Cognitive Radio: From Theory to Practical Network Engineering

  • Chapter
  • First Online:
New Directions in Wireless Communications Research

Under utilization of radio spectrum in traditional wireless communication systems [30], along with the increasing spectrum demand from emerging wireless applications, is driving the development of new spectrum allocation policies for wireless communications. These new spectrum allocation policies, which will allow unlicensed users (i.e., secondary users) to access the radio spectrum when it is not occupied by licensed users (i.e., primary users) will be exploited by the cognitive radio (CR) technology. Cognitive radio will improve spectrum utilization in wireless communication systems while accommodating the increasing amount of services and applications in wireless networks. A cognitive radio transceiver is able to adapt to the dynamic radio environment and the network parameters to maximize the utilization of the limited radio resources while providing flexibility in wireless access [45].

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (Canada)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (Canada)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (Canada)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free ship** worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (Canada)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free ship** worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. M. Alicherry, R. Bhatia, and L. (E).Li, “Joint channel assignment and routing for throughput optimization in multi-radio wireless mesh networks,” in Proc. ACM Mobicom’05.

    Google Scholar 

  2. P. Bahl, A. Chandra, and J. Dunagan, “SSCH: Slotted seeded channel hop** for capacity improvement in IEEE 802.11 ad hoc wireless networks,” in Proc. ACM Mobicom’04.

    Google Scholar 

  3. M. M. Buddhikot, “Understanding dynamic spectrum access: Models, taxonomy and challenges,” in Proc. IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN), April 2007, pp. 649–663.

    Google Scholar 

  4. S. H. Seyedmehdi, Y. **n, and Y. Lian, “An achievable rate region for the causal cognitive radio,” in Proc. Allerton Conf. Commun. Control and Comp., Monticello, IL, Sept. 2007.

    Google Scholar 

  5. G. Caire and S. Shamai, “On the achievable throughput of a multi-antenna gaussian broadcast channel,” IEEE Trans. Inf. Theory, vol. 49, no. 7, pp. 1691–1705, July 2003.

    Article  MathSciNet  Google Scholar 

  6. M. Cao, X. Wang, S. -J. Kim, and M. Madihian, “Multi-hop wireless backhaul networks: A cross-layer design paradigm,” IEEE J. Sel. Areas Commun., vol. 25, no. 4, pp. 738–748, May 2007.

    Article  Google Scholar 

  7. A. Carleial, “Interference channels,” IEEE Trans. Inf. Theory, vol. IT-24, no. 1, pp. 60–70, Jan. 1978.

    Article  MathSciNet  Google Scholar 

  8. N. B.Chang and M. Liu, “Optimal channel probing and transmission scheduling for opportunistic spectrum access,” in Proc. ACM Mobicom’07, Sept. 2007.

    Google Scholar 

  9. N. B. Chang and M. Liu, “Competitive analysis of opportunistic spectrum access strategies,” in Proc. IEEE INFOCOM’08, April 2008.

    Google Scholar 

  10. Y. Chen, Q. Zhao, and A. Swami, “Joint design and separation principle for opportunistic spectrum access in the presence of sensing errors,” IEEE Trans. Inf. Theory, vol. 54, no. 5, pp. 2053–2071, May 2008.

    Article  MathSciNet  Google Scholar 

  11. P. Cheng, G. Yu, Z. Zhang, H.-H. Chen, and P. Qiu, “On the maximum sum-rate capacity of cognitive multiple access channel,” http://arxiv.org/abs/cs.IT/0612024.

  12. H. Chong, M. Motani, H. Garg, and H. E. Gamal, “On the han-kobayashi region for the interference channel,” To appear in IEEE Trans. Inf. Theory, vol. 54, no. 7, pp. 3188–3195, July 2008.

    Google Scholar 

  13. Y. S. Chow, H. Robbins, and D. Siegmund, Great Expectations: The Theory of Optimal Stop**, Houghton Mifflin Company, Boston, USA, 1971.

    Google Scholar 

  14. T. Clancy, “Achievable capacity under the interference temperature model,” IEEE Conference on Computer Communications (INFOCOM), May 2007.

    Google Scholar 

  15. C. Cordeiro and K. Challapali, “C-MAC: A cognitive MAC protocol for multi-channel wireless networks,” in Proc. DySPAN’07, April 2007.

