MULTI-STAGES CO-OPERATIVE/NON- COOPERATIVE SCHEMES OF SPECTRUM SENSING FOR COGNITIVE RADIO SYSTEMS

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1 MULTI-STAGES CO-OERATIVE/NON- COOERATIVE SCHEMES OF SECTRUM SENSING FOR COGNITIVE RADIO SYSTEMS Anwar Mousa 1 an Tara Javii 2 University o Caliornia, San Diego (UCSD)- Jacobs School o Engineering 9500 Gilman Dr., La Jolla, CA Abstract Searching or spectrum holes in practical wireless channels where primary users experience multipath aing an shaowing, with noise uncertainty, limits the etection perormance signiicantly. Moreover, the etection challenge will be tougher when ierent ban types have to be sense, with ierent signal an spectral characteristics, an probably overlapping spectra. Besies, primary user waveorms can be known (completely or partially) or unknown to allow or orbi cognitive raios to use speciic kins o etection schemes! Hien primary user s problem, an oubly selective channel oblige the use o cooperative sensing to exploit the spatial iversity in the observations o spatially locate cognitive raio users. Incorporate all the aorementione practical challenges as a whole, this paper evelope a new multistage etection scheme that intelligently ecies the etection algorithm base on power, noise, banwith an knowlege o the signal o interest. The propose scheme switches between iniviual an cooperative sensing an among eature base sensing techniques (cyclo-stationary etection an matche ilter) an sub-ban energy etection accoring to the characteristics o signal an ban o interest.compare to the existing schemes, perormance evaluations show reliable results in terms o probabilities o etection an mean sensing times uner the aorementione conitions. Keywors spectrum sensing,local an cooperative,cognitive raio, sub-ban energy etection, probability o etection, mean etection time 1. INTRODUCTION AND RELATED WORK Spectrum sensing can be iniviual into (non-cooperative) or cooperative [1]. In iniviual sensing, each cognitive raio (CR) perorms spectrum sensing locally on the receive signal an makes a ecision about the presence or absence o a primary user (U). However,in cooperative sensing, CRs perorm iniviual sensing an irect their ecisions or sense inormation to a usion center, an a inal cooperative ecision is taken at the usion center. Hence, to increase the eectiveness o cooperative perormance, it is necessary irst to improve iniviual sensing. DOI: /ijwmn

2 Iniviual sensing or single CR user, can be generallyclassiie as matche ilter etection, energy etection, cyclostationary eature etection,wavelet etection, multi antenna base sensing, eigenvalue base sensing an sub-nyquist wieban base sensing.a matche ilter (MF) is optimal to signal etection in the presence o AWGN as it maximizes the receive signal to noise ratio (SNR) an takes minimum sensing time. That isthanks to a complete knowlege o primary user signal that shoul be available to the MF etector. I CR is operating in ew U bans, then MF is the best choice, but i the number o operating U bans will increase, then practically, it is iicult to use MF because eicate circuitry is essential or each U licensee to achieve synchronization.conventional Energy Detection (ED) is generally aopte or spectrum sensing because it oes not nee a priori inormation o the primary signal an enjoys low computational an implementation complexities.however, one o the major shortcomings o the ED is its poor perormance when SNR alls below a certain threshol known as the SNR wall,that epens on noise uncertainty. However, Sub-ban Base Energy Detection (SBED) [2]uses spectrum analysis techniques that make it possible to etect rapily the spectral holes in a wie requency ban or CR operation. The most basic an computationally eective technique or spectrum analysis is block-wise FFT or AFB (analysis ilter bank) processing o the observe signal an measuring the power o each sub-ban. From the sensing point o view, when the channel is wie an requency selective, AFB ivies it into small an lat sub-ban an optimize weighting process can be ae to combat the eect o requency selectivity, making it possible or reliable sensing even in low SNIR. Cyclostationary eature etection (CS) has capability to isolate noise rom useul signal, so it can work well uner low SNR but requires some prior inormation o the primary user signal[3]. On the other han, it suers rom high computational complexity an long sensing time. Wavelet etection is eicient or wieban signal but suers also rom high computational complexity. Eigenvalue base sensing oes not nee noise variance inormation an is consiere as a possible solution to the challenging noise uncertainty conitions. Likewise, multi antenna base sensing, utilizing spatial correlations o U signals, is consiere an alternate metho to aor robustness against the noise uncertainty eects, however, it suers rom increase harware an computational complexity. Sub-Nyquist wieban base sensing is base on compressive sensing an multichannel sub-nyquist sampling techniques [4]. It reers to the proceure o employing sampling rates lower than the Nyquist rate an etecting spectrumholes using these partial measurements. SNR-base two-stage aaptive spectrum sensing is propose in [5]. In the irst stage, the SNR is estimate or available channels. The CR then perorms either ED or one-orer CS etection base on the SNR estimate in the irst stage o U etection. Simulation results showe that reliable results can be attaine with less mean etection time. In [6] the authors propose a spectrum sensing scheme which obtains reliable results with less mean etection time. First, the scheme etermines a better matche ilter, or a combination o ED an CS base on the power an ban o interest. An ED with a bi-threshol is use, an the CSetector is applie only i the energy o the signal lies between two threshols. Secon, sensing is perorme by the selection choice resulting rom the irst step. The istinction o the propose scheme is that it eals with multiple types o primary systems, i.e., or Us with known an unknown waveorms. However, all the existing two-stage etection schemes in the literature only consiere single type o primary system. Similarly, in [7] an aaptive local spectrum sensing scheme is propose. First, 2

