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  1. 1. Akshansh Kaushik, Amanpreet Singh Saini / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 Vol. 3, Issue 2, March -April 2013, pp.546-555 Performance Evaluation For Detection Of White Spaces In Cognitive-Ofdm Based Wireless Communications Networks Akshansh Kaushik*, Amanpreet Singh Saini** *PG student ,Department Of Electronics & Communication Engg. Galgotias College Of Engineering And Technology Greater Noida ,Uttar Pradesh (India)**Assistant Professor ,Department Of Electronics & Communication Engg. Galgotias College Of Engineering& Technology , Knowledge Park, Phase II, Greater Noida-201306Abstract-The radio electromagnetic spectrum is I. Introductionlimited source for many wireless communication A. BACKGROUNDdevices.many studies on wireless communication Many studies on wireless communication shows thatshow that a large portion of our radio the modern society has become dependent onelectromagnetic spectrum remains vacant all electromagnetic radio spectrum[1]. Notably, thetime .How this radio electromagnetic spectrum unlicensed bands (e.g., ISM and UNII) play ancan be utilized more ? cognitive radio is a important role in this wireless ecosystem since thesolution to this problem. The cognitive radio, uses of applications in these bands is unencumberedbased on a software-defined radio. Cognitive by regulatory delay sand which resulted in aradio is an advanced and intelligent wireless plethora of new applications including last-milecommunication system that is aware of its broadband wireless access, health care, wirelessenvironment and uses the methodology of PANs/LANs/MANs, and cordless phones. Thisunderstanding- by-building to learn from the unbelievable success of unlicensed operations andenvironment and adapt to statistical variations in the many advancements in technology that resultedthe input stimuli, with two primary objectives in from it, foces the regulatory bodies (e.g., the FCCmind: [2]) to consider opening further bands for unlicensed• there should be always highly reliability in use. Whereas, spectrum occupancy measurementscommunication network . [1] show the underutilization of licensed bands,• there should be proper utilization of the radio such as the TV bands. Cognitive Radios (CRs) arespectrum. seen as the solution to the current low usage of theMany research has proved that orthogonal radio spectrum. It is the main technology that willfrequency division multiplexing system (OFDM) enable flexible, efficient and reliable spectrum usehas been proposed as a main candidate for cr’s by adapting the radio’s operating characteristics tophysical layer. Additionally, performance of a the real-time conditions of the environment. CRswide band spectrum analysis can be supported have the potential to utilize the large amount ofby Fast Fourier Transform (FFT) in an OFDM unused spectrum in an intelligent way while notreceiver. Multitaper spectrum estimation method interfering with other incumbent devices in(MTM) is a non-coherent promising spectrum frequency bands already licensed for specific uses.sensing technique. It has solved the problems of CRs are enabled by the rapid and significantbad biasing and large variance in power advancements in radio technologies (e.g., software-spectrum estimation .Biasing and Variance are defined radios, frequency agility, power control,two important parameters to calculate etc.), and can be characterized by the utilization ofperformance evaluation of any power spectrum disruptive techniques such as wide-band spectrumestimation method. sensing, real-time spectrum allocation and acquisition, and real-time measurementkeywords-cognitive radio;fast fourier dissemination (please also refer to the DARPA neXttransform(fft) algorithm;multitaper Generation (XG) program RFCs [1] for a goodmethod;spectrum sensing,ofdm,awgn (additive overview of issues in and the potential of CRs)white gaussian noise) channel ,awareness,ieee Definition of cognitive radio as given [3].802.22,primary users ,secondary users,periodogram “An intelligent wireless communication system thatmethod, is aware of surrounding environment, and uses methodology of understanding-by-building to learn from the environment and adapt its internal states to corresponding changes in certain operating parameters (e.g. transmit power, carrier frequency, and modulation strategy) in real-time, with two primary objectives in mind: 546 | P a g e
