectrum
by increasing detection reliability and decreasing sensing time.

16. I3S SYSTEM MODEL
Figure (6):-Structure of I3S
[7]Anushka Das, Yamini Mehta, Raaz Parwani,Preeti Bhardwaj,Prof. Vijay Rughwani,"Survey Paper on
Spectrum Sensing Algorithm for Cognitive Radio Applications

17. SYSTEM ARCHITECTURE
[8]Ian F. Akyildiz, Won-Yeol Lee, Mehmet C. Vuran *, Shantidev Mohanty," NeXt
generation/dynamic spectrum access/cognitive radio wireless networks: A survey".
 We consider a CR network with N independent channels, where each channel has its own
high-priority and low-priority .
 It is assumed that there are N channels to be sensed. The SU will scan the whole spectrum and
detect whether or not there is a spectrum hole available.
 The SU identifies that a PU waveform is known (or not) on the basis of the power and band
of interest, and then selects either a combined energy and Cyclostationary detector, or a
matched filter detector.

18. Figure(7):- architecture of CRN (a) Cognitive radio transceiver, (b) Front End Architecture

19. PREVIOUS WORKDONE
The ROC curves of the I3S, matched filter detection, energy detection, and Cyclostationary detection.
Figure(8):- Result of Previous sensing

20. PROPOSED RESULT
Fig(9):- results proposed

21. CONCLUSION
 ROC of all the detection scheme has been plotted in previous graph.
 The above graph shown is between the probability of detection and probability of false
alarm.
 It gives reliable results with less mean detection time, depending on the prior knowledge of
PU waveform.
 It is concluded that for a specific value of average SNR, it gives low probability of false
alarm results in a high probability of detection.
 Its performance is best even in lower SNR value.
 I3S have the best result ,so it is more efficient then other detection techniques

22. FUTURE SCOPE
 Till now software implementation of the spectrum detectors have been proposed but we will
extend it to implement these detectors in hardware and use in real time systems.
 It can be more safe.
 Security can be enhanced.
 Clear assignments to deal with the transmit power, coding scheme, transmission rate to the
CR users can be devised .

23. REFERENCES
 [1] S. Haykin, “Cognitive Radio: Brain-Empowered Wireless Communication”, IEEE JSAC,
Feb 2005.
 [2] Rahul Tandra , Shridhar Mubaraq Mishra and Anant Sahai, "What is spectrum hole
and what does it take to recognise one?? ", Dept. of Electrical Engineering and Computer
Sciences, U C Berkeley", Dept. of Electrical Engineering and Computer Sciences, U C
Berkeley.
 [3]Pooja Anand," OFDM Based Cooperative Sequential Spectrum Sensing", International
Journal of Scientific & Engineering Research, Volume 6, Issue 4, April-2015 .
 [4]Waleed Ejaz, Najam ul Hasan and Hyung Seok Kim, "SNR-based Adaptive Spectrum
Sensing For Cognitive Radio Networks', International Journal of Innovative Computing,
Information and Control Volume 8, Number 9, September 2012.
 [5]Waleed Ejaz, Najam ulHasan, Muhammad Awais Azam, Hyung Seok Kim,"Improved
local spectrum sensing for cognitive radio networks ", EURASIP journal on advances in
signal proessing December 2012, 2012:242

24. CONTI.....
 [6]Waleed Ejaz1, Najam ul Hasan1, Seok Lee2 and Hyung Seok Kim1*,"I3S: Intelligent
spectrum sensing scheme for cognitive radio networks", Ejaz et al. EURASIP Journal on
Wireless Communications and Networking 2013, 2013:26.
 [7]Anushka Das, Yamini Mehta, Raaz Parwani,Preeti Bhardwaj,Prof. Vijay
Rughwani," Survey Paper on Spectrum Sensing Algorithm for Cognitive Radio
Applications International Journal of Advanced Research in Computer Engineering &
Technology (IJARCET) Volume 3 Issue 5, May 2014
 [8]Ian F. Akyildiz, Won-Yeol Lee, Mehmet C. Vuran *, Shantidev Mohanty,"NeXt
generation/dynamic spectrum access/cognitive radio wireless networks: A survey",
Broadband and Wireless Networking Laboratory, School of Electrical and Computer
Engineering ,Received 2 January 2006, accepted 2 May 2006.

25. THANK YOU!!!!!!
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