3 the channels available in the banwith o interest are sense serially. The scheme etermines a better MF, or a combination o ED an CSetectors base on the available inormation o the signal present in the channel. The concept o SNR wall was also iscusse or ED. One-orer CS etection is perorme in time omain in place o CS in requency omain so that real-time operation an low-computational complexity can be accomplishe. Likewise, a two-stage spectrum sensing scheme is also propose in [8], in which the ED is use at the irst stage to sort channels in ascening orer base on the power o each. The one-orer CS is use on the channel with the lowest power to etect weak signals in the secon stage. The authors [9] in propose two novel schemes o two stage spectrum sensing or CR uner environment as noise power uncertainty. The two-stage spectrum sensing technique combines two conventional spectrum sensing methos to perorm sensing by exploiting their iniviual avantages. However, in [10], authors propose a two-stage uzzy logic-base sensing where the output rom each technique employe in the irst stage is combine in the secon stage using a uzzy logic to make the inal ecision. Likewise, [11] propose high-spee two-stage etector base on an ED. I the measure energy is greater than a speciic threshol then U present is ecie in the irst stage, else SNR is compute where i it is greater than another SNR threshol, then the result is still vali. Otherwise, then secon stage is perorme base on covariance absolute value. In [12] an ED is use in the irst stage to estimates the SNR, base on which, it eclares the absence or presence o a U at the irst stage, otherwise it runs the secon stage to have aprecise ecision. Noise uncertainty, multipath aing an shaowing, which are characteristics o practical wireless channels, egrae the etection perormance in iniviual spectrum sensing signiicantly. As an alternative solution to overcome the challenges o practical environments, cooperative sensing has been broaly stuie in the literature as a metho to improve the sensing perormance. Besies, Hien U problem, which appears when the U is not etectable by the sensing station, e.g., ue to shaowing, can be solve [13]. The main iea o cooperative sensing is to enhance the sensing perormance by using the spatial iversity in the observations o spatially locate CR users.by cooperation, CR users can share their sensing inormation or making a combine ecision more precise than the iniviual ecisions. In [14],the authors consiere a multichannel CR network, where cooperative CRs have heterogeneous sensing ability in terms o their sensing accuracy. They employe a group-base cooperative sensing scheme in which cooperating CRs are groupe such that ierent groups are responsible or sensing ierent channels. The perormance enhancement ue to spatial iversity is calle cooperative gain. On the other han, the cooperation overhea enotestheaitional sensing time, elay, energy, an operations eicate to cooperative sensing, compare to the iniviual (non-cooperative) spectrum sensing case[15]. More speciically, the elay overheas in cooperative sensing are aresse as: Sensing elay, epens on the employesensing metho. The sensing time is proportional to the number o samples use by the signal etector where the longer the sensing time is, the better the perormance will be. However, ue to the harware restriction that a single RF transceiver exists in each CR equipment, user cannot perorm etection an transmissions in the same time. The more time is eicate to sensing, the less time is available or transmissions an thus reucing the CR user throughput. This is known as the sensing eiciency problem [16] or the sensing-throughput traeo in spectrum sensing. In[17], the sensing-throughput traeo is ormulate as an optimization problem to maximize the average CR throughput uner the presence an the absence o Us. 3