  2. 2. Akshansh Kaushik, Amanpreet Singh Saini / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 Vol. 3, Issue 2, March -April 2013, pp.546-555  Highly reliable communications whenever and wherever needed;  Efficient utilization of the radio spectrum.B. THE IEEE 802.22 SYSTEMWhile US has played a major role towards thecommercial deployment of CRs, the IEEE 802.22 isgoaled to define an international standard that mayoperate in any regulatory regime. Therefore, thecurrent 802.22 project identifies the North Americanfrequency range of operation from 54-862 MHz,while there is an ongoing debate to extend the Figure 1. Exemplary 802.22 deploymentoperational range to 41-910 MHz as to meet configuration.additional international regulatory requirements.Also, the standard shall accommodate the various E. Service Coverageinternational TV channel bandwidths of 6, 7, and 8 BS coverage range is another distinctive feature ofMHz [22]. 802.22 WRAN as compared to existing IEEE 802 standards , which is proposed to go up to 100 Km if C. Entities ,Topology and Relationships power is not an issue (current specified coveragefixed point-to-multipoint (P-MP) wireless air range is 33 Km at 4 Watts CPE EIRP). As shown ininterface is used in the 802.22 system, uses a where Figure 2, coverage range of WRANs is much largera base station (BS) manages its own cell and all than today’s networks, which is primarily due to itsassociated Consumer Premise Equipments (CPEs), higher power and the favorable propagationas depicted in Figure 1. The BS (a professionally characteristics of TV frequency bands. This featureinstalled entity) controls the medium access in its of IEEE802.22 ,enhanced coverage range offerscell and transmits in the downstream direction to the unique technical challenges as well as opportunities.various CPEs, which respond back to the BS in theupstream direction. In addition to the traditional roleof a BS, it also manages a unique feature ofdistributed sensing. This is needed to ensure properincumbent protection and is managed by the BS,which instructs the various CPEs to performdistributed measurement of different TV channels.Based on the feedback received, the BS decideswhich steps, if any, are to be taken.D. Service CapacityThe 802.22 system specifies spectral efficiencies inthe range of 0.5 bit/(sec/Hz) up to 5 bit/(sec/Hz). Ifwe consider an average of 3 bits/sec/Hz, this wouldcorrespond to a total PHY data rate of 18 Mbps in a6 MHz TV channel. In order to obtain the minimumdata rate per CPE, a total of 12 simultaneous usershave been considered which leads to a requiredminimum peak throughput rate at edge of coverage Figure2. comparasion of IEEE 802.22 with otherof 1.5 Mbps per CPE in the downstream direction. popular wireless standards.In the upstream direction, a peak throughput of 384kbps is specified, which is comparable to DSL F. COGNITIVE CYCLEservices. Cognitive cycle is given in diagram 3 as in[3].A basic cognitive cycle comprises of following three basic tasks:  Spectrum Sensing  Spectrum Analysis  Spectrum Decision Making 547 | P a g e
