Abstract
The endeavor of categorizing the existing Cognitive-MAC (C-MAC) protocols requires definition of general classification frameworks or layouts that merge most of the aspects of the protocols in a single unified presentation. This chapter introduces the C-MAC cycle as a general classification and systematization layout for C-MAC protocols. The C-MAC cycle originates form the idea that the MAC layer in spectrally heterogeneous environments should provide support for three generic technical features: radio environmental data acquisition; spectrum sharing; and control channel management. The inclusion of these generic technical features is necessary in Cognitive Radio Networks (CRNs) for improving the network performance and achieving spectrum efficiency gain while providing maximal level of protection for the primary system. This chapter presents extensive survey on the state-of-art advances in C-MAC protocol engineering by reviewing existing technical solutions and proposals, identifying their basic characteristics and placing them into the C-MAC cycle, with emphasis on the modularity of the C-MAC cycle. It provides overview of large number of technical details concerning the three generic functionalities (i.e. the radio environmental data acquisition, the spectrum sharing and the control channel management) as the main building blocks of the C-MAC cycle. Three uses cases (each in different generic functional group), illustrate the capabilities of the proposed C-MAC cycle layout. In more detail, the first use case theoretically presents and practically evaluates cooperative spectrum sensing based on Estimated Noise Power. The results illustrate the effect of estimating the noise variance on the detection capabilities of the Majority Voting and Equal Gain Combining cooperative spectrum sensing strategies. The second use case presents advanced and computationally efficient horizontal spectrum sharing strategy for secondary systems based on Node Clustering and Beamforming. Finally, the last use case presents and assesses a multiuser quorum-based multiple rendezvous strategy for control channel establishment in distributed Cognitive Radio Networks.
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References
Mitola, J.: Cognitive radio for flexible mobile multimedia communication. Paper Presented at 1999 IEEE International Workshop on Mobile Multimedia Communications, San Diego, Nov 1999
Standard for Recommended Practice for Installation and Deployment of IEEE 802.22 Systems, Official IEEE Standard, 28 Sept 2012
IEEE 802.11af Standard for Wireless LAN in TV White Space. http://grouper.ieee.org/groups/802/11/Reports/tgaf_update.htm. Accessed 20 Dec 2013
EC FP7-248303 project QUASAR. http://www.quasarspectrum.eu/. Accessed 20 Dec 2013
EC FP7-216856 project ARAGORN. http://www.ict-aragorn.eu/. Accessed 20 Dec 2013
EC FP7-248351 project FARAMIR. http://www.ict-faramir.eu/. Accessed 20 Dec 2013
EC FP7-257626 project ACROPOLIS. http://www.ict-acropolis.eu/. Accessed 20 Dec 2013
Gavrilovska, L., et al.: Medium access control protocols in cognitive radio newtorks: overview and general classification. IEEE Commun. Surv. Tutor. Accepted 2014
Walke, B.H., et al.: IEEE 802 Wireless Systems: Protocols, Multi-Hop Mesh/Relaying, Performance and Spectrum Coexistence. Chichester, West Sussex, England (2006)
Krishna, T.V., Das, A.: A survey on MAC protocols in OSA networks. Comput. Netw. J. (Elsevier) 53(9), 1377–1394 (2009)
Domenico, A.D., et al.: (2012) A Survey on MAC Strategies for Cognitive Radio Networks. IEEE Commun. Surv. Tutor. 14(1), 21–44