4 Reporting elay, in cooperative sensing, sharing local sensing ata with other CR users an/or the FC (Fusion Center) yiels reporting elay. This is part o cooperation overhea as it oes not exist in non-cooperative spectrum sensing. In aition to transmission elay rom the cooperating CR users to the FC, there are many causes that result in reporting elay. First, i cooperating CR users transmit on a control channel by a ranom access scheme, it is probable that the control messages sent rom ierent CR users collie an then retransmission is requeste. Besies, sening the sensing ata by multiple hops, as the case in the relay-assiste cooperative sensing yiels extra reporting elay. In[18], the authors aresse the issue o cooperation processing traeo in cooperative sensing. The traeo is ormulate as an optimization problem to minimize the total sensing time subject to constraints o etection an alse alarm probabilities. Synchronization elays, the synchronization o all the cooperating users is neee in many cooperative sensing schemes that epen on simultaneous reporting o the CR users. However, the synchronization may not be easily accomplishe or a large amount o CR users. Hence, many asynchronous cooperative sensing methos are proposein [19] to treat this problem roblem Statement Searching or spectrum holes in practical wireless channels where U s experience multipath aing an shaowing, with noise uncertainty, limits the etection perormance signiicantly.the etection challenge will be tougher when ierent ban types have to be sense, with ierent signal an spectral characteristics, an possibly overlapping spectra. Each ban can be narrow or wie, lat or requency selective, experiencing AWGN or Rayleigh channel. Besies, U waveorms can be known (completely or partially) or unknown to allow or orbi CRs to use speciic kins o etection schemes! Moreover, Hien U problem, an oubly selective channel oblige the use o cooperative sensing an exploit the spatial iversity in the observations o spatially locate CR users. However, accoring to the author s best knowlege, none o the existing approaches in literature have incorporate all the aorementione practical challenges as a whole; all the existing multistage etection schemes in the literature only consiere single type o primary system with single type o channel conition! The propose solutions to the above challenges will ocus on: Developing aaptive Co-operative/non-cooperative multi-stage schemes o spectrum sensing. Cooperative sensing has been wiely stuie in the literature as a metho to combat eects o multipath aing an hien U problem by exploiting space iversity o the U s. Switching between iniviual an cooperative sensing an switching amongeature base sensing techniques (cyclo-stationary etection an matche ilter)ansubban Energy Detection accoring to the characteristics o signal an ban o interest. 4

5 Hence, the istinction o the propose multi-stage etection scheme is that it eals with: First,almost alltypes o Us signals an bans o interest. Secon, it tries to etect signals experiencing practical wireless channels. Thir, the propose multi-stage scheme intelligently ecies the etection algorithm base on the power, noise, banwith an knowlege o signal o interest, thus increasing accuracy an reucing mean etection time or the overall etection process.the remainer o this article is organize as ollows. Section 2etails system moel an the propose new aaptive multi-stage scheme. Section 3escribes the consiere setting an simulation parameters. Section 4 analyzes the achieve numerical results an Section 5 conclues the paper. 2.System Moel an ropose New Aaptive Multi-Stage Scheme 2.1.System Moel We consier M, CRs trying to etect K, Us o ierent signal types, with ierent spectral characteristics, an possibly overlapping spectra, uner various channel conitions. Each ban can be narrow or wie, lat or requency selective, experiencing AWGN or Rayleigh channel. The M, CRs an the K, Us are sprea in a coexisting coverage area. A blocking objects may exist to make hien Us to some CRs where some CR acts as relay to etect hien ones. Some CRs acts as usion center or cooperation sensing. To ecrease harware complexity o CRs, every CR, rather than the usion center, is equippe with only one speciic type o etector. I the aaptive moel chooses a speciic type o etection, then the usion center will orer the CR which is equippe with that etector to perorm sensing. Figure 1 shows the moel or M=4 an K=8 where CR-1 is a usion center. Figure 1: System Moel 5

6 2.2.ropose New Aaptive Multi-Stage Scheme The propose scheme is shown in Figure 2. the CRs will perorm comprehensive test o the observe signal o interest beginning bymeasuring the SNIR. In the irst stage, the scheme will check whether the SNIR value o the U signal o interest is greater than or equal to the SNIR wall,,[20]. I so, the scheme will perorm non-cooperative sensing. Otherwise cooperative sensing is perorme. I the SNIR o U signals is below the SNR wall, the etection perormance cannot be improve by increasing the sensitivity. Fortunately, thesensitivity requirement an the harware limitation issuescan be consierably relieve by cooperative sensing. In the secon stage, the scheme checks whether the observe signal is wieban or narrow ban. I narrow ban signal an non-cooperative, the scheme will check again in a thir stage whether complete or even partial knowlege o U waveorm is available to perorm matche ilter (MF) etection. The intuition behin the MF relies on the prior knowlege o a U waveorm, such as moulation type, orer, the pulse shape, an the packet ormat. I this is true, then MF etection is perorme as local (non-cooperative) ecision. No nee to pass thru the ourth stage since the threshol T is less than an the SNIR alreay excees. However, i the U waveorm is unknown, then the thir stage will work in perorming sub-ban energy etection(sbed) uner non-lat spectral characteristics as local (non-cooperative) ecision. SBED, base on FFT/AFB, works or both wie an narrow ban signals[2]. In the secon stage, i the observe signal is wieban an non-cooperative, the scheme will also perorm sub-ban energy etection as this sensing metho is suitable or wieban signals. On the other han, i the SNIR <, then cooperative sensing is chosen, an the secon stage will test the wieness o the signal ban. I it is wie, then cooperative SBED is perorme an the result is sent to the usion center. On the other han, i the signal ban is narrow, then a thir stage test or the signal is perorme by checking whether complete or even partial knowlege o U waveorm is available to perorm cooperative MF etection. I the signal is known enough, then a ourth stage test is carrie out to ensure that the signal SNIR is greater than a threshol T m. The intuition behin the threshol T m is to ensure that the SNIR is aequate or goo perormance o the MF. Note that the perormance o the MF is relatively poor below certain SNIR[21]. I so, then cooperative MF etection is perorme an the result is sent to the usion center. I not, then cooperative one-orer cyclo-statioary(oocs) etection is perorme. One-orer cyclo-stationary etection is chosen although the perormance o higher orer cyclo-stationary etection is a bit better than that o one-orer etection. The gain o higher orers is ue to harware complexity an power consume by aitional multiplying algorithm[22]. For commercial implementation o CRs, it is necessary to minimize harware complexity an power consumption. Thereore, the OOCS etection will be use instea o the higher-orer cyclo-stationary etection. On the other han, i the U waveorm is unknown, then cooperative OOCS etection is also perorme an the result is sent to the usion center. 6