  3. 3. Akshansh Kaushik, Amanpreet Singh Saini / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 Vol. 3, Issue 2, March -April 2013, pp.546-555 .which is mostely used in our spectrum sensing framework. Figure 3. Basic cognitive cycle. (The figure Figure 5. The unoccupied spectrum portionsfocuses on three fundamental cognitive tasks). (holes) at specific geographical location.G . IEEE 802.22 –Cognitive Radio Capabilitiescrepresents capabilities of cognitive radio are shownin following figure 4 [4]. Spectral Holes Figure 6. Pr User’s Signal Under Spectrum Sensing. I . Organization of this paper Section II describe spectrum sensing methods . partFigure 4. Cognitive Radio Capabilities. A and part B of section II describes the periodogram methods and multitaper methodsOur focus is on spectrum sensing. Tasks of spectrum theories .In part C theories for making roc diagramsensing involves the following subtasks as in [5]. is given .in section D MTM performance evaluation[1] detection of Spectral holes; in terms of many parameters is given .in section III[2] spectral resolution of each spectral hole; basics OFDM is given . With all of this background[3]estimation of spatial direction of incoming theory at hand ,the stage is set for an experimentalinterference; study of detection of spectral hole in section IV.This[4] signal classification; paper concludes with summary and discussion inThe subtask of spectral –hole detection is ,at its section Vsimpliest form,when focus is on white space II. Spectrum Sensing Methods(spectral holes) There are many methods for power estimation ofDefinition of spectral hole as in [2] signal . we have studied some of them for“A spectrum hole is a band of frequencies assigned identifying the presence of signal a primary user, but, at a particular time and These are as follows :specific geographic location, the band is not being  PERIODOGRAM METHODutilized by that user”  MULTITAPER METHODSpectral holes have three dimensions:the time ,the  AUTO CORRELATION BASEDfrequency,and the geographical location s as can be  SD COOPERATIVE BASED SENSINGseen in diagram 5. Diagram 6, represents spectral  CYCLOSTATIONARY BASEDholes in another fashion that is Psd Vs Frequency SENSING 548 | P a g e
  4. 4. Akshansh Kaushik, Amanpreet Singh Saini / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 Vol. 3, Issue 2, March -April 2013, pp.546-555 (B) For periodogram method we use theseA.Power Spectrum Estimation using formulaes for probability of detection andPERIODOGRAM method probability of false alarm as in [6]The spectrum estimation formula for periodogrampower spectrum estimation is given by as in [6][11]. 1 γ−L E s +𝜍 2 w 𝑆PE 𝑓𝑖 = 𝑁 ∣ 𝑡=0 𝑥 𝑡 𝑒 −𝑗 2𝜋𝑓 𝑖 𝑡 ∣2 (1) 𝑁−1 PE Pd (fi ) = Q( ) (6) 2L 𝜍 2 w (2E s +𝜍 2 w )periodogram estimate of desired signal shows morespectral leakages (more bias) and large variances . γ−L 𝜍 2 walso periodogram estimation is more contaminated PfPE (fi ) = Q (7) 2𝐿𝜍 4 wby noise,which is shown in section IV. (C) For Autocorrelation And Sd Cooperative Based Sensing Method we use these formulaes forB.Power Spectrum Estimation using probability of detection and probability of falseMULTITAPER METHOD alarm as in [6]Problems occurred in periodogram (BIAS- 𝜂 𝑙 −𝜌 1VARIANCE DILEMMA) estimation can be 𝑃 𝑑𝐴𝐶 = 𝑄( 2𝐿 𝐴𝐶 . 2 ) (8) 𝜌1resolved using MTM method [3] [5][6].Consider a finite time series {xt :t = 0,1,….N-1] 𝑃𝑓 𝐴𝐶 = 𝑄( 2𝐿 𝐴𝐶 . 𝜂 𝑙 ) (9)with discrete samples of a continuing time processthat represent the PR’s signal plus noise. 𝜂 𝑙 −𝜌 1Multiplying the samples with different DPSS 𝓥(t,k) 𝑃 𝑑𝐴𝐶 = 𝑄( 2𝐿 𝐴𝐶 . 2 ) (10) 𝜌1(N,W) (dot multiplication) represents convolution in η 𝑃𝑓𝑆𝐷 = 𝑄( 𝜍 𝑆𝐷 ) (11)the frequency domain . The FFT of the product is 𝑓0taken to compute the energy concentrated in thebandwidth(-W,W) and centred in a frequency f . By using this formulaes we find roc curves usingSince there are K orthonormal tapers, then, there matlab and we can see that mtm is better than anywill be K different eigenspectrums produced from other method.this process; this can be defined as [3] [ 5][6][7] This result is derived in section IV.