Ren, P., et al.: A survey on dynamic spectrum access protocols for distributed cognitive wireless networks. EURASIP J. Wirel. Commun. Netw. 60 (2012). doi:10.1186/1687-1499-2012-60
Cormio, C., Chowdhury, K.R.: A survey on MAC protocols for cognitive radio networks. Ad Hoc Netw. J. (Elsevier) 7(7), 1315–1329 (2009)
Yucek, T., Arslan, H.: A survey of spectrum sensing algorithms for cognitive radio application. IEEE Commun. Surv. Tutor. 11(1), 116–130 (2009)
Denkovski, D., et al.: HOS based goodness-of-fit testing signal detection. IEEE Commun. Lett. 16(3), 310–313 (2012)
Akyildiz, I.F., et al.: Cooperative spectrum sensing in cognitive radio networks: a survey. Elsevier Phys. Commun. J. 4(1), 40–62 (2011)
Aziz, A.M., et al.: A new soft-fusion approach for multiple-receiver wireless communication systems. ETRI J. 33(3), 310–319 (2011)
Ciuonzo, D. et al.: Decision fusion in MIMO wireless sensor networks with channel state information. Paper Presented at 2012 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM), Hoboken, June 2012
Cordeiro, C., et al.: Cognitive PHY and MAC layers for dynamic spectrum access and sharing of TV bands. Paper Presented at 2006 First International Workshop on Technology and Policy for Accessing Spectrum (TAPAS), Boston, Aug 2006
Khan, Z., et al.: Autonomous sensing order selection strategies exploiting channel access information. IEEE Trans. Mob. Comput. 12(2), 274–288 (2013)
Peh, E., et al.: Optimization of cooperative sensing in cognitive radio networks: a sensing-throughput tradeoff view. IEEE Trans. Veh. Technol. 58(9), 5294–5299 (2009)
Mehanna, O., et al.: Blind cognitive MAC protocols. Paper Presented at 2009 IEEE International Conference on Communications, Dresden, June 2009
Li, X., et al.: Optimal cognitive access of Markovian channels under tight collision constraints. IEEE J. Sel. Areas Commun. 29(4), 746–756 (2011)
Zhang, Z., et al.: Channel exploration and exploitation with imperfect spectrum sensing in cognitive radio networks. IEEE J. Sel. Areas Commun. 31(3), 429–441 (2013)
Pollin, S., et al.: A distributed multichannel MAC protocol for multihop cognitive radio networks. IEEE Trans. Veh. Technol. 59(1), 446–459 (2010)
Kim, H., Shin, K.G.: Efficient discovery of spectrum opportunities with MAC-layer sensing in cognitive radio networks. IEEE Trans. Mob. Comput. 7(5), 533–545 (2008)
Su, H., Zhang, X.: Channel exploration and exploitation with imperfect spectrum sensing in cognitive radio networks. IEEE J. Sel. Areas Commun. 26(1), 118–129 (2008)
Hu, D., Mao, S.: A sensing error aware MAC protocol for cognitive radio networks. ICST Trans. Mob. Commun. Appl. 12(2), e1 (2012). http://eudl.eu/doi/10.4108/mca.2012.07-09.e1
Bkassiny, M., et al.: Optimal and low-complexity algorithms for dynamic spectrum access in centralized cognitive radio networks with fading channels. Paper Presented at 2011 IEEE Vehicular Technology Conference (VTC-Spring) 2011, Budapest, May 2011
Zhao, Q., et al.: On myopic sensing for multi-channel opportunistic access: structure, optimality, and performance. IEEE Trans. Wirel. Commun. 7(12), 5431–5440 (2008)
Jia, J., et al.: HC-MAC: A Hardware-constrained cognitive MAC for efficient spectrum management. IEEE J. Sel. Areas Commun. 26(1), 106–117 (2008)
Xia, W., et al.: Optimization of cooperative spectrum sensing in ad-hoc cognitive radio networks. Paper Presented at 2010 IEEE International Conference on Communications, Miami, Dec 2010
Karami, E., et al.: Cluster size optimization in cooperative spectrum sensing. Paper Presented at 2011 Ninth Annual Communication Networks and Services Research (CNSR) Conference, Ottawa, May 2011