7 2.3.erormance Metrics Figure 2: A ropose Aaptive Sensing Moel To evaluate the scheme s perormance, the results will be partiallycompare with those where only one type o etector exists. That is because no speciic etector can accommoate ierent ban types with ierent signal, channel an spectral characteristics as the propose aaptive multi-stage scheme oes. The perormance metrics are the probability o etection, probability o alse alarm, an mean overall etection time. robability o etection, shown as ( 1/ 1) i.e. probability o successul ecision o the spectrum sensing process. Actually it conirms the presence o U signal in a channel on the basis o ecision o the spectrum sensing schemes. 7

8 robability o alse alarm, shown as ( 1/ 0) i.e. probability o unsuccessul an alse ecision o the spectrum sensing process. In other wors, it shows that U signal is present in a channel while the channel is vacant. Mean overall etection timet, eine as the mean time or etecting all available bans with ierent etectors, wither iniviually or cooperatively in the propose multi-stage scheme. Knowing that alse alarms reuce spectral eiciency an miss etection causes intererence with the U, it is vital or optimal etection perormance that maximum probability o etection is accomplishe subject to minimum probability o alse alarm. Relative to IEEE stanar Error! Reerence source not oun., must be <= 0.1 an >= 0.9. The overall an o the propose scheme, Figure 2, are erive as ollow: = 1, nco + ( 1 1 ), co (1) = + ( 1 (2) 1, nco 1), co is the probability that channel woul be sense by the non-cooperative etections(probability 1 that SNR ), hence ( 1 1 ) is the probability that channel woul be sense by the cooperative etection., nco an, co are the probabilities or non-cooperative an cooperative etectionsrespectively. Similarly,, nco an, co are the probabilities or non-cooperative an cooperative alse alarm respectively., co = 2, ED ), co NB, co = 2, ED ), co NB ( (3) ( (4) is the probability that the U signal in interest is wieban, hence 2 ( 1 2 ) is the probability that the U signal in interest is narrowban., ED an, ED are the probabilities o etection an o alse alarm, or energy etector, respectively., co NB an, co NB are the probabilities o etection an o alse alarm, or cooperative etections when the signal is narrowban, respectively., nco = 2, nco WB ), nco NB, nco = 2, nco WB ), nco NB ( (5) ( (6), nco WB an nco WB, are the probabilities o etection an o alse alarm, or non-cooperative etections when the signal is wieban, respectively. 8

9 , nco NB an nco NB Similarly,, are the probabilities o etection an o alse alarm, or noncooperative etections when the signal is narrowban, respectively., nco NB = 3, MF + ( 1 3 ), ED, nco NB = 3, MF + ( 1 3 ), ED (7) (8), MF an MF, are the probabilities o etection an o alse alarm, or matche ilter, respectively. 3 is the probability o complete knowlege o U signal, yieling matche ilter etection an 1 ) is the probability o unknown U signal. ( 3, nco WB =, ED, nco WB =, ED, co NB = 3 4, MF + ( 1 3 ), CYC + 3 (1 4 ), CYC, co NB = 3 4, MF + ( 1 3 ), CYC + 3 (1 4 ), CYC (9) (10) (11) (12) Here,, co NB an co NB, are the probabilities o etection an o alse alarm, or cooperative etections when the signal is narrowban, respectively. 4 is the probability that the SNIR is greater than T, yieling cooperative matche ilter etection o U signal an ( 1 4 ) return the U signal or cooperative cyclo-statioaryetection. The overall probability o etection an probability o alse alarm o the propose scheme become: The overall mean etection time T o the propose sensing scheme is: T = T nco + T co (15) T + T co = TCYCLO + TMF CO + TED CO + TR TS (16) nco = T T (17) MF NCO + ED NCO WhereT nco an Tco are the mean etection times or non-cooperative an cooperative etections respectively. TMF CO, TED CO an T CYCLO are the sensing times o cooperative matche ilter etection, cooperative energy etection an one-orer cyclostationary etection, respectively. 9

