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Cognitive radio: survey on communication protocols, spectrum decision issues, and future research directions

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Abstract

Currently, the radio spectrum is statically allocated and divided between licensed and unlicensed frequencies. Due to this inflexible policy, some frequency bands are growing in scarcity, while large portions of the entire radio spectrum remain unused independently of time and location. Cognitive Radio is a recent network paradigm that aims a more flexible and efficient usage of the radio spectrum. Basically, it allows wireless devices to opportunistically access portions of the entire radio spectrum without causing any harmful interference to licensed users. The present document surveys the literature on Cognitive Radio. It aims to provide a comprehensive and self-contained description of this research topic area, mainly focusing on communication protocols, spectrum decision issues, and future research directions. It is a tutorial in nature and consequently does not require any previous knowledge about Cognitive Radio. Readers are only required to have some general background on wireless data networks. Emphasis is put on Cognitive Radio genesis, issues that must be addressed, related technologies, standardization efforts, the state of the art, and future research directions according to the vision of the authors.

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Notes

  1. DCF (Distributed Coordination Function), which is based on the CSMA/CA (Carrier Sense Multiple Access with Collision Avoidance) algorithm, is one of the basic access protocols supported by the IEEE 802.11 standard. It is one of the today's main protocols for wireless local area networks.

  2. In geographic routing, a node knows the location of the destination and that of the candidate forwarding nodes within its range, and therefore can choose the next hop that is closer towards the destination.

References

  1. FCC Spectrum Policy Task Force. (2002). Report of the spectrum efficiency working group.

  2. Lopez-Benitez, M., Umbert, A., & Casadevall, F. (2009). Evaluation of spectrum occupancy in Spain for cognitive radio applications. In 69th Conference on vehicular technology, 2009 (pp. 1–5). VTC Spring 2009, IEEE.

  3. Tsagkaris, K., Katidiotis, A., & Demestichas, P. (2008). Neural network-based learning schemes for cognitive radio systems. Computer Communications (Elsevier), 31(14), 3394–3404.

    Google Scholar 

  4. Akyildiz, I., Lee, W., Vuran, M., & Mohanty, S. (2008). A survey on spectrum management in cognitive radio networks. Communications Magazine, IEEE, 46, 40–48.

    Article  Google Scholar 

  5. Ghaboosi, K., Latva-aho, M., & Xiao, Y. (2008). A distributed multi-channel cognitive MAC protocol for IEEE 802.11 s wireless mesh networks. In 3rd International conference on cognitive radio oriented wireless networks and communications, 2008 (pp. 1–8). CrownCom 2008.

  6. Niyato, D., & Hossain, E. (2009). Cognitive radio for next-generation wireless networks: an approach to opportunistic channel selection in IEEE 802.11-based wireless mesh—[accepted from open call]. Wireless Communications, IEEE, 16, 46–54.

    Article  Google Scholar 

  7. Vuran, M., & Akyildiz, I. (2007). A-MAC: Adaptive medium access control for next generation wireless terminals. EEE/ACM Transactions Network, 15, 574–587.

    Article  Google Scholar 

  8. Akyildiz, I., Lee, W., & Chowdhury, K. (2009). CRAHNs: Cognitive radio ad hoc networks. Ad Hoc Networks (Elsevier), 7(5), 810–836.

    Article  Google Scholar 

  9. Beltrán, F., Gutiérrez, J., & Melús, J. (2010). Technology and market conditions towards a new competitive landscape in the wireless access market. IEEE Communications Magazine, pp. 46–52.

  10. Chen, T., Zhang, H., Matinmikko, M., & Katz,M. (2008). CogMesh: Cognitive wireless mesh networks (pp. 1–6). GLOBECOM workshops, 2008 IEEE.

  11. Mueck, M., et al. (2010). ETSI reconfigurable radio systems: status and future directions on software defined radio and cognitive radio standards. IEEE Communications Magazine, 48(9), 78–86.

    Article  Google Scholar 

  12. Chowdhury, K., & Melodia, T. (2010). Platforms and test beds for experimental evaluation of cognitive ad hoc networks. IEEE Communications Magazine, 48(9), 96–104.

    Article  Google Scholar 

  13. Yucek, T., & Arslan, H. (2009). A survey of spectrum sensing algorithms for cognitive radio applications. Communications Surveys & Tutorials, IEEE, 11, 116–130.

    Article  Google Scholar 

  14. Cormio, C., & Chowdhury, K. (2009). A survey on MAC protocols for cognitive radio networks. Ad Hoc Networks (Elsevier), 7(7), 1315–1329.

    Article  Google Scholar 

  15. Wang, H., Qin, H., & Zhu, L. (2008). A survey on MAC protocols for opportunistic spectrum access in cognitive radio networks. In International conference on computer science and software engineering (pp. 214–218).