[11]: D. MTM performance evaluation 𝑁−1 Now mainly MTM performance depends upon𝑌𝑘 𝑓𝑖 = 𝑡=0 𝒱 𝑡,𝑘 𝑁, 𝑊 𝑥 𝑡 𝑒 −𝑗 2𝜋𝑓 𝑖 𝑡 (2) number of tapper used and time bandwidth product. After fixing a particular values of these parametersThe spectrum estimate is given by the weighted we can also see performance of mtm in terms ofsums of the first few eigenspectrums 𝘠k (fi) many other parameters as in figure below.representing the largest eigenvalues 𝜆k(N,W), whichare produced from the first few K tapers, and isgiven by [2] [ 5][6][7] [11]: 𝑘−1 2 𝑘=0 𝜆 𝑘 (𝑁,𝑊)∣𝑌 𝑘 (𝑓 𝑖 )∣ 𝑆 𝑀𝑇𝑀 𝑓𝑖 = 𝑘−1 𝜆 (𝑁,𝑊) (3) 𝑘=0 𝑘C.Performance evaluation of various powerspectrum spectrum estimation methods using roccurvesUsing roc curves we can compare the detectionprobabilities of various power spectrum estimationmethods . Figure 7. MTM performance evaluation (A) For mtm method we use these formulaes expressions. for probability of detection and probability of false alarm as in [6] Figure 7 depicts that how and why multitaper method is more advanced and intelligent than any MTM γ−LK E s +𝜍 2 wPd (fi ) = Q( ) (4) other method.We shall use these periodogram 2LC 2 λ 𝜍 2 w (2E s +𝜍 2 w ) method ,multitaper method,detection probability and false alarm probability equations and expressions to γ−LK 𝜍 2 w describe many outcomes of our experimental study PfMTM (fi ) = Q( ) (5) in section IV . 2LC 2 λ 𝜍 4 w 549 | P a g e
  5. 5. Akshansh Kaushik, Amanpreet Singh Saini / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 Vol. 3, Issue 2, March -April 2013, pp.546-555III OFDM (ORTHOGONAL FREQUENCY DEVISION MULTIPLEXING) Why Ofdm is main candidate for cognitiveOfdm1 is promising candidate for cognitive radio .In radio?this section we shall study about ofdm. OFDM is Following diagram gives answer to this questionOrthogonal frequency-division multiplexing(OFDM) is a multicarrier modulation technique . In .OFDM, each carrier is orthogonal to all othercarriers. However, this condition is not alwaysmaintained in MCM. OFDM is an optimal versionof multicarrier transmission schemes. Aim ofdeveloping OFDM as a popular scheme forwideband digital communication, whether wirelessor over copper wires, used in applications such asdigital television and audio broadcasting, DSLbroadband internet access, wireless networks, and4G mobile communications.OFDM is essentiallyidentical to 1. coded OFDM (COFDM) 2. discrete multi-tone modulation (DMT),DMT a frequency-division multiplexing (FDM)scheme used as a digital multi-carrier modulationmethod. The word "coded" in coded OFDM comesfrom the use of forward error correction (FEC). Alarge number of closely spaced orthogonal sub-carrier signals are used to carry data on severalparallel data streams or channels. conventionalmodulation scheme (such as quadrature amplitudemodulation or phase-shift keying) is used formodulation of each sub-carrier similar toconventional single-carrier modulation schemes inthe same bandwidth. Figure 8 and Figure 9 describethe transceiver of ofdm and basics ofofdm[20][31][40][41][46] . Figure 10. Advantages of using OFDM with CR.Figure 8. Basic block diagram of OFDMtransceiver. 1 Ofdm is main multiplexing technique proposed for next generation communication networks. Mathematically, each carrier can be described as a complex wave: Sc(t) =Acej[ 𝝎nt+ 𝛷n(t)] The real signal is the real part of sc(t). Both Ac(t) and fc(t), the amplitude and phase of the carrier, can vary on a symbol by symbol basis. The values of the parameters are constant over the symbol duration period.OFDM consists of many carriers. Thus the complex signals ss(t) is represented by 1 𝑁−1 𝑆𝑧 𝑡 = 𝐴 𝑁 𝑡 𝑒 𝑗 𝑤 𝑛 𝑡+𝛷 𝑛 𝑡 Figure 9. basics of OFDM . 𝑁 𝑛 =0 Where 𝝎n=𝝎0+n 𝛥𝝎 550 | P a g e
  6. 6. Akshansh Kaushik, Amanpreet Singh Saini / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 Vol. 3, Issue 2, March -April 2013, pp.546-555 IV. EXAMPLE: OFDM SIGNAL estimation there are small variances and less bias .so A. Estimation Of Ofdm Signal we can detect spectral holes clearly and better peaks For our experimental study, we consider the ofdm as in figure 13. signal ,Which is generated in matlab as shown in Small variances Less bias (less spectral leakages) figure 11 . Figure 13. Multitaper estimate of ofdm signal. Now we pass this ofdm signal through AWGN Figure 11. Ofdm signal generation in matlab. channel at SNR=-10db .Generally there are more Now we make periodogram and multitaper channels in wireless communications like noise, estimates of this ofdm signal to find a