    Google Scholar 

  16. M. Costa, “Writing on dirty paper,” IEEE Trans. Inf. Theory, vol. IT-29, pp. 439–441, May 1983.

    Article  Google Scholar 

  17. T. Cover and J. Thomas, Elements of Information Theory New York: John Wiley & Sons, 1991.

    Book  MATH  Google Scholar 

  18. I. Csiszár and J. Kőrner, Information Theory: Coding Theorems for Discrete Memoryless System. Akadémiai Kiadó, Budapest, Hungary, 1981.

    Google Scholar 

  19. C. da Silva, B. Choi, and K. Kim, “Distributed spectrum sensing for cognitive radio systems,” in Information Theory and Applications ITA Workshop, Feb. 2007.

    Google Scholar 

  20. N. Devroye, “Information theoretic limits of cooperation and cognition in wireless networks,” Ph.D. dissertation, Harvard, 2007.

    Google Scholar 

  21. N. Devroye, P. Mitran, M. Sharif, S. S. Ghassemzadeh, and V. Tarokh, “Information theoretic analysis of cognitive radio systems,” in Cognitive Wireless Communication Networks, V. Bhargava and E. Hossain, Eds. Springer, 2007.

    Google Scholar 

  22. N. Devroye, P. Mitran, and V. Tarokh, “Achievable rates in cognitive radio channels,” in 39th Annual Conference on Information Sciences and Systems (CISS), Mar. 2005.

    Google Scholar 

  23. N. Devroye, P. Mitran, and V. Tarokh, “Achievable rates in cognitive networks,” in 2005 IEEE International Symposium on Information Theory, Sept. 2005.

    Google Scholar 

  24. N. Devroye, P. Mitran, and V. Tarokh, “Achievable rates in cognitive radio channels,” IEEE Trans. Inf. Theory, vol. 52, no. 5, pp. 1813–1827, May 2006.

    Article  MathSciNet  Google Scholar 

  25. N. Devroye, P. Mitran, and V. Tarokh, “Cognitive decomposition of wireless networks,” in Proc. CROWNCOM, Mykonos Island, Greece, Mar. 2006.

    Google Scholar 

  26. N. Devroye and M. Sharif, “The multiplexing gain of MIMO X-channels with partial transmit side-information,” in IEEE International Symposium on Information Theory, June 2007.

    Google Scholar 

  27. N. Devroye and V. Tarokh, “Fundamental limits of cognitive radio networks,” in Cognitive Wireless Networks: Concepts, Methodologies and Vision, F. Fitzek and M. Katz, Eds. Springer, New York, USA, 2007.

    Google Scholar 

  28. R. Etkin, A. Parekh, and D. Tse, “Spectrum sharing for unlicensed bands,” IEEE J. Sel. Areas Commun., vol. 25, no. 3, pp. 517–528, Apr. 2007.

    Article  Google Scholar 

  29. FCC, Spectrum Policy Task Force Report, No. 02-155, Nov. 2002.

    Google Scholar 

  30. G. Ganesan and Y. Li, “Cooperative spectrum sensing in cognitive radio networks,” in New Frontiers in Dynamic Spectrum Access Networks (DYSPAN), Nov. 2005.

    Google Scholar 

  31. M. Gastpar, “On capacity under receive and spatial spectrum-sharing constraints,” IEEE Trans. Inf. Theory, vol. 53, pp. 471–487, Feb. 2007.

    Article  MathSciNet  Google Scholar 

  32. S. Geirhofer, L. Tong, and B. M. Sadler, “Dynamic spectrum access in the time domain: Modeling and exploiting whitespace,” IEEE Commun. Mag., vol. 45, no. 5, pp. 66–72, May 2007.

    Article  Google Scholar 

  33. S. Gel’fand and M. Pinsker, “Coding for channels with random parameters,” Probl. Contr. Inf. Theory, vol. 9, no. 1, pp. 19–31, 1980.

    MATH  MathSciNet  Google Scholar 

  34. A. Ghasemi and E. Sousa, “Collaborative spectrum sensing for opportunistic access in fading environments,” in New Frontiers in Dynamic Spectrum Access Networks (DYSPAN), Nov. 2005.