10 Similarly, TMF NCO, TED NCO are the sensing times o non-cooperative matche ilter etection an non-cooperative energy etection. In case o cooperative sensing, TR is the reporting elay an TS is the synchronization elay. T cyclo is erive as ollows: T T cyclo = NTcyclo 1 cyclo [( 1 1 )(1 2 )(1 3 ) + (1 1 )(1 2 ) 3 (1 4)] = NTcyclo 1[( 1 1 )(1 2 )(1 3 4 )] (19) where Tcyclo 1 is the mean sensing time or each channel by the one-orer cyclostationaryetector. M C1 T cyclo 1 = in which M C1 is the number o samples or etection, an W c1 is the channel 2W c 1 banwith. Similarly, (18) TMF CO an ED CO T are erive as ollows: T T MF CO = NTMF 1 ED [( 1 1 )(1 2 ) 3 4] CO = NTED 1[( 1 1 ) 2 ] (21) where TMF 1 is the mean sensing time or each channel by the matche ilter etector. M m T MF 1 2W in which M m is the number o samples or etection, an W m is the channel m banwith. T ED 1 is the mean sensing time or each channel by the energy etector. M e TED 1 = in which M e is the number o samples or etection, an W e is the channel 2We banwith. Likewise, T T MF ED NCO = NTMF 1[ 1 (1 2 ) 3 ] (22) NCO = NTED 1[ (1 2 )(1 3 )] (23) The overall mean etection time o the propose scheme: (20) 10

11 The ollowing two cases can be mae on the basis o 1, the probability that SNR. Case 1: When 0 1 <0.5 or the majority o the channels,snir<. Thereore, the CRwill perorm cooperative etection or sensing the majority o the channels because cooperative sensing is an eicient approach to combat multipath aing an shaowing an mitigate the receiver uncertainty problem etection encountereat low SNR. When 0, then the probability 1 o etection, the probability o alse alarm, an the mean etection time can be oun by putting 0 ineq.s(13), (14) an (24), respectively: 1 = + (1 )[ + (1 ) ) + (1 ) ]) (25) ( 2, ED 2 3 4, MF 3 4, CYC 3, CYC ( 2, ED + (1 2 )[ 3 4, MF + 3 (1 4 ), CYC) + (1 3 ), CYC = ]) (26) T + T + T = N( Tcyclo 1 [( 1 2 )( 1 3 4)] + TMF 1[( 1 2 ) 3 4] + TED 1 2) R S (27) Base on case 1, especially when 1 0, the ollowing two subcases can be mae on the basis o 2 : Subcase 1.1:When or the majority o the channels, WB signal. Thereore, the CR will perorm ED etection or sensing most o the channels. ED is suitable or etecting wieban signals. When 2 1, (Coop-WB, 1=0,2=1)then the probability o etection, the probability o alse alarm, an the mean etection time can be oun by putting 2 1 in Eq.s (25), (26) an (27), respectively:, ED, ED = (28) = (29) T = NTED 1 + TR + TS (30) Subcase 1.2:When or the majority o the channels, NB signal. Thereore, the CR will procee in thir stage an ourth stage tests. When 2 0, (Coop-NB, 1=0,2=0)then the probability o etection, the probability o alse alarm, an the mean etection time can be oun by putting 2 0in Eq.s (25), (26) an (27), respectively: 3 4, MF +( 1 3 4), CYC 3 4, MF +( 1 3 4), CYC = (31) = (32) T + = N( Tcyclo 1 [( 1 3 4)] + TMF 1[ 3 4]) + TR TS (33) Base on Subcase 1.2, especially when 2 0, the ollowing two subcases can be mae on the basis o 3 : 11