better rayleigth fading,multipath fading etc.but here we estimator . consider only noise channel2.Large variances Greater spectral leakages (more bias) Figure 14. Periodogram Estimates Of Ofdm Signal At SNR= -10db. Figure 12. Periodogram estimate of ofdm signal. Here we can clearly see that in periodogram estimate 2 of ofdm signal there are large variances and more In our wireless communication system there are many types of we can not detect better peaks and also we Noises,like thermal noise,white noise,Johnson noise etc .but we shall consider additive White Gaussian noise in our literature. can not detect spectral holes in proper manner. Multitaper method solve this bias- variance dilemma .we can see this in mtm estimation that in mtm 551 | P a g e
  7. 7. Akshansh Kaushik, Amanpreet Singh Saini / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 Vol. 3, Issue 2, March -April 2013, pp.546-555Figure 15. Multitaper Estimate Of Ofdm Signal Figure 17. Comparasion Of Mtm AndAt SNR= -10db. Periodogram.We can clearly see that at this low snr value mtm Clearly in Figure 17 it can be viewed that mtm ismethod is giving better spectral resolution i.e, better giving better performance evaluation thanpeaks and the spectral we can say mtm is periodogram because it requires less number ofbetter than periodogram method .which is also given ofdm blocks for detection at low SNR values .Nowin [3][5][6][7]. Our main focus is comparasion of mtm is compared with autocorrelation and Sdmtm method and periodogram method . cooperative based sensing[6] to examine that whichB. Study of different power estimation power spectrum estimation method gives better techniques using roc curves spectral resolution.Now we shall see the performance evaluation ofmtm and other power spectrum estimation mehodsin terms of roc diagrams. At Pf=10% , Pd(detectionprobability) of mtm is better than Pd of periodogram. Figure 18. The Roc curves when MTM ,Auto. corr, and cooperative SD with G=2,and 3 CR users are used at AWGN with SNRs=-10dB and L=20.Figure 16. Comparasion Of Mtm And At different values of Pf , Pd for mtm is better thanPeriodogram. other methods, So we can finally say that mtm is better than any other methods . Now we shall seeNow performance of mtm is compared with how performance of mtm is affected by manyperiodogram in terms of number of ofdm blocks parameters , Now performance of mtm is evaluatedrequired for detecttion at lower SNR by fixing value of Pf at 5% and 10% at SNR=0db atvalues[6].Actualy noise affects the performances of both Pf values Pd is 100% in figure 19.any power estimation method at low SNRs. 552 | P a g e
  8. 8. Akshansh Kaushik, Amanpreet Singh Saini / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 Vol. 3, Issue 2, March -April 2013, pp.546-555Figure 19. Pd that meets Pf=5 % and 10% VsSNR at AWGN using MTM with NW=4, and data Figure 21. PDFs versus threshold of noise andtaper=5 and L=50 SAMPLES . noise added to signal cases for L=2 samples whenFigure 20 show that a threshold can be chosen in MTM is used with NW=4 and K=5 taper atorder to meet the specific probability of false alarm AWGN with SNR= -5db.and probability of detection at defined SNR level andL used in the spectrum sensing framework .This As we increase ofdm blocks from 2 to 100, We canfacility in mtm method make mtm more advanced easily detect that which is noise only and which isand intelligent power spectrum estimation noise +signal .so our detection is having more robustmethod.In mtm method we can get good ,better,best as we increase ofdm blocks in our experimentalcategories of spectral resolution by making some framework . Specral resolution is now better thanchanges in parameters. previous one. Figure 22. PDFs versus threshold of noise andFigure 20. Threshold versus Pd and Pf when mtm noise added to signal cases for L=100 sampleswith nw=4and 5tapers is used at AWGN with when MTM is used with NW=4 and K=5 taper atSNR=-7db and L=50 samples. AWGN with SNR= -5db.Now in figure 21 and figure 22 ,we can see effects ofofdm blocks on detection of signal [6]. When twoOfdm blocks are used, we can not easilydestinguishe between noise and noise only signal . 553 | P a g e