    Google Scholar 

  35. A. Ghasemi and E. Sousa, “Capacity of fading channels under spectrum-sharing constraints,” in Proc. IEEE Int. Conf. Commun., Istanbul, Turkey, June 2006.

    Google Scholar 

  36. A. Goldsmith, S. Jafar, I. Maric, and S. Srinivasa, “Breaking spectrum gridlock with cognitive radios: An information theoretic perspective,” Proceedings of the IEEE, vol. 97, no. 5, pp. 894–914, May 2009.

    Google Scholar 

  37. P. Grover and A. Sahai, “On the need for knowledge of the phase in exploiting known primary transmissions,” 2nd IEEE Int. Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2007 (DySPAN 2007), pp. 462–471, Dublin, Ireland, 17–20 April 2007.

    Google Scholar 

  38. P. Gupta and P. R. Kumar, “The capacity of wireless networks,” IEEE Trans. Inf. Theory, vol. 46, no. 2, pp. 388–404, Mar. 2000.

    Article  MATH  MathSciNet  Google Scholar 

  39. B. Hamdaoui and K. G. Shin, “OS-MAC: An efficient MAC protocol for spectrum-agile wireless networks,” IEEE Trans. Mobile Comput., vol. 7, no. 8, pp. 915–930, Aug. 2008.

    Article  Google Scholar 

  40. T. Han and K. Kobayashi, “A new achievable rate region for the interference channel,” IEEE Trans. Inf. Theory, vol. IT-27, no. 1, pp. 49–60, 1981.

    Article  MathSciNet  Google Scholar 

  41. Z. J. Hass and J. Deng, “Dual busy tone multiple access (DBTMA) – A multiple access control scheme for ad hoc networks,” IEEE Trans. Commun., vol. 50, no. 6, pp. 975–985, Jun. 2002.

    Article  Google Scholar 

  42. S. Haykin, “Cognitive radio: Brain-empowered wireless communications,” IEEE J. Sel. Areas Commun., vol. 23, no. 2, pp. 201–220, Feb. 2005.

    Google Scholar 

  43. C. Heegard and A. E. Gamal, “On the capacity of computer memories with defects,” IEEE Trans. Inf. Theory, vol. 29, pp. 731–739, Sept. 1983.

    Article  MATH  Google Scholar 

  44. S.-C. Hong, M. Vu, and V. Tarokh, “Cognitive sensing based on side information,” Sarnoff Conf., Apr. 2008.

    Google Scholar 

  45. N. Hoven and A. Sahai, “Power scaling for cognitive radio,” Int Conf. Wireless Netw., Comm. Mobile Comput., vol. 1, pp. 250–255, Jun. 2005.

    Article  Google Scholar 

  46. A. C. C. Hsu, D. S. L. Wei, and C.-C. J. Kuo, “A cognitive MAC protocol using statistical channel allocation for wireless ad-hoc networks,” in Proc. IEEE WCNC’07.

    Google Scholar 

  47. J. Huang, R. Berry, and M. Honig, “Distributed interference compensation for wireless networks,” IEEE J. Sel. Areas Commun., vol. 24, no. 5, pp. 1074–1084, May 2006.

    Article  Google Scholar 

  48. J. Huang, R. Berry, and M. Honig, “Auction-based spectrum sharing,” ACM/Kluwer J. Mobile Netw. Appl. (MONET), vol. 11, no. 3, pp. 405–418, Jun. 2006.

    Article  Google Scholar 

  49. S. Huang, X. Liu, and Z. Ding, “Opportunistic spectrum access in cognitive radio networks,” in Proc. IEEE INFOCOM 2008, Apr. 2008.

    Google Scholar 

  50. T. Hunter, A. Hedayat, M. Janani, and A. Nostratinia, “Coded cooperation with space-time transmission and iterative decoding,” in WNCG Wireless, Oct. 2003.

    Google Scholar 

  51. M. Islam, Y.-C. Liang, and A. T. Hoang, “Joint power control and beamforming for secondary spectrum sharing,” in Proc. of IEEE 66th Vehicular Technology Conference (VTC), Oct. 2007.

    Google Scholar 

  52. S. A. Jafar and S. Srinivasa, “Capacity limits of cognitive radio with distributed and dynamic spectral activity,” IEEE J. Sel. Areas Commun., vol. 25, pp. 529–537, Apr. 2007.