  16. Amanna, A., & Reed, J. (2010). Survey of cognitive radio architectures. In Proceedings of the IEEE southeast conference 2010 (pp. 292–297).

  17. Renk, T., Kloeck, C., Burgkhardt, D., Jondral, F., Grandblaise, D., Gault, S., et al. (2008). Bio-inspired algorithms for dynamic resource allocation in cognitive wireless networks. Mobile Networks and Applications, 13(5), 431–441.

    Article  Google Scholar 

  18. Mody, A., Sherman, M., Martinez, R., Reddy, R., & Kiernan, T. (2008). Survey of IEEE standards supporting cognitive radio and dynamic spectrum access. In Military communications conference, 2008 (pp. 1–7). MILCOM 2008. IEEE.

  19. Zhao, Q., & Swami, A. (2007). A survey of dynamic spectrum access: Signal processing and networking perspectives. In IEEE international conference on acoustics, speech and signal processing, 2007 (pp. IV-1349–IV-1352). ICASSP 2007.

  20. Issariyakul, T., Pillutla, L., & Krishnamurthy, V. (2009). Tuning radio resource in an overlay cognitive radio network for TCP: Greed Isn’t good (pp. 57–63). IEEE Communications Magazine.

  21. Wellens, M., & Mähönen, P. (2010). Lessons learned from an extensive spectrum occupancy measurement campaign and a stochastic duty cycle model. Mobile Networks and Applications, 15(3), 461–474.

    Article  Google Scholar 

  22. Yu, F., Tang, H., Huang, M., Li, Z., & Mason, P. (2009). Defense against spectrum sensing data falsification attacks in mobile ad hoc networks with cognitive radios. In Military communications conference (pp. 1–7). MILCOM 2009. IEEE.

  23. Timmers, M., Pollin, S., Dejonghe, A., Van der Perre, L., & Catthoor, F. (2010). A distributed multichannel MAC protocol for multihop cognitive radio networks. IEEE Transactions on Vehicular Technology, 59, 446–459.

    Article  Google Scholar 

  24. Malady, A., & da Silva, C. (2008). Clustering methods for distributed spectrum sensing in cognitive radio systems. In Military communications conference, 2008 (pp. 1–5). MILCOM 2008, IEEE.

  25. Wang, X., Wong, A., & Ho, P. (2010). Dynamically optimized spatiotemporal prioritization for spectrum sensing in cooperative cognitive radio. Wireless Networks, 16(4), 889–901.

    Article  Google Scholar 

  26. Baddour, K., Üreten, O., & Willink, T. (2010). A distributed message-passing approach for clustering cognitive radio networks. Wireless Networks. doi:10.1007/s11277-010-0010-z.

  27. Zhao, Q., & Sadler, B. (2007). A survey of dynamic spectrum access. Signal Processing Magazine, IEEE, 24, 79–89.

    Article  Google Scholar 

  28. Hamdaoui, B., & Shin, K. (2008). OS-MAC: An efficient mac protocol for spectrum-agile wireless networks. IEEE Transactions on Mobile Computing, 7, 915–930.

    Article  Google Scholar 

  29. Wang, J., Abolhasan, M., Safaei, F., & Franklin, D. (2007). A survey on control separation techniques in multi-radio multi-channel MAC protocols. In International Symposium on communications and information technologies, 2007 (pp. 854–859). ISCIT ‘07.

  30. Cormio, C., & Chowdhury, K. (2010). Common control channel design for cognitive radio wireless ad hoc networks using adaptive frequency hopping. Ad Hoc Networks (Elsevier), 8(4), 430–438.

    Article  Google Scholar 

  31. Ma, L., Han, X., & Shen, C. (2005). Dynamic open spectrum sharing MAC protocol for wireless ad hoc networks. In First IEEE International Symposium on new frontiers in dynamic spectrum access networks, 2005 (pp. 203–213). DySPAN 2005.

  32. Brown, T., & Sethi, A. (2008). Potential cognitive radio denial-of-service vulnerabilities and protection countermeasures: A multi-dimensional analysis and assessment. Mobile Networks and Applications, 13(5), 516–532.

    Article  Google Scholar 

  33. Sharma, A., & Belding, E. (2008). FreeMAC: Framework for multi-channel mac development on 802.11 hardware. In Proceedings of the ACM workshop on programmable routers for extensible services of tomorrow (pp. 69–74). Seattle, WA: ACM.

  34. Ji, Z., & Liu, K. (2007). Cognitive radios for dynamic spectrum access—dynamic spectrum sharing: A game theoretical overview. Communications Magazine, IEEE, 45, 88–94.

