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  1. 1. D.Kalaiabirami, D.Kalaiselvi / International Journal of Engineering Research and Applications(IJERA) ISSN: 2248-9622 www.ijera.comVol. 3, Issue 3, May-Jun 2013, pp.852-856852 | P a g eQueue Balancing Dynamic Resource Allocation Management inCR networksD.Kalaiabirami1, D.Kalaiselvi21Asst.Professor,Department of Computer Science, Jay shriram group of institutions ,Tirupur,India2Asst.Professor,Department of Computer Science,Jay shriram group of institutions, Tirupur,IndiaABSTRACTIn Future wireless communication andnetworking Cognitive radio is a powerfultechnology. It is a new communicationparadigm in spectrum. When the spectrum is leftunused by the licensed users it allows theunlicensed users to access the spectrumefficiently. However the secondary users vacatethe current occupied channel the specificprimary users for that channel to transmit databy that channel itself because the primary usershave the priority to access the channel. Toprovide reliable transmission to the secondaryusers, spectrum hand off method is help thesecondary user return the channel to the specificprimary users and stop the secondary user’stransmission and the remaining transmission ofthe secondary user at other free channel. Theproblem is allocating channels and transmissionpower in multihop CR networks. This researchpaper proposed a frequent feature selectionmethod for CR networks. Good performance ofthis method comes from the use of the spectrumutilization. The proposed approach improves thedata transmission accuracy and reduces thepacket loss of the secondary user transmission.Keywords - cognitive radio (CR),Muihopnetworks.I. INTRODUCTIONThe term cognitive radio is designed as aradio frequency transceiver to detect whether aparticular segment of the radio spectrum is in useand out of the temporarily unused spectrum withoutinterfering with the transmission of the authorizedusers. It reduces the spectrum shortage problem.Here the problem is distributed resource allocation[5],[6].In this research paper flow control(routing)is used to transmission of data between source todestination. The flow control used the commonmethod resource directive decomposition[7].Commonly routing problems for networks areformulated as multi commodity flow problems. Therouting of data flows depends on the linkcapacities. It is usually assumed fixed. However thelink capacities of the wireless networks are notnecessarily fixed. but it can adjusted by theallocation of resources. Adjusting the resourceallocation changes the link capacities. Thesimultaneous optimization of routing and resourceallocation only used to achieved overall optimalperformance of the network.[7].This methodconverts multi commodity flow problems into asingle commodity flow problem. In this -researchpaper proposed a queue balancing method. Thismethod for the multi commodity flowproblem.[8][9].The multicommodity flow problem consists ofseveral different commodities from their respectivesources to their sinks through a common networkso that the total flow going through each edge doesnot exceeds its capacity.[8].To protect primaryusers in CR networks each node has the powermask on every channel. Sometimes the status ofchannel in a licensed spectrum may change becauseof primary users activities is called spectrumdynamics.Cognitive radios (CRs) intelligently exploitavailable side information about the Channel conditions Activity Code books MessagesOf other nodes with which share the spectrum.Fig .1 CR network in Spectrum
  2. 2. D.Kalaiabirami, D.Kalaiselvi / International Journal of Engineering Research and Applications(IJERA) ISSN: 2248-9622 www.ijera.comVol. 3, Issue 3, May-Jun 2013, pp.852-856853 | P a g eFig.2 CR Network framework[1]inactive, an important requirement of secondaryusers is the capability to sense their surroundingradio spectrum environment. Further, since primaryusers should be carefully protected frominterference due to secondary users operation,secondary users also need to sense the licensedspectrum before each transmission and can onlytransmit when the spectrum is idle. One efficientway of spectrum detection is the primarytransmitter detection based on local observations ofsecondary users. If the information of the primaryuser signal is known to secondary users, they canuse matched Alter detection to maximize thereceived signal-to-noise ratio (SNR) understationary Gaussian noise. Dynamic spectrumaccess has become a promising approach to fullyutilize the spectrum resource.II. CR NETWORK CREATIONCognitive radio (CR) network makes itpossible for unlicensed/cognitive users or devicesto opportunistically utilize the licensed spectrumwhen it is not occupied by licensed/primary users.It can overcome the drawback of the current staticspectrum allocation policy. Using this module theuser can reserve the path for their future datatransmission. The Licensed (Reserved) users datatransmissions are take into account seriously thanunlicensed users data transmission. It consists ofset of nodes V and a set of links L.HereT(L)=Transmitter of link(L).R(L)=Receiver of link(L).In order to reduce the complexity ofresource allocation several subcarriers arecombined to be a channel. Specific minimumnumber of channels only required for wirelessnetwork.[5].For the flexibility of spectrum it can bedivided into more channels. Assume that number ofC channels are avillable.III. UNLICENSED USERTRANSMISSIONThe special functionality of Cognitiveradio (CR) network allows the unlicensed users canmakes data transmission through the reserved path,when the paths are not utilized by the licensedusers. the path utilization is achieved by theUnlicensed user data transmission and this allowthat the data transmission on On-Demand Resourceprovisioning mode.Interference-Aware Transmission ModelTo protect the communication of the primarynodes, the Transmit power of CR nodes should berestricted as∑ wlkPlk < QikT(L)=iPlk-Transmit power at link l on channel C. wlk-Binary indicator for channel allocation. i.e., meansthat channel is (not) allocated to link L .IV. SPECTRUM DYNAMICSFor CR networks, each node has thepower mask on every channel to protect primaryusers, and the status of channels in a licensedspectrum may change because of the primary users’activities, which is known as spectrum dynamics.The channel accessibility is superior for licensedusers than the unlicensed users. From this viewwant make a better channel provisioning forunlicensed users data transmission.In multi-hop Cognitive Radio Network(CRN), the CR nodes sense spectrum and getavailable frequency bands, named as SpectrumOpportunities (SOP) [2], then select one candidatefrom SOP via specific policy, which will notinterfere with licensed nodes.[14]. One of the mostchallenging problems of cognitive radio is theinterference which occurs when a cognitive radioaccesses a licensed band but fails to notice thepresence of the licensed user. To address thisproblem, the cognitive radio should be designed toco-exist with the licensed user without creatingharmful interference. Recently, several interferencemitigation techniques have been presented forcognitive radio systems. An orthogonal frequencydivision multiplexing (OFDM) was considered as a
  3. 3. D.Kalaiabirami, D.Kalaiselvi / International Journal of Engineering Research and Applications(IJERA) ISSN: 2248-9622 www.ijera.comVol. 3, Issue 3, May-Jun 2013, pp.852-856854 | P a g ecandidate for cognitive radio to avoid theinterference by leaving a set of sub channelsunused [3]. A power control rule was presented toallow cognitive radios to adjust their transmitpowers in order to guarantee a quality of service tothe primary system [4]. To avoid the interference tothe licensed users, the transmit power of thecognitive radio should be limited based on thelocations of the licensed users [4]. However, it isdifficult to locate the licensed users for thecognitive radio in practice because the channelsbetween the cognitive radio and the licensed usersare usually unknown.[13]. In this research paper,present a power control approach in cognitive radiosystems based on spectrum sensing sideinformation in order to mitigate the interference tothe primary user due to the presence of cognitiveradios. This approach consists of two steps. Firstly,the shortest distance between a licensed receiverand a cognitive radio is derived from the spectrumsensing side information. Then, the transmit powerof the cognitive radio is determined based on thisshortest distance to guarantee a quality of servicefor the licensed user. Because the worst case isconsidered in this approach where the cognitiveradio is the closest to the licensed user, theproposed power control approach can be applied tothe licensed user in any location.Power control based on