    Article  Google Scholar 

  53. S. Jafar and S. Shamai, “Degrees of freedom region for the MIMO X channel,” IEEE Trans. Inf. Theory, vol. 54, no. 1, pp. 151–170, Jan. 2008.

    Article  MathSciNet  Google Scholar 

  54. S.-W. Jeon, N. Devroye, M. Vu, S.-Y. Chung, and V. Tarokh, “Cognitive networks achieve throughput scaling of a homogeneous network,” IEEE Trans. Info. Theory, submitted Mar 2008.

    Google Scholar 

  55. J. Jia, Q. Zhang, and X. Shen, “HC-MAC: A hardware-constrained cognitive MAC for efficient spectrum management,” IEEE J. Sel. Areas Commun., vol. 26, no. 1, pp. 106–117, Jan. 2008.

    Article  Google Scholar 

  56. J. Jiang and X. **n, “On the achievable rate regions for interference channels with degraded message sets,” submitted to IEEE Trans. Inf. Theory, vol. 54, no. 10, pp. 4707–4712, Apr. 2007.

    Google Scholar 

  57. J. Jiang, X. **n, and H. Garg, “Interference channels with common information,” submitted to IEEE Trans. Inf. Theory, vol. 54, no. 1, pp. 171–187, Jan. 2008.

    Google Scholar 

  58. A. Jovicic and P. Viswanath, “Cognitive radio: An information-theoretic perspective,” Proc. IEEE ISIT 2006, Seattle, USA, July 9–14, 2006.

    Google Scholar 

  59. A. Karnik, A. Iyer, and C. Rosenberg, “Throughput-optimal configuration of fixed wireless networks,” IEEE/ACM Trans. Networking, vol. 16, no. 5, pp. 1161–1174, Oct. 2008.

    Google Scholar 

  60. S. M. Kay, Fundamentals of Statistical Signal Processing, Volume 2: Detection Theory. Prentice Hall, New Jersey, USA, 1998.

    Google Scholar 

  61. F. P. Kelly, A. Maulloo, and D. Tan, “Rate control for communication networks: Shadowing prices, proportional fairness, and stability,” J. Oper. Res. Soc., vol. 49, no. 3, pp. 237–252, Mar. 1998.

    Article  MATH  Google Scholar 

  62. D. I. Kim, L. Le, and E. Hossain, “Joint rate and power allocation for cognitive radios in dynamic spectrum access environment,” IEEE Trans. Wireless Commun., vol. 7, no. 12, pp. 5517–5527, Dec. 2008.

    Google Scholar 

  63. P. J. Kolodzy, “Interference temperature: A metric for dynamic spectrum utilization,” Int. J. Netw. Manag., vol. 16, no. 2, pp. 103–113, Mar. 2006.

    Google Scholar 

  64. O. Koyluoglu and H. Gamal, “On power control and frequency re-use in the two-user cognitive channel,” submitted to IEEE Trans. Wireless Commun., 2007.

    Google Scholar 

  65. S. Kulkarni and C. Rosenberg, “Opportunistic scheduling: Generalizations to include multiple constraints, multiple Interfaces, and short term fairness,” ACM/Kluwer Wireless Netw. J. (WINET), vol. 11, no. 5, pp. 557–569, Sept. 2005.

    Google Scholar 

  66. A. Kusnetsov and B. Tsybakov, “Coding in a memory with defective cells,” Prob. Pered. Inform., vol. 10, pp. 52–60, Apr.–Jun. 1974.

    Google Scholar 

  67. L. Le and E. Hossain, “OSA-MAC: A MAC protocol for opportunistic spectrum access in cognitive radio networks,” in Proc. IEEE WCNC’08, Mar.–Apr. 2008.

    Google Scholar 

  68. L. Le and E. Hossain, “Resource allocation for spectrum underlay in cognitive radio networks,” IEEE Trans. Wireless Commun., vol. 7, no. 12.

    Google Scholar 

  69. J. Li, C. Blake, D. S. J. D. Couto, H. I. Lee, and R. Morris, “Capacity of ad hoc wireless networks,” in Proc. ACM Mobicom’01.

    Google Scholar 

  70. Y. Liang, A. Somekh-Baruch, H. V. Poor, S. S. (Shitz), and S.Verdú, “Capacity of cognitive interference channels with and without secrecy,” submitted to IEEE Trans. Inf. Theory, vol. 55, no. 2, pp. 604–619, Feb. 2009.