  9. 9. Akshansh Kaushik, Amanpreet Singh Saini / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 Vol. 3, Issue 2, March -April 2013, pp.546-555V . SUMMARY AND DISCUSSION Technology Royal Institute of TechnologyIn finding and then exploiting spectrum holes in (KTH)ofdm signal ,cognitive radio has the capability to [10] IEEE 80.22 web site:solve the underutilization of radio-spectrum when the following compelling [11] D. J. Thomson, "Spectrum estimation andpractical issues are recognized ,we begin to harmonic analysis," Proceedings of theappreciate the research and development challenges IEEE, vol. 70, pp. 1055-1096, 1982.involved in building and commercializing cognitive [12] Dr. Mary Ann Ingram Guillermo “OFDMradio : Simulation Using Matlab,Smart Antenna  underlying physics of radio propagation is Research Laboratory,”Faculty Advisor: complex,so nature of wireless channels is Acosta August, 2000 notoriously unreliable; [13] William C.Y.Lee “Mobile Cellular  The uncertainties surrounding the Telecommunications ANALOG AND availability of spectrum holes as they come DIGITAL SYSTEMS “Second Edition . and go; [14] THEODORE S.RAPPAPORT “ Wireless  The need for reliability in communication communication PRINCLES AND network whenever and wherever it is PRACTICES “Second Edition. needed. [15] Kiran Challapali, Dagnachew Birru, and Sai Shankar “IEEE 802.22: The First Worldwide Wireless Standard based onREFERENCES Cognitive Radios Carlos Cordeiro,” Philips [1] Carlos Cordeiro, Kiran Challapali, and Research USA Dagnachew Birru “ IEEE 802.22: An [16] zhongmin Wang “New Sampling And Introduction to the First Wireless Standard Detection Approaches For Compressed based on Cognitive Radios “Philips Sensing And Their Application To Ultra Research North America/Wireless Wideband Communications “ Communication and Networking Dept., [17] “Spectrum sensing and Spectrum shifting Briarcliff Manor, USA implementation in a Cognitive Radio based [2] Federal Communications Commission IEEE 802.22 Wireless Regional Area (FCC),“Spectrum Policy Task Force,” ET Network” Docket no. 02-135, November 15, 2002. [18] 802.22 Based On Crs,Lectures On [3] Simon Haykin “Cognitive Radio: Brain Cognitive Radio Empowered,”Life Fellow, IEEE [19] Kyou Woong Kim” Exploiting [4] IEEE 802.22 Wireless rans group “IEEE Cyclostationarity for Radio Environmental 802.22 Wireless Regional Area networks Awareness in Cognitive Radios enabling Rural Broadband Wireless “Dissertation submitted to the Faculty of Access Using Cognitive Radio the Virginia Polytechnic Institute and State Technology” USA University in partial fulfillment of the [5] Simon Haykin ,David J. Thomson, and requirements for the degree of Doctor of Jeffrey H. Reed,”Spectrum Sensing for Philosophy Cognitive Radio,”Life Fellow IEEE [20] OFDM-based Terrestrial Geolocation .ppt [6] Owayed A Alghamdi” Spectrum Sensing [21] Chandrasekhar Korumilli, Chakrapani And Cooperation IN Cognitive-Ofdm Gadde, I.Hemalatha “Performance Based Wireless Communications Analysis of Energy Detection Algorithm in Networks, “A phd thesis ,Plymouth U.K. Cognitive Radio “ [7] G. A. Prieto , R. L. Parker, D. J. Thomson, [22] Amanpreet Singh Saini “The Automated F. L. Vernon and R. L. Graham “Reducing Systems For Spectrum Occupancy the bias of multitaper spectrum estimates” Measurement And Channel Sounding IN Scripps Institution of Oceanography, ultra-wideband, Cognitive Communication, University of California San Diego, La And Networking “Master of Science in Jolla CA 92093, USA Mathematics and Electrical Engineering Statistics Department, Queens University, [23] "The OFCOM official web site; radio Kingston spectrum allocation chart of the UK, [ 8] Stephen J. Shellhammer “SPECTRUM avaliable [online]:," SENSING IN IEEE 802.22”, Http:// qualcomminc. Sandiego, CA 921 ukfat/. [9] Joseph Mitola III “Cognitive Radio, An [24] "The ofcom official web site, Integrated Agent Architecture for Software avaliable[online]:," Defined Radio ,”Dissertation Doctor of 554 | P a g e