12 Subcase 1.2.1:When or the majority o the channels, unknown signals. Thereore, the CR will not be able to etect most o signals by matche ilter an hence, will perorm cyclostationaryetection or sensing most o the channels. When 3 0, (Coop-NB, 1=0,2=0, 3=0-Cyc)then the probability o etection, the probability o alse alarm, an the mean etection time can be oun by putting 3 0 in Eq.s (31), (32) an (33), respectively:, CYC, CYC = (34) = (35) T = NT 1 + T + T (36) cyclo R S Subcase 1.2.2: When or the majority o the channels; known signals. Thereore, the CR will be able to etect the majority o signals by MF i the SNIR is greater than T. Thereore, the CR will procee in the ourth stage tests.when 3 1, (Coop-NB, 1=0,2=0, 3=1) then the probability o etection, the probability o alse alarm, an the mean etection time can be erive by putting 3 1 in Eq.s (31), (32) an (33), respectively: 4, MF + ( 1 4 ), CYC 4, MF + ( 1 4 ), CYC = (37) = (38) T + = N( Tcyclo 1 [( 1 4 )] + TMF 1[ 4 ]) + TR TS (39) Base on Subcase 1.2.2, especially when 3 1, the ollowing two subcases can be mae on the basis o 4 : Subcase :When or the majority o the channels, the CR will perorm cyclostationaryetection or sensing the majority o the channels since the SNIR is not suitable or using the matche ilter. When 4 0, (COO-NB, 1=0,2=0, 3=1,4=0,CYC) an the probability o etection, the probability o alse alarm, an the mean etection time can be erive by putting 4 0 in Eq.s (37), (38) an (39), respectively:, CYC, CYC = (40) = (41) T = NT 1 + T + T (42) cyclo R S Subcase :When or the majority o the channels, the SU will perorm MFetection or sensing the majority o the channels. The mean etection time o the MF etection is the least, an thereore the best case or the etection time is when the majority o channels are sense by the MF. The best scenario is when 4 0, (COO-NB, 1=0,2=0, 3=1,4=1,MF)an the probability o etection, the probability o alse alarm, an the mean etection time can be oun by putting 4 1 in Eq.s(37), (38) an (39), respectively: 12

13 , MF, MF International Journal o Wireless & Mobile Networks (IJWMN) Vol. 8, No. 4, August 2016 = (43) = (44) T = NT 1 + T + T (45) MF R S Case 2: When <1 or the majority o the channels,snr ( NON-COO sensing). Thereore, the CR will perorm noncooperative sensing an the algorithm will procee in testing the banwith o the signal in the secon stage. When 1, then the probability o etection, the 1 probability o alse alarm, an the mean etection time can be oun by putting 1 in Eq.s 1 ((13), (14) an (24), respectively: = + (1 ) + (1 )(1 ) ) (46) ( 2, ED 2 3, MF 2 3, ED ( 2, ED + (1 2 ) 3, MF + (1 2 )(1 3 ), ED = ) (47) T = N( TMF 3 1[( 1 2 ) 3 ] + TED 1[ 2 + (1 2 )( 1 )]) (48) Base on case 2, especially when 1 1, the ollowing two subcases can be mae on the basis o 2, the probability o wie banwith o U signal: Subcase 2.1:When or the majority o the channels, the U waveorm is WB. Thereore, CR will perorm noncooperativeed etection or sensing most o the channels. ED is suitable or etecting wieban signals. When 2 1, (noncoop-wb, 1=1,2=1) then the probability o etection, the probability o alse alarm, an the mean etection time can be oun by putting 2 1 in Eq.s (46), (47) an (48), respectively:, ED, ED = (49) = (50) T = NT ED 1 (51) Subcase 2.2:When 0 2 <0.5 or most o the channels, the U waveorm is NB. The CR will go to the thir stage to test the signal knowlege. The probability o alse alarm, an the mean etection time can be evaluate by putting 2 0 in Eq.s(46), (47) an (48), respectively: = + (1 ) ) (52) ( 3, MF 3, ED ( 3, MF + (1 3 ), ED = ) (53) T = N( TMF 1[ 3 ] + TED 1[( 1 3 )]) (54) Base on subcase 2.2, especially when ( 1 1, 2 0), the ollowing two subcases can be mae on the basis o 3, the probability o complete knowlege o U signal. Note that the algorithm oes not nee to perorm the ourth stage test since the SNIR is alreay greater than. Which is greater than the threshol T: 13

14 Subcase 2.2.1:When 0 3 <0.5 or most o the channels, the U waveorm is unknown. Thenthe CR will perorm noncooperativeenergy etection or sensing the majority o channels. When 3 0, all the signals are unknown, the probability o etection, the probability o alse alarm, an the mean etection time can be evaluate by putting 3 0 in Eq.s(52), (53) an (54), respectively:, ED, ED = (55) = (56) T = NT ED 1 (57) Subcase 2.2.2:When <1 or most o the channels, the U waveorm is known. Then the CR will perorm noncooperative matche ilter or sensing the majority o channels. When 3 1, all the signals are known, the probability o etection, the probability o alse alarm, an the mean etection time can be evaluate by putting 3 1 in Eq.s(52), (53) an (54), respectively: = (68), MF, MF = (59) T = NT MF 1 (60) 3.CONSIDERED SETTING AND SIMULATION ARAMETERS SimulationsusingMat-labwere carrie out unerthe ollowing system setting: there are 8uniormly istributeus with signal, ban an channelcharacteristics accoring to Table1.4 CRs seeking to sense the holes in the 8 Us bans whether iniviually (non-cooperatively)or using cooperative etection where CR-1 acts as the usion center. The simulation parameters are given in Table 2. Table 1: Characteristics o bans o interest BANDS OF INTEREST BAND-1 BAND-2 BAND-3 BAND-4 BAND-5 BAND-6 BAND-7 CHARACTERISTICS BW=5MHz, Channel: Multi-path, Carrier requency: 2GHz Signal type: WCDMA, SNIR(B)=-7 BW=7MHz, Channel: Multi-path, Carrier requency: 5GHz Signal type: OFDM, SNIR(B)=0 BW=10MHz, Channel: Multi-path, Carrier requency: 5GHz Signal type: OFDM, SNIR(B)=-17 BW=20MHz, Channel: Multi-path, Carrier requency: 8GHz Signal type: OFDM, SNIR(B)=-24 BW=200KHz, Channel: AWGN, Carrier requency: 900MHz Signal type: GMSK, SNIR(B)=-3 BW=100KHz, Channel: AWGN, Number o samples: 200K, Carrier requency: 2GHz Signal type: 16-QAM, SNIR(B)=-19 BW=50KHz, Channel: AWGN, Carrier requency: 2GHz 14