    Google Scholar 

  71. Y. C. Liang, Y. Zeng, E. C. Y. Peh, and A. T. Hoang, “Sensing-throughput tradeoff for cognitive radio networks,” IEEE Trans. Wireless Commun., vol. 7, no. 4, pp. 1326–1337, Apr. 2008.

    Article  Google Scholar 

  72. X. Liu, E. K. P. Chong, and N. B. Shroff, “Opportunistic transmission scheduling with resource-sharing constraints in wireless networks,” IEEE J. Sel. Areas Commun., vol. 19, no. 10, pp. 2053–2065, Oct. 2001.

    Article  Google Scholar 

  73. X. Luo and K. Kar, “Joint scheduling and power allocation in multi-channel access point networks under QoS constraints,” in Proc. IEEE ICC’08, May 2008.

    Google Scholar 

  74. L. Ma, X. Han, and C. C. Shen, “Dynamic open spectrum sharing MAC protocol for wireless ad hoc networks,” in Proc. DySPAN’05, Nov. 2005.

    Google Scholar 

  75. M. Maddah-Ali, A. Motahari, and A. Khandani, “Signaling over MIMO multi-base systems: combination of multi-access and broadcast schemes,” in 2006 IEEE International Symposium on Information Theory, Jul. 2006.

    Google Scholar 

  76. M. Marcus, “Unlicensed cognitive sharing of TV spectrum: The controversy at the federal communications commission,” IEEE Comm. Mag., vol. 43, no. 5, pp. 24–25, May 2005.

    Google Scholar 

  77. I. Maric, R. Yates, and G. Kramer, “Capacity of interference channels with partial transmitter cooperation,” IEEE Trans. Inf. Theory, vol. 53, pp. 3536–3548, Oct. 2007.

    Article  MathSciNet  Google Scholar 

  78. S. M. Mishra, A. Sahai, and R. W. Brodersen, “Cooperative sensing among cognitive radios,” in Proc. IEEE Int. Conf. Commun., Istanbul, Turkey, Jun. 2006.

    Google Scholar 

  79. J. Mitola, “Cognitive radio,” Ph.D. dissertation, Royal Institute of Technology (KTH), 2000.

    Google Scholar 

  80. P. Mitran, N. Devroye, and V. Tarokh, “On compound channels with side-information at the transmitter,” IEEE Trans. Inf. Theory, vol. 52, no. 4, pp. 1745–1755, Apr. 2006.

    Article  MathSciNet  Google Scholar 

  81. J. Mo, H.-S.W. So, and J. Walrand, “Comparison of multichannel MAC protocols,” IEEE Trans. Mobile Comput., vol. 7, no. 1, pp. 50–65, Jan. 2008.

    Article  Google Scholar 

  82. J. Mo and J. Walrand, “Fair end-to-end window-based congestion control,” IEEE/ACM Trans. Netw., vol. 8, no. 5, pp. 556–567, Oct. 2000.

    Article  Google Scholar 

  83. D. Niyato and E. Hossain, “Competitive spectrum sharing in cognitive radio networks: A dynamic game approach,” IEEE Trans. Wire less Commun., vol. 7, no. 7, pp. 2651–2660, Jul. 2008.

    Article  Google Scholar 

  84. M. Oner and F. Jondral, “On the extraction of the channel allocation information in spectrum pooling systems,” IEEE J. Sel. Areas Commun., vol. 25, no. 3, pp. 558–565, Apr. 2007.

    Article  Google Scholar 

  85. P. Popovski, H. Yomo, K. Nishimori, R. D. Taranto, and R. Prasad, “Opportunistic interference cancellation in cognitive radio systems,” in Proc. 2nd IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN), Dublin, Ireland, Apr. 2007.

    Google Scholar 

  86. A. Sabharwal, A. Khoshnevis, and E. Knightly, “Opportunistic spectral usage: Bounds and a multi-band CSMA/CA protocol,” IEEE/ACM Trans. Netw., vol. 15, no. 3, pp. 533–545, Jun. 2007.

    Article  Google Scholar 

  87. Y. Shi and Y. T. Hou, “A distributed optimization algorithm for multi-hop cognitive radio networks,” in Proc. INFOCOM’08, Apr. 2008.