Zhao, Y., et al.: Resource allocation in multiuser OFDM system based on ant colony optimization. Paper Presented at 2010 IEEE Wireless Communications and Networking Conference, Sidney, Apr 2010
Jiang, X., et al.: Cross-layer design of partial spectrum sharing for two licensed networks using cognitive radios. Wirel. Commun. Mob. Comput. (2013). doi:10.1002/wcm.2345
Li, F., et al.: Improved quantum genetic algorithm for competitive spectrum sharing in cognitive radios. Paper Presented at 2011 International Conference on Wireless Communications and Signal Processing (WCSP), Nanjing, Nov 2011
Wang, Z., Zhang, W.: Spectrum sharing with limited channel feedback. IEEE Trans. Wirel. Commun. 12(5), 2524–2532 (2013)
Tang, M., et al.: Nonconvex dynamic spectrum allocation for cognitive radio networks via particle swarm optimization and simulated annealing. J. Comput. Netw.: Int. J. Comput. Telecommun. Netw. 55(11), 2690–2699 (2012)
Tan, L.T., Le, L.B.: Distributed MAC protocol for cognitive radio networks: design, analysis, and optimization. IEEE Trans. Veh. Technol. 60(8), 3990–4003 (2010)
Mahmoud, H., et al.: OFDM for cognitive radio: merits and challenges. IEEE Wirel. Commun. 16(2), 6–15 (2009)
Wilcox, D., et al.: On spatial domain cognitive radio using single-radio parasitic antenna arrays. IEEE J. Sel. Areas Commun. 31(3), 571–580(2008)
Chavez-Santiago, R., et al.: Cognitive radio for medical body area networks using ultra wideband. IEEE Wirel. Commun. 19(4), 74–81 (2012)
Kamruzzaman, S.M.: Dynamic TDMA slot reservation protocol for cognitive radio ad hoc networks. Paper Presented at 2010–13th International Conference on Computer and Information Technology (ICCIT), Dhaka, Dec 2010
Cheng, Z.: Cognitive radio based multiple access algorithm for differential frequency hopping network. Paper Presented at 2009 5th International Conference on Wireless Communications, Networking and Mobile Computing (WiCom), Beijing, Sept 2009
Yongwei, H., et al.: Robust multicast beamforming for spectrum sharing-based cognitive radios. IEEE Trans. Signal Process. 60(1), 527–533 (2012)
Tae, W.B.: Capacity and energy efficiency of multi-user spectrum sharing systems with opportunistic scheduling. IEEE Trans. Wirel. Commun. 8(6), 2836–2841 (2009)
Khan, Z., et al.: Modeling the dynamics of coalition formation games for cooperative spectrum sharing in an interference channel. IEEE Trans. Comput. Intell. AI Games 3(1), 17–30 (2011)
Christian, I., et al.: Spectrum mobility in cognitive radio networks. IEEE Commun. Mag. 50(6), 114–121 (2012)
Feng, C., et al.: Cognitive learning-based spectrum handoff for cognitive radio network. Int. J. Comput. Commun. Eng. 1(4), 350–353 (2012)
Zhang, Z., et al.: Self-organization paradigms and optimization approaches for cognitive radio technologies: a survey. IEEE Wirel. Commun. 20(2), 36–42 (2013)
Pawełczak, P., et al.: Performance analysis of multichannel medium access control algorithms for opportunistic spectrum access. IEEE Trans. Veh. Technol. 58(6), 3014–3031 (2009)
Zhao, J., et al.: Distributed coordination in dynamic spectrum allocation networks. Paper Presented at 2005 First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySpan), Baltimore, Nov 2005
Liu, S., et al.: Cluster-based control channel allocation in opportunistic cognitive radio networks. IEEE Trans. Mob. Comput. 11(10), 1436–1449 (2012)
Doerr, C., et al.: Dynamic control channel assignment in cognitive radio networks using swarm intelligence. Paper Presented at 2008 IEEE Global Communications Conference (GLOBECOM), New Orleans (2008)