15 BAND-8 Signal type: 4-QAM, SNIR(B)=10 BW=30KHz, Channel: AWGN, Carrier requency: 400KHz Signal type: BSK, SNIR(B)=-21 Table 2: Simulation parameters or consiere setting arameter Value/Assumption Number o Bans 8 robability o alse alarm or each etection scheme Sensing times or a single channel by CS (T 1 ), con-ed ( 2 ) an MF ( 3 ) SNR wall T R T S 0.01 T 1 =12, 2 =2 an 3 =1 Error! Reerence source not oun. -9B [21] 3ms (max.) 1ms (max.) FFT OINTS 256 N N t N an Nt are the averaging ilter lengths in the requency an time omain, respectively T m N =4 N t =40-18B[21] 4.NUMERICAL RESULT Table 3 shows the main characteristics o each ban o interest base on which the propose aaptive algorithm selects the appropriate etection scheme iniviually or cooperatively. The igure also inicates the applicability or inapplicability o other schemes besies the selecte one. It is shown that or the our wieban signals, SBED is always selecte as all other schemes are inapplicable to sense wieban. For narrow ban signals, MF is selecte when the signal characteristics are known enough an OOCS is selecte accoring otherwise. 15

16 Table 3: Aaptive Algorithm: Selecte Scheme an applicability o other Schemes Base on Table 3, Figure 3 shows the probabilities o etection or each ban in interest accoring to the selecte etection scheme an other applicable ones. Conventional energy etection, although not use in the algorithm, is ae to the igure in orer to compare it with SBED. The igure shows that optimal probability o etection (1.00) at ban-1 using SBED when SNIR is 0 B but it is better at ban-3 than at ban-1 although the signal there has lower SNIR. That was ue to the use o cooperative sensing. In ban-4, the probability o etection is below 0.9 ue to very low SNIR espite using cooperative sensing. The narrowban signals in ban 5- to-8, MF is use when the signal is known an OOCS is use otherwise. We note that the conventional energy etection, i use, will perorm well in ban-5 an ban-7 where the SNIR is relatively aequate or its unction. However, or ban-6 an ban-8, its probabilities o etection are very poor ue to inaequate SNIR. 16

17 Figure 3: robabilities o etection or each ban in interest accoring to the selecte etection scheme an other applicable ones. Figure 4 shows the mean etection times or each ban in interest accoring to the selecte etection scheme an other applicable ones. We notice relatively long etection times or wieban signals as expecte. However, or narrow ban ones, it epens on the selecte etection scheme an whether cooperative or iniviual etection. Note that cooperative overheas are represente by extra reporting an synchronization elays in aition to the sensing time. Comparing with results achieve in Figure 3, we notice that the selecte scheme or both ban-5 an ban-7 (MF) was the best as it yiels best probability o etection an least etection time. However, or both ban-6 an ban-8, cooperative OOCS was selecte since complete signal characteristics are unknown an suers rom low SNIR. So, no way to use MF or lower etection time. Moreover, i conventional ED was use, it woul lea to very low probability o etection. 17

18 Figure 4: Mean etection times or each ban in interest accoring to the selecte etection scheme an other applicable ones. Figure 5 shows the average probability o etection- average over all bans- or ierent values o (the probability that channel woul be sense by the non-cooperative etections) uner the 1 conition that each o other probabilities,, 2 an 3, is ixe to 0.5. Figure 5 shows the 4 average etection time uner same conitions. 18