spectrum sensing sideinformation.In this section present a power controlapproach in cognitive radio systems based onspectrum sensing side information to efficientlyutilize the spectrum by allowing the cognitive radioto co-exist with the primary system. firstly proposean idea of determining the distance d between theprimary transmitter and the cognitive radio fromspectrum sensing. Then, we show that the transmitpower of the cognitive radio can be controlledbased on the distance d in order to guarantee aquality of service to the primary receiver.Spectrum Sensing Side InformationIn order to avoid the harmful interferenceto the primary (licensed) system, the cognitiveradio needs to sense the availability of thespectrum. The goal of spectrum sensing is to decidebetween the following two hypotheses:H0 : x(t) = n(t) 0< t ≤ TH1 : x(t) = hs(t) + n(t) 0< t ≤ Twhere T denotes the observation time, x(t)is the received signal at the cognitive radio, s(t) isthe transmitted signal from the primary transmitter,n(t) is the zero-mean additive white Gaussian noise(AWGN) with the variance σ2 and h denotes theRayleigh fading channel coefficient. Theinstantaneous SNR is defined as γ _ |hs(t)|2/σ2.forthis channel allocation proposed a algorithm.Distributed Spectrum Allocation Algorithm:1. Let the available bandwidth options be: {b1, b2,..., bn},with b1 < b2 < . . . < bn.2. I := min{i|bi _ B/N};3. for i = I, . . . , 1 do4 .Δf = bi;Δt := min{Tmax, Tx Duration(bi, qLen)}5: if Δt == Tmax or i == 1 then6: Find the best placement of the Δf×Δt block inthelocal spectrum allocation table that minimizes thefinishing time and is compatible with the existingallocations and prohibited bands.7: if the block can be placed in the local spectrumallocation table then8: return the allocation (t,Δt, f,Δf).9: end if10: end if11: end for.This algorithm is used to allocate a channel in CRNetwork.V.POWER MASKThe power mask model is considered as ageneral case of the channel availability model.With the queue-balancing flow control method, ourproposed distributed resource-allocation schemecan deal with spectrum. For cognitive radio, thepower mask for each channel and can adapt itself toaccount for the spectrum dynamics according to thespectrum condition and the current linktransmission requirement. The flow control, powerallocation, and channel allocation are consideredjointly to balance the queue sizes. The proposeddistributed scheme is also suitable forasynchronous scenarios in which not all thenetwork nodes have to execute the scheme at thesame time. With the help of this module theUnlicensed user can make better data transmissionby either switching to the free channels or reducingthe data rate.Queue balancing flow control is proposedto pushes data from source to destination. the queuesize of the source is always larger than that of thedestination for each session.The link capacitieschange with dynamic resource allocations affectedby primary activities and different queue sizes ofthe nodes. Additional coordination of nodes isneeded because of the complex wirelessenvironment, especially caused by primary usersmoving in and out of channels.Queue balancing worked in a distributed way .Inthis research paper this scheme in two parts1.Node level resource allocation.2.Network level resource allocation.Node level resource allocationBy using the queue-balancing flowcontrol, the problem can be transformed to a
  4. 4. D.Kalaiabirami, D.Kalaiselvi / International Journal of Engineering Research and Applications(IJERA) ISSN: 2248-9622 www.ijera.comVol. 3, Issue 3, May-Jun 2013, pp.852-856855 | P a g eresource-allocation problem for each link.Specifically, we need to allocate the channel andpower resource for each link so as to maximize thedecrease of potential functions in each time slot.Inthis research paper consider three types of resourceallocation, ranging from small-scale to larger-scaleadjustments.• Adjust the data rate over a link for each sessionaccording to the queue sizes at transmitters andreceivers.• Allocate the power of the links transmitting fromthe same nodes. The power adjustment changes thelink capacities, but does not affect other linksbecause of interference-free channel allocation.