Bian, K., et al.: Control channel establishment in cognitive radio networks using channel hopping. IEEE J. Sel. Areas Commun. 29(4), 689–703 (2011)
Romaszko, S., et al.: Asynchronous rendezvous protocol for cognitive radio ad hoc networks. Lect. Notes Inst. Comput. Sci. Soc. Inf. Telecommun. Eng. 111, 135–148 (2013)
Masri, A.M., et al.: Common control channel allocation in cognitive radio networks through UWB communication. J. Commun. Netw. (JCN) 14(6), 710–718 (2013)
Federal Communications Commission (FCC). http://www.fcc.gov. Accessed 20 Dec 2013
EC FP7-248303 project QUASAR (2013) Deliverable 4.2. http://quasarspectrum.eu/images/stories/Documents/deliverables/QUASAR_D4.2.pdf. Accessed 20 Dec 2013
Sonnenschein, A., Fishman, P.M.: Radiometric detection of spread-spectrum signals in noise of uncertain power. IEEE Trans. Aerosp. Electron. Syst. 28(3), 654–660 (1992)
Torrieri, D.: The radiometer and its practical implementation. Paper Presented at 2010 IEEE Military Communications Conference (MILCOM), San Jose (2010)
Shen, B., et al.: Energy detection based spectrum sensing for cognitive radios in noise of uncertain power. Paper Presented at 2008 International Symposium on Communications and Information Technologies (ISCIT), Lao, Oct 2008
Mariani, A., et al.: Effects of noise power estimation on energy detection for cognitive radio applications. IEEE Trans. Commun. 59(12), 3410–3420
Rakovic, V., et al.: Cooperative spectrum sensing based on noise power estimation. In: International Symposium on Wireless Personal Multimedia Communications, Atlantic City, June 2013
Rakovic, V., et al.: Clustered network coordinated beamforming for cooperative spectrum sharing of multiple secondary systems. Paper Presented at 2011 International Conference on Cognitive Radio and Advanced Spectrum Management (CogART), Barcelona, Oct 2011
Chae, C.B., et al.: Network coordinated beamforming for cell-boundary users: linear and nonlinear approaches. IEEE J. Sel. Top. Signal Process. 3(6), 1094–1105 (2009)
Chae, C.B., et al.: Coordinated beamforming with limited feedback in the MIMO broadcast channel. IEEE J. Sel. Areas Commun. 26(8), 1505–1515 (2008)
LTE; E-UTRA; UE radio transmission and reception. 3GPP technical specification 36.101
Erceg, V., et al.: TGn channel models. IEEE 802.11 document 802.11-03/940r4 (2004)
Pavlovska, V., et al.: Novel rendezvous protocol for asynchronous cognitive radios in cooperative environments. Paper Presented at 2010 21st Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), Istanbul, pp. 26–30, Sept 2010
Jiang, J.R., et al.: Quorum-based asynchronous power-saving protocols for IEEE 802.11 ad hoc networks. J. Mob. Netw. Appl. 10(1/2), 169–181 (2005)
Maekawa, M.: A p N algorithm for mutual exclusion in decentralized systems. ACM Trans. Comput. Syst. 3(2), 145–159 (1985)
Romaszko, S., Mähönen, P.: Quorum-based channel allocation with asymmetric channel view in cognitive radio networks. Paper Presented at 2011 6th ACM PM2HW2N Workshop (co-located with MSWiM’11), Miami (2011)
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Gavrilovska, L., Denkovski, D., Rakovic, V., Angjelicinoski, M. (2015). Medium Access Control Protocols in Cognitive Radio Networks. In: Di Benedetto, MG., Cattoni, A., Fiorina, J., Bader, F., De Nardis, L. (eds) Cognitive Radio and Networking for Heterogeneous Wireless Networks. Signals and Communication Technology. Springer, Cham. https://doi.org/10.1007/978-3-319-01718-1_4
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