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Cooperative spectrum sensing using random access R-ALOHA
1.
International Research Journal
of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 05 Issue: 01 | Jan-2018 www.irjet.net p-ISSN: 2395-0072 © 2018, IRJET | Impact Factor value: 6.171 | ISO 9001:2008 Certified Journal | Page 335 RANDOM ACCESS COOPERATIVE SPECTRUM SENSING IN COGNITIVE RADIO NETWORK Siva Sankari. S1, Jayasri. C2 1P.G Student, Dept. of ECE, A.V.C College of Engineering, 2Assitant Professor, Dept. of ECE, A.V.C College of Engineering, Mayiladuthurai, ---------------------------------------------------------------------***--------------------------------------------------------------------- Abstract - Cooperative spectrum sensing increases the detection performance in a cognitive radio network, based on the number of sensing nodes. However, as the number of sensing nodes increases, the reporting overhead linearly increases. Such an approach has been first suggested in the packet reservation multiple-access (PRMA) technique, an adaptation of the reservation ALOHA protocol to the cellular environment. Contention based protocols, which limits their achievable throughput is the high number of packet collisions under heavy load of offered traffic. A key factor limiting throughput in such methods is that when a transmission is initiated, the full time and frequency resources of the channel are being used even though the sender have no knowledge if the transmitted packet will not encounter a collision.Incaseof collision the channel resources are wasted. There is group of medium access protocols that avoid some of the inefficiencies of the contention based protocols, by adding more control to the access method. They are called controlled random access methods. Two such protocols are described in this lesson: reservation ALOHA (R ALOHA)and polling.R-ALOHAis the example of distributed control random access scheme, poling is the example of centrally controlled random access scheme. Slots for the WSs reserved as per the current demand of the WSs. In the R-ALOHA scheme the control of the systemis distributed among all users in the network. Because all reservation messages are heard by all users in the network, each user maintains information on the queue of outstanding reservations for all other users in the network as well as for its own reservation. When the queue length drops to zero, the system returns to the unreserved mode, in which there are reservation sub slots only. Key Words: R-ALOHA, Cognitive Radio(CR), primary Users(PU), Fusion Centre(FC). 1.INTRODUCTION Cognitive Radio (CR) enables the efficient use of limited spectrum by allowing secondary users (SUs) to access the licensed frequency bands of primary users (PUs). Fig 1 Spectrum sensing is a key element required to allow SUs to use vacant frequency bands in a CR network. Many signal detection techniques such as energy detection, matched filtering, and cyclostationary featuredetectioncanbeusedto enhance detection performance in spectrum sensing . However, in practice, many factors, such as multipathfading, shadowing, and the hidden PU problem, may significantly affect detection performance. In cooperative spectrum sensing, each sensing node reports its sensing result to a fusion center (FC). The FC determines the presenceofthePU by combining multiple independent sensing results from sensing nodes. Each sensing node performs local spectrum sensing and decides the presence of a PU by using a different detection threshold. Each sensing node reports its local decision to the FC and then the FC finally decides the presence of a PU by using hard combination (HC) methods (e.g., OR-rule or AND-rule). However, the SC method shows better sensing performance than HC methods at the cost of increased bandwidth of reporting channels. In cellular networks with multiuser diversity, various approacheshave been studied to reduce the amount of the channel state information fed back by users. One approach is to quantize the observed channel state. An alternative approach is to allow users to report only if their channel state exceeds a threshold. In cellular networks with multiuser diversity, a base station finds one user who has the best channel condition among multiple users, for every frame. Contrastively, in the CR networkswithcooperativespectrum sensing, an FC combines multiple sensing information reported from sensing nodes. Hence, previous multiuser diversity schemes with limited feedbackincellularnetworks cannot be directly applied to the CR networks. 1.1 RELATED WORK Spectrum sensing is a major function of cognitive radio to sense the spectrum before using it to avoid interfering with the signals of the licensed users. Each SU implements a detection method such as matched filter detection [3], energy detection [4] and cyclostationary detection [5] to sense the PU signal. The SUs encounter several challenges such as signal attenuation, fading and shadowing when detecting the PU signal in the spectrum. Research issueswhich have been extensively studied in co – operative spectrum sensing include detection methods, collaborative SU’s and FU’s rules[8]. It does not address the reporting channel or reporting issues, in which SUs send their detection report to the FC. The reporting phase has been considered in a scenario with noise. In cellular networkswith multiuser diversity, variousapproacheshave been studied to reduce the amount of the channel state information fed back by users. Contrastively, in the CR networks with cooperative spectrum sensing, an FC combines multiple sensing information [1] reported from
2.