    Google Scholar 

  88. O. Simeone, Y. Bar-Ness, and U. Spagnolini, “Stable throughput of cognitive radios with and without relaying capability,” IEEE Trans. Commun., vol. 55, no. 12, pp. 2351–2360, Dec. 2007.

    Article  Google Scholar 

  89. R. Smallwood and E. Sondik, “The optimal control of partially observable Markov processes over a finite horizon,” Oper. Res., vol. 21, no. 5, pp. 1071–1088, Sept.–Oct. 1973.

    Google Scholar 

  90. J. So and N. Vaidya, “Multi-channel MAC for ad hoc networks: Handling multi-channel hidden terminals using a single transceiver,” in Proc. ACM Mobihoc’04.

    Google Scholar 

  91. S. Srinivasa, S. Jafar, and N. **dal, “On the capacity of the cognitive tracking channel,” Proc. IEEE Int. Symp. Inf. Theory, July 2006.

    Google Scholar 

  92. Y. Steinberg and N. Merhav, “Identification in the presence of side information with application to watermarking,” IEEE Trans. Inf. Theory, vol. 47, pp. 1410–1422, May 2001.

    Article  MATH  MathSciNet  Google Scholar 

  93. H. Su and X. Zhang, “Channel-hop** based single transceiver MAC for cognitive radio networks,” in Proc. CISS’08, Mar. 2008.

    Google Scholar 

  94. H. Su and X. Zhang, “Cross-layer based opportunistic MAC protocols for QoS provisionings over cognitive radio wireless networks,” IEEE J. Sel. Areas Communs., vol. 26, no. 1, pp. 118–129, Jan. 2008.

    Article  Google Scholar 

  95. J. Sun, E. Modiano, and L. Zheng, “Wireless channel allocation using an auction algorithm,” IEEE J. Sel. Areas Commun., vol. 24, no. 5, pp. 1085–1096, May 2006.

    Article  Google Scholar 

  96. R. Tandra and A. Sahai, “SNR walls for signal detection,” IEEE J. Sel. Areas Commun., vol. 2, no. 1, pp. 4–17, Feb. 2008.

    Google Scholar 

  97. A. Tkachenko, “Testbed design for cognitive radio spectrum sensing experiments,” Ph.D. dissertation, Berkeley, 2007.

    Google Scholar 

  98. J. Unnikrishnan and V. V. Veeravalli, “Cooperative sensing for primary detection in cognitive radio,” IEEE J. Sel. Signal Process., vol. 2, no. 1, pp. 18–27, Feb. 2008.

    Article  Google Scholar 

  99. S. Verdú, Multiuser Detection. Cambridge University Press, Cambridge, UK, 2003.

    Google Scholar 

  100. P. Viswanath, D. Tse, and R. Laroia, “Opportunistic beamforming using dumb antennas,” IEEE Trans. Inf. Theory, vol. 48, no. 6, pp. 1277–1294, Jun., 2002.

    Article  MATH  MathSciNet  Google Scholar 

  101. M. Vu, N. Devroye, and V. Tarokh, “On the primary exclusive regions in cognitive networks,” submitted to IEEE Trans. Wireless Comm., to appear.

    Google Scholar 

  102. M. Vu, S. S. Ghassemzadeh, and V. Tarokh, “Interference in a cognitive network with beacon,” IEEE Wireless Comm. Netw. Conf., Mar. 2008.

    Google Scholar 

  103. M. Vu and V. Tarokh, “Scaling laws of single-hop cognitive networks,” submitted to IEEE Trans. Wireless Comm., to appear.

    Google Scholar 

  104. F. Wang, M. Krunz, and S. Cui, “Price-based spectrum management in cognitive radio network,” IEEE J. Sel. Signal Process., vol. 2, no. 1, pp. 74–87, Feb. 2008.

    Article  Google Scholar 

  105. H. Weingarten, Y. Steinberg, and S. Shamai, “The capacity region of the Gaussian MIMO broadcast channel,” submitted to IEEE Trans. Inf. Theory, vol. 52, no. 9, pp. 3936–3964, Sept. 2006.

    Google Scholar 

  106. W. Weng, T. Peng, and W. Wang, “Optimal power control under interference temperature constraints in cognitive radio network,” in Proc. of IEEE Wireless Communications and Networking Conference, Hong Kong, Mar. 2007.