19 Figure 5: Average probability o etection or ierent values o 1, average SNIR=10B The two igures show that when =0, which mean all the ban are sense cooperatively, the 1 average probability o etection is at the expense o 48.2 ms o average etection time. At the other ege, i =1, which mean all the bans are sense non-cooperatively, the average 1 probability o etection becomes practically unacceptable (0.78) although the average etection time is lower ue to the absence o reporting an synchronization elays. The best case was when =0.5 where hal o the bans are sense cooperatively an the other hal are sense 1 iniviually as the case o the propose aaptive moel. Average Detection Time (ms) Figure 6: Average etection times or ierent values o 1, average SNIR=10B 19

20 In Table 3, the perormance o the propose multi-stage etection scheme is compare with existing onespresente in Section 1. As mentione in section 1, no other scheme consiere switching between local an cooperative sensing or most types o Us signals with both narrow an wie bans- reaching 20 MHz.Moreover, signals experience practical wireless channels incluing hien U problem. Although comparison is not air, the results o propose schemeinicatesthat the probability o etection is aroun or a given alse alarmprobability o 0.1 at an assume average SNR o 10 B.Although some other schemes, show slightly better etection probabilities, however, i they encountere the aorementione conitions o the propose one, their perormance woul be ierent. Detection Scheme ropose Scheme Table 4: erormance Comparison with Existing Sensing Schemes Avera ge SNR (B) Applicability Both cooperative an local sensing. Wie types o Us signals an bans o interest in most practical wireless channels incluing hien U problem. I3S[6] Local sensing No hien U problem. Only Gaussian channels. Fuzzy Logic- Base[10] SNR-base aaptive[5] High-spee two-stage[11] Local sensing. Only consiere limite types o primary system an channel conition. No hien U problem. Only Gaussian channels Local sensing. Only consiere limite types o primary system an channel conition. No hien U problem Local sensing. Only consiere limite types o primary system an channel conition. No hien U problem. Only Gaussian channels. 20

21 two- Fast stage[12] Local sensing. Only consiere limite types o primary system an channel conition. No hien U problem. 5. CONCLUSION The propose multi-stage etection scheme eals withalmost all types o Us signals an bans o interest. It tries to etect signals experiencing practical wireless channels an ecies the etection algorithm base on the power, noise, banwith an knowlege o signal, thus traing o accuracy an mean etection time or the overall etection process. The perormance o the propose multi-stage scheme is compare with existing onesin spite o the act that no one o them consiere most types o Us signalswith both narrow an wie bans- reaching 20 MHz, as the propose scheme i. Moreover,etecting signals experiencing practical wireless channels incluing hien U problem necessitate switching between local an cooperative sensing. The results o propose scheme inicate that the probability o etection is aroun or a given o alse alarmprobability o 0.1 at an assume average SNR o 10 B. Although some other schemes, show slightly better etection probabilities, however, i they encountere the aorementione conitions o the propose one, their perormance woul be ierent. Reerences [1] J. Kantian G. Singh Tomar Various Sensing Techniques in Cognitive Raio Networks: A Review International Journal o Gri an Distribute Computing Vol. 9, No. 1 (2016), pp [2] SenerDikmese, aschalis C. Sootasios, TeroIhalainen, Markku Renors an MikkoValkama, Eicient Energy Detection Methos or Spectrum Sensing uner Non-Flat Spectral Characteristics, IEEE Journal on Selecte Areas in Communications (JSAC), DOI: /JSAC , Oct [3] W. Yue, B. Zheng, an Q. Meng, Cyclostationary property base spectrum sensing algorithms or primary etection in cognitive raio systems, Journal o Shanghai Jiaotong University (Science), vol. 14, no. 6, pp , Dec [4] H. Sun et al., Wieban spectrum sensing or cognitive raio networks- a survey IEEE Wireless Communications April 2013, pp [5] Ejaz et al. " SNR-base aaptive spectrum sensing or cognitive raio networks". International Journal o Innovative Computing, Inormation an Control Vol. 8, No: 9, (2012) [6] Ejaz et al. " I3S: Intelligent spectrum sensing scheme or cognitive raio networks" EURASI Journal onwireless Communications an Networking 2013, 2013:26 [7] Amarip Kumar et al. "An Aaptive an Eicient Local Spectrum Sensing Scheme in Cognitive Raio Networks" International Journal o Computer Applications ( ) Volume72 No.23, June 2013 [8] W Yue, B Zheng, Q Meng, W Yue, Combine energy etection one-orer cyclostationary eature etection techniques in cognitive raio systems. J China Univ. osts Telecommun. 17(4), (2010) [9] K. Srisomboo et al., Two-stage Spectrum Sensing or Cognitive Raio uner Noise Uncertainty roceeing o the Eighth International Conerence on Mobile Computing, 2015, pp [10] WEjaz, NU Hasan, MA Azam, HS Kim, Improve local spectrum sensing or cognitive raio networks. EURASI J. Av. Signal rocess(2012). asp.eurasipjournals.com/content/2012/1/242 21

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