• Change the channel allocation to achieve betterperformance. To avoid the interference betweenlinks, nearby nodes need to be coordinated forchannel allocation.Network level resource allocationBased on the above analysis, we propose anode-based distributed algorithm for joint flowcontrol, channel allocation, and power control inCR networks.Step 1) Update the queue sizes at each node.Step 2) Send the control information needed forresourceAllocation.Step 3) Determine the resource allocation andexchangeINFO and REQ, if necessary.Step 4) Adjust the channel allocation strategy anddetermine the corresponding power and data ratefor each session. Send OCCUPY for new channeloccupation.VI.EXPERIMENTAL RESULTFrom the experiment the channel isallocated to a secondary users in efficient waywithout interfere a primary users activity using thequeue balancing and flow control method.Normally when the secondary user connection islost because primary user occupy that specificchannel.at that time packet loss in secondary userside is not controlled. In this paper that is rectified(packet loss is controlled) .VII.ISSUES AND CHALLENGESSpectrum management is considered as asignificant yet intricate task that needs to be carriedout precisely and efficiently. It reduces spectrumshortage problem in future.The queue balancing and flow control of the samewould be highly beneficial. Primary users decisionsare often made based on channel allocation . Thispractice leads to unwanted packet loss, errorswhich affects the quality of service provided tousers. Networking have the potential to generatea knowledge-rich environment which can help tosignificantly improve the quality of CR networks.VIII.CONCLUSIONThis paper proposed an efficient frequentfeature selection method for Spectrummanagement. Good performance of this methodcomes from the use of the queue balancing and therelevant flow control. The power mask reflects theimportance of the channel allocation as well astheir interactions..The proposed work can befurther enhanced and expanded for the CRnetworks We intend to extend our work applyingvarious classification methods to improve spectrumutilization more efficiently.REFERENCES[1] J. Mitola and G. Maguire, “Cognitiveradio: Making software radios morepersonal,” IEEE Pers. Commun., vol. 6,no. 4, pp. 13–18, Aug.1999.[2] C. Xin, B. Xie and Shen, “A NovelLayered Graph Model for TopologyFormation and Routing in DynamicSpectrum Access Networks,” IEEEDySPAN, 2005.[3] T. Weiss, J. Hillenbrand, A. Krohn, and F.K. Jondral, “Mutual interferenceinOFDM-based spectrum pooling systems,”in Proc. IEEE VTC,May 2004, vol. 4, pp.1873–1877.[4] N. Hoven and A. Sahai, “Power scalingfor cognitive radio,” in Proc.WCNC,Maui, Hawaii, USA, June 2005, vol. 1, pp.250–255.[5] Y. Xi and E. M. Yeh, “Distributedalgorithms for spectrum allocation,powercontrol, routing, and congestion control inwireless networks,”in Proc. ACMMobiHoc, Sep. 2007, pp. 180–189.[6] L. Xiao, M. Johansson, and S. P. Boyd,“Simultaneous routing and resourceallocation via dual decomposition,” IEEETrans. Commun.,vol. 52, no. 7, pp. 1136–1144, Jul. 2004.[7] R.K.Ahuja,T.L.Magnanti,andJ.B.Orlin,Network Flows: Theory,Algorithms andApplications. Upper Saddle River, NJ:Prentice-Hall,1993.[8] B. Awerbuch and T. Leighton, “A simplelocal-control approximation algorithm formulticommodity flow,” in Proc. IEEEFOCS, Nov. 1993,pp. 459–468.[9] B. Awerbuch and T. Leighton, “Improvedapproximation algorithms for the multi-commodity flow problem and localcompetitive routing in dynamicnetworks,” in Proc. ACM STOC, 1994,pp. 487–496.[10] C. Peng, H. Zheng, and B. Y. Zhao,“Utilization and fairness in spectrumassignment for opportunistic spectrum
  5. 5. D.Kalaiabirami, D.Kalaiselvi / International Journal of Engineering Research and Applications(IJERA) ISSN: 2248-9622 www.ijera.comVol. 3, Issue 3, May-Jun 2013, pp.852-856856 | P a g eaccess,” Mobile Netw.Appl., vol. 11, no.4, pp. 555–576, May 2006.[11] Y. Yuan, P. Bahl, R. Chandra, T.Moscibroda, and Y. Wu, “Allocatingdynamic time-spectrum blocks incognitive radio networks,” in Proc.ACMMobiHoc, Sep. 2007, pp. 130–139.[12] T. Weiss, J. Hillenbrand, A. Krohn, and F.K. Jondral, “Mutual interferenceinOFDM-based spectrum pooling systems,”in Proc. IEEE VTC,May 2004, vol. 4, pp.1873–1877.[13] K. Hamdi, W. Zhang, and K. B. Letaief,“Power control in cognitive radio systemsbased on spectrum sensing sideinformation,” in Proc.IEEE ICC, Jun.2007, pp. 5161–5165.[14] G. Cheng,W. Liu, Y. Li, andW. Cheng,“Joint on-demand routing and spectrumassignment in cognitive radio networks,”in Proc. IEEE ICC Jun. 2007, pp. 6499–6503.