  10. 10. Akshansh Kaushik, Amanpreet Singh Saini / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 Vol. 3, Issue 2, March -April 2013, pp.546-555[25] "The ITU official web site, OFDM/OQAM in Doubly Dispersive avaliable[online]:," Channels “, Senior Member, IEEE [42] Channel Sensing Based on Self-Signal[26] "FFT Windows Function: Limits on FFT Suppression (SSS).ppt Analysis," Bores Signal Processing [43] Kyou Woong Kim” Exploiting (Online: Cyclostationarity for Radio Environmental[27] Silpa S. Prasad, R. Gandhiraj, K.P. Awareness in Cognitive Radios “the Soman”Multi-User Spectrum Sensing Doctor of Philosophy thesis,Virginia based on Multi-Taper Method for Polytechnic Institute and State University Cognitive Environments Communication [44] Cognitive Ultra Wide Band (CUWB) Engineering Research Group, “Department Radio Implementation and Challenges of Electronics and communication [45] Roman Marsalek, Jiri Dvorak, Karel[28] Viswanath Honeywell “Spectrum Sensing Povalac, Jitka Pomenkova “Use Of Matlab for Cognitive Radios G,” Bangalore In The Multicarrier Signal Sensing,[29] Miguel López-Benítez and Fernando Optimization And Implementation “ “Improved Energy Detection Spectrum [46] E225C – Lecture 16 OFDM Introduction Sensing for Cognitive Radio” EE225C casadevallvdepartment of Signal Theory [47] Cognitive Radio: Brain-Inspired Wireless and communicationsvuniversitat Communications Simon Haykin mcmaster, Politècnica de Catalunya, Barcelona, Spain University Hamilton, Ontario, Canada[30] Signal Processing Box for use with [48] Software Testbed for Cognitive Radio MATLAB®, User’s Guide, Version6, 2. Networks: Work in Progress Simon Haykin[31] Identification And Classification Of Ofdm mcmaster, University Hamilton, Ontario, Based Signals Using Preamble Correlation Canada And Cyclostationary Feature Extraction [49] Analog and Digital communication by[32] Foundations of Cognitive Dynamic Simon Haykin . Systems Simon Haykin mcmaster, [50] S. shellhammer, s. shankar, R. tandra, and University Hamilton, Ontario, Canada j. tomcik, bperformance of power detector[33] Cognitive Dynamic Systems Simon Haykin sensors of dtv signals in ieee 802.22 Mcmaster University Hamilton, Ontario, wrans,[ in proc. 1st acm int. workshop Canada technol. policy access. spectrum (tapas), aug. 2006. [online]. available:[34] A Signal Detector for Cognitive Radio System Aldo Buccardo June 11, 2010 /10.1145/123488.1234392[ 35] Anurag Bansal ,Ms. Rita Mahajan [51] W.A.Gardner ” Spectrum sensing and “Building Cognitive Radio System Using Spectrum shifting implementation in a Matlab” Cognitive Radio based IEEE 802.22[36] Chandrasekhar Korumilli, Chakrapani Wireless Regional Area Network” Gadde, I.Hemalatha ”Performance [52] R. Tandra, S. M. Mishra, and A. Sahai, Analysis of Energy Detection Algorithm in “what is a spectrum hole and what does it Cognitive Radio “ take to recognize one?” Proc. IEEE, vol.[37] Systems Pedram Paysarvi Hoseini and 97, Mar. 2009 Norman C. Beaulieu Icore “An Optimal [53] Silpa S. Prasad, R. Gandhiraj, K.P. Soman Algorithm for Wideband Spectrum Sensing “Multi-User Spectrum Sensing based on in Cognitive Radio “Wireless Commun. Multi-Taper Method for Cognitive Lab., Dept. Elec. & Comp. Eng., Environments “ University of Alberta Edmonton, Alberta [54] S.O.Rice,”A Short Table of Values of T6G 2V4 Canada Prolate Spheriodal Harmonics,”Bell[38] Sequential Detection based Cooperative Telephone Labs.,MM63-3241-13,1963 Spectrum Sensing Algorithms in Cognitive [55] A.F.Molisch,L.J.Greenstein, and .shafi , Radio ”propogation issues for cognitive radio,”[39] Vinod Sharma and arunkumar Proc.IEEE,vol.97.May 2009 Jayaprakasam “An Efficient Algorithm for Cooperative Spectrum Sensing in Cognitive Radio Networks “[40] Dong Chen,Jiandong Li “On The Performance Of in-Band Sensing Without Quiet Period in Ofdm System,”russia[41] Jinfeng Du, and Svante Signell “Comparison of CP-OFDM and 555 | P a g e