    Article  MathSciNet  Google Scholar 

  35. Jo, O., Choi, H., & Cho, D. (2009). Seamless spectrum handover improving cell outage in cognitive radio systems. In 4th International conference on cognitive radio oriented wireless networks and communications, 2009 (pp. 1–6). CROWNCOM ‘09.

  36. Jia, J., & Zhang, Q. (2009). A testbed development framework for cognitive radio networks. In IEEE international conference on communications, 2009 (pp. 1–5). ICC ‘09.

  37. Eljack, S., Huang, B., Tu, L., & Zhang, P. (2009). Synchronized multi-channel cognitive MAC protocol with efficient solutions for second spectrum access. In Ubiquitous, Symposia and workshops on autonomic and trusted computing, 2009 (pp. 477–481). UIC-ATC ‘09.

  38. Grace, D., Chen, J., Jiang, T., & Mitchell, P. (2009). Using cognitive radio to deliver ‘Green’ communications. In 4th International conference on cognitive radio oriented wireless networks and communications, 2009 (pp. 1–6). CROWNCOM ‘09.

  39. Yau, A., Komisarczuk, P., & Teal, P. (2008). On multi-channel MAC protocols in cognitive radio networks. In Telecommunication networks and applications conference, 2008 (pp. 300–305). ATNAC 2008, Australasian.

  40. IEEE 802.22 WRAN WG Website, (Online). (2009). Available: http://www.ieee802.org/22/. Accessed 2 Dec 2009.

  41. Sherman, M., Mody, A., Martinez, R., Rodriguez, C., & Reddy, R. (2008). IEEE Standards supporting cognitive radio and networks, dynamic spectrum access, and coexistence. Communications Magazine, IEEE, 46, 72–79.

    Article  Google Scholar 

  42. Ko, G., Franklin, A., You, S., Pak, J., Song, M., & Kim, C. (2010). Channel management in IEEE 802.22 WRAN systems. IEEE Communications Magazine, 48(9), 88–94.

    Article  Google Scholar 

  43. Guan, Q., Yu, F., Jiang, S., & Wei, G. (2010). Prediction-based topology control and routing in cognitive radio mobile Ad Hoc networks. IEEE Transactions on Vehicular Technology. doi:10.1109/TVT.2010.2069105.

  44. Su, H., & Zhang, X. (2008). Cross-layer based opportunistic MAC protocols for QoS provisioning over cognitive radio wireless networks. IEEE Journal on Selected Areas in Communications, 26, 118–129.

    Article  Google Scholar 

  45. Le, L., & Hossain, E. (2008). A MAC protocol for opportunistic spectrum access in cognitive radio networks. In Wireless communications and networking conference, 2008 (pp. 1426–1430). WCNC 2008, IEEE.

  46. Joe, I., & Son, S. (2008). Dynamic spectrum allocation MAC protocol based on cognitive radio for QoS support. In Japan–China joint workshop on frontier of computer science and technology, 2008 (pp. 24–29). FCST ‘08.

  47. Hsu, A., Weit, D., & Kuo, C. (2007). A cognitive MAC protocol using statistical channel allocation for wireless Ad-Hoc networks. In Wireless communications and networking conference, 2007 (pp. 105–110). WCNC 2007. IEEE.

  48. Ghaboosi, K., MacKenzie, A., DaSilva, L., Abdallah, A., & Latva-Aho, M. (2009). A channel selection mechanism based on incumbent appearance expectation for cognitive networks. In Wireless communications and networking conference, 2009 (pp. 1–6). WCNC 2009, IEEE.

  49. Wang, X., & Garcia-Luna-Aceves, J. (2010). Collaborative routing, scheduling and frequency assignment for wireless Ad Hoc networks using spectrum-agile radios. Wireless Networks. doi:10.1007/s11276-010-0271-1.

  50. Chowdhury, K., & Felice, M. (2009). Search: A routing protocol for mobile cognitive radio ad-hoc networks. Computer Communications (Elsevier), 32(18), 1983–1997.

    Google Scholar 

  51. Yu, F., Sun, B., Krishnamurthy, V., & Ali, S. (2010). Application layer QoS optimization for multimedia transmission over cognitive radio networks. Wireless Networks. doi:10.1007/s11276-010-0285-8.

  52. Zhao, Q., Tong, L., Swami, A., & Chen, Y. (2007). Decentralized cognitive MAC for opportunistic spectrum access in ad hoc networks: a POMDP framework. IEEE Journal on Selected Areas in Communications, 25(3), 589–600.

    Article  Google Scholar 

  53. Clancy, C., Hecker, J., Stuntebeck, E., & O’Shea, T. (2007). Applications of Machine Learning to Cognitive Radio Networks. Wireless Communications, IEEE, 4, 47–52.