International Research Journal
of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 05 Issue: 01 | Jan-2018 www.irjet.net p-ISSN: 2395-0072 © 2018, IRJET | Impact Factor value: 6.171 | ISO 9001:2008 Certified Journal | Page 336 sensing nodes. Hence, previousmultiuser diversity schemes with limited feedback in cellular networkscannotbedirectly applied to the CR networks. The OR voting rule [6] in their analysis to maximize a utility function as a weighted sum of capacity and energy expenditure. Fig -1: Cognitive Radio Sensing and Reporting Fig -2: Frame Structure 2. REPORTING CHANNELS BASED ON R-ALOHA The system has two modes of operation: unreserved mode and reserved mode. In the unreserved mode, the time axis is divided into short equal-length sub slots for making reservations. Fig:3 Users transmitshortreservationrequests in the reservation sub slots. After transmitting a reservation request a user waits for positive acknowledgment (ACK). The reservation acknowledgment advices the requesting user where to locate its first data packet. The system then switches to the reserved mode. Figure -3: Frame structure of Reservation Aloha In the reserved mode the time axis is divided into fixed- length frames. Each frame consistsof M+1 equal-lengthslots of which the first M slots are used for message transmission (message slots) and the last slot is subdivided into R short reservation sub slots used for reservation. A sending user that has been granted a reservation sends its packets in successive message slots, skipping over the reservation sub slots when they are encountered. When there are no reservations taking place, the system returns to the unreserved mode. METHODOLOGY Maximize throughput The maximum throughput Occurs at G(n) = 1 If we knew m, n, and qa we could pick qr so that G(n) = (m − n)qa + nqr = 1 qr = 1 − (m − n)qa/n Slotted Aloha Departure rate = Prob of 1 transmission in a slot = Ge−G Maximum departure rate occurs at: d/dG (Ge−G) = e −G − Ge−G = 0 G = 1 Maximum departure rate = e −1 ≈ 0. 368 At the maximum departure rate: Pr( empty slot ) = e −G = e −1 ≈ . 368 Pr (successful x mission ) = Ge−G = e −1 ≈ . 368 Pr (collision ) = 1 − e −G − Ge−G ≈ 1 − 2*. 368 = . 264 S = Ge−2G for un slotted Aloha and S = Ge−G for slotted Aloha Average Delay The average number of times a source transmits is G S The average number of times a source retries, when thereis an equilibrium point, is R = (G/S – 1) Runslotted = e 2G – 1 Rslotted = e G − 1 At G = Gmax, R = e − 1, for both systems If the average time between retriesisW, the average delayis T = 1 + R (1 + W)
3.
International Research Journal
of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 05 Issue: 01 | Jan-2018 www.irjet.net p-ISSN: 2395-0072 © 2018, IRJET | Impact Factor value: 6.171 | ISO 9001:2008 Certified Journal | Page 337 2.1 EXPERIMENTAL RESULT Figure -4: Starts transmission using R-Aloha Figure -5: Cooperative False Alarm prob.(Qf) Vs Mean of Reserved Slot Length(V) with Hard Decision Figure -6: ROC Curve of Random Access Approaches In Fig -5, cooperative false alarm probabilities Qf versus the numbers of reporting slots Nr is presented. Sensing performance of all protocolsimprove with increasingNrand the cooperative performance varies. It is importanttonotice that, with limited number of reporting slots, good cooperative spectrum sensing performance can beobtained. For example, with R-Aloha with collision, we achieve approximately 2%cooperative false alarm probabilitywhen Nr = 10. From the above Fig -6, the performance of an ideal scenario in which all SUs’ individual reports are collected perfectly at FC. cooperative false alarm probability (Qf) cooperative detection probability (Qd) performance bound R−Aloha (collision/theory) R−Aloha (collision/simulation). The simulation results match well with theoretical analyses. 3. CONCLUSIONS A reporting channel design approach for cooperative spectrum sensing cognitive radio networks. This reporting channel design approach is based on random access protocols, including R-Aloha. This approach is utilized to reduce channel assignment complexity in any fixed assignment reporting channel design. Analyticalevaluations and performance comparisons are performedconsideringR- Aloha (perfect/imperfect capture, collision) andhardversus soft fusion rules. With various R-Aloha design parameters and hard/soft fusion rules, it is shown that good cooperative spectrum sensing performance is achieved with limit number of reporting slots. It is also observed that,ingeneral, R-Aloha performs better than previous approaches in providing effective reporting channels. Future work to increases the throughputs “original” frames generated at all nodes of a contention-based network (ALOHA, CSMA, etc.) per unit time.
4.
International Research Journal
of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 05 Issue: 01 | Jan-2018 www.irjet.net p-ISSN: 2395-0072 © 2018, IRJET | Impact Factor value: 6.171 | ISO 9001:2008 Certified Journal | Page 338 REFERENCES [1] J. Mitola and G. Maguire, “Cognitive radio: Making software radios more personal,” IEEE Pers. Commun., vol. 6, no. 4, pp. 13-18, Aug. 1999. [2] J. Mitola, “Cognitive radio: An integrated agent architecture for software defined radio,” Doctor of Technology, Royal Inst. Technol. (KTH), Stockholm,Sweden, May 2000. [3] D. Cabric, A. Tkachenko, and R. W. Brodersen, “Experimental study of spectrum sensing based on energy detection and network cooperation,”inProc. ACM 1st Int. Workshop on Technology and Policy for Accessing Spectrum (TAPAS), Aug. 2006. [4] S. M. Kay, Fundamentals of Statistical Signal Processing: Detection Theory. Englewood Cliffs, NJ: Prentice-Hall, 1998. [5] S. Enserink and D. Cochran, “A cyclostationary feature detector,” in Proc.28th AsilomarConference on Signals, Systems, and Computers, Monterey,CA, Oct. 1994, pp. 806-810. [6] J. Ma, G. Zhao, and Y. Li, “Soft combination and detection for cooperative spectrum sensing in cognitive radio networks,” IEEE Trans. Wireless Commun., vol. 7, no. 11, pp. 4502-4507, Nov. 2008. [7] G. Ganesan and Y. Li, “Cooperativespectrumsensing in cognitive radio networks,” in Proc. IEEE DySPAN, Nov. 2005, pp. 137-143. [8] Ghasemi and E. Sousa, “Collaborative spectrum sensing for opportunistic access in fading environment,” in Proc. IEEE DySPAN, Nov.2005,pp. 131-136.
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