    Google Scholar 

  107. W. Wu, S. Vishwanath, and A. Arapostathis, “Capacity of a class of cognitive radio channels: Interference channels with degraded message sets,” IEEE Trans. Inf. Theory, vol. 53, no. 11, pp. 4391–4399, Jun. 2007.

    Article  MathSciNet  Google Scholar 

  108. W. Wu, S. Vishwanath, and A. Aripostathis, “On the capacity of interference channel with degraded message sets,” submitted to IEEE Trans. Inf. Theory, vol. 53, no. 11, pp. 4391–4399, 2007.

    Google Scholar 

  109. Y. **ng, C. Marthur, M. Haleem, R. Chandramouli, and K. Subbalakshmi, “Dynamic spectrum access with QoS and interference temperature constraints,” IEEE Trans. Mobile Comput., vol. 6, no. 4, pp. 423–433, Apr. 2007.

    Article  Google Scholar 

  110. R. Yeung, A First Course in Information Theory. Springer, New York, USA, 2002.

    Google Scholar 

  111. S. Yiu and M. Vu, “Interference reduction by beamforming in cognitive networks,” submitted to Proc. IEEE Global Telecommun. Conf., pp. 1–6, Nov. 30–Dec. 4.

    Google Scholar 

  112. L. Zhang, Y. -C. Liang, and Y. **n, “Joint beamforming and power allocation for multiple access channels in cognitive radio networks, IEEE J. Sel. Areas Commun., vol. 26, no. 1, pp. 38–51, Jan. 2008.

    Article  MATH  Google Scholar 

  113. L. Zhang, Y.-C. Liang, Y. **n, and H. V. Poor, “Robust cognitive beamforming with partial channel state information,” http://front.math.ucdavis.edu/0711.4414.

  114. L. Zhang, Y. **n, and Y.-C. Liang, “Power allocation for multi-antenna multiple access channels in cognitive radio networks,” in Annual Conference on Information Sciences and Systems (CISS), Mar. 2007.

    Google Scholar 

  115. R. Zhang and Y. Liang, “Exploiting multi-antennas for opportunistic spectrum sharing in cognitive radio networks,” http://front.math.ucdavis.edu/0711.4414.

  116. Q. Zhao and B. M. Sadler, “A survey of dynamic spectrum access,” IEEE Signal Process. Mag., vol. 24, no. 3, pp. 79–89, May, 2007.

    Article  Google Scholar 

  117. Q. Zhao, L. Tong, A. Swami, and Y. Chen, “Decentralized cognitive MAC for opportunistic spectrum access in ad hoc networks: A POMDP framework,” IEEE J. Sel. Areas Commun., vol. 25, no. 3, pp. 589–600, Apr. 2007.

    Article  Google Scholar 

Additional Readings

  1. K. R. Chowdhury and I. F. Akyildiz, “Cognitive wireless mesh networks with dynamic spectrum access,” IEEE J. Sel. Areas Communs., vol. 26, no. 1, pp. 168–181, Jan. 2008.

    Article  Google Scholar 

  2. M. Gandetto and C. Regazzoni, “Spectrum sensing: A distributed approach for cognitive terminals,” IEEE J. Sel. Areas Commun., vol. 25, no. 3, pp. 546–546, Apr. 2007.

    Google Scholar 

  3. S. Geirhofer, L. Tong, and B. M. Sadler, “Cognitive medium access: Constraining interference based on experimental models,” IEEE J. Sel. Areas Commun., vol. 26, no. 1, pp. 95–105, Jan. 2008.

    Article  Google Scholar 

  4. D. Niyato, E. Hossain, and L. Le, “Competitive spectrum sharing and pricing in cognitive wireless mesh networks,” in Proc. IEEE WCNC'08, Mar.–Apr. 2008.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ekram Hossain .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag US

About this chapter

Cite this chapter

Hossain, E., Le, L., Devroye, N., Vu, M. (2009). Cognitive Radio: From Theory to Practical Network Engineering. In: Tarokh, V. (eds) New Directions in Wireless Communications Research. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-0673-1_10

Download citation

  • DOI: https://doi.org/10.1007/978-1-4419-0673-1_10

  • Published:

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4419-0672-4

  • Online ISBN: 978-1-4