    Article  Google Scholar 

  54. Li, X., & Zekavat, S. (2009). Traffic pattern prediction based spectrum sharing for cognitive radios. In W. Wang, (Ed.), Cognitive radio systems (pp. 77–95). Sciyo.com.

  55. Xiukui, L., & Zekavat, S. (2008). Traffic pattern prediction and performance investigation for cognitive radio systems. In IEEE Conference on wireless communications and networking, 2008 (pp. 894–899). WCNC 2008.

  56. Hoyhtya, M., Pollin, S., Mammela, A. (2008). Performance improvement with predictive channel selection for cognitive radios. In First international workshop on cognitive radio and advanced spectrum management, 2008 (pp. 1–5). CogART 2008.

  57. Wang, Z., & Salous, S. (2008). Time series arima model of spectrum occupancy for cognitive radio. In Seminar on cognitive radio and software defined radios: technologies and techniques, 2008 (pp. 1–4). IET.

  58. Jiang, T., Grace, D., & Liu, Y. (2008). Cognitive radio spectrum sharing schemes with reduced spectrum sensing requirements. In 2008 IET seminar on cognitive radio and software defined radios: Technologies and techniques (pp. 1–5).

  59. Jiang, T., Grace, D., & Liu, Y. (2008). Performance of cognitive radio reinforcement spectrum sharing using different weighting factors. In Third international conference on communications and networking in China, 2008 (pp. 1195–1199). ChinaCom 2008.

  60. Kim, H., & Shin, K. G. (2008). Efficient discovery of spectrum opportunities with MAC-layer sensing in cognitive radio networks. IEEE Transactions on Mobile Computing, 7(5), 533–545.

    Article  MathSciNet  Google Scholar 

  61. Akyildiz, I., & Wang, X. (2005). A survey on wireless mesh networks. Communications Magazine, IEEE, 43, S23–S30.

    Article  Google Scholar 

  62. Newman, T., Hasan, S., Depoy, D., Bose, T., & Reed, J. (2010). Designing and deploying a building-wide cognitive radio network test bed. IEEE Communications Magazine, 48(9), 106–112.

    Article  Google Scholar 

  63. Sutton, P., Fahmy, S., Nolan, K., Özgul, B., Rondeau, T., Noguera, J., & Doyle, L. (2010). Iris: An architecture for cognitive radio networking testbeds. IEEE Communications Magazine, 48(9), 114–12275 (ORBIT Testbed, [Online]. Available: http://www.orbit-lab.org. Accessed 2 Dec 2 2009).

  64. ORBIT Testbed, (Online). (2009). Available: http://www.orbit-lab.org. Accessed 2 Dec 2009.

  65. Pawelczak, P., Prasad, R., Xia, L., & Niemegeers, I. (2005). Cognitive radio emergency networks—requirements and design. In First IEEE international Symposium on new frontiers in dynamic spectrum access networks, 2005 (pp. 601–606). DySPAN 2005.

  66. Hsieh, H., Liu, T., Liao, W., & Ho, T. (2008). Moving toward higher speed WLANs through dynamic spectrum access in the unlicensed band. In European conference on wireless technology, 2008 (pp. 111–114). EuWiT 2008.

  67. Nan, H., Hyon, T., & Yoo, S. (2007). Distributed coordinated spectrum sharing MAC protocol for cognitive radio. In 2nd IEEE international Symposium on new frontiers in dynamic spectrum access networks (pp. 240–249). DySPAN 2007.

  68. Kondareddy, Y., & Agrawal, P. (2008). Synchronized MAC protocol for multi-hop cognitive radio networks. In IEEE international conference on communications, 2008 (pp. 3198–3202). ICC ‘08.

  69. Zhang, Q., Fitzek, F., & Iversen, V. (2008). Cognitive radio MAC protocol for WLAN. In IEEE 19th international Symposium on personal, indoor and mobile radio communication, 2008 (pp. 1–6). PIMRC 2008.

  70. Choi, N., Patel, M., & Venkatesan, S. (2006). A Full duplex multi-channel MAC protocol for multi-hop cognitive radio networks. In 1st International conference on cognitive radio oriented wireless networks and communications (pp. 1–5).

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Acknowledgments

The authors would like to thank the anonymous reviewers for their constructive comments and suggestions which have significantly contributed to improve this paper. The first author is also grateful to the support which was provided in the context of PROTEC, a Portuguese PhD supporting program.

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Correspondence to José Marinho.

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Marinho, J., Monteiro, E. Cognitive radio: survey on communication protocols, spectrum decision issues, and future research directions. Wireless Netw 18, 147–164 (2012). https://doi.org/10.1007/s11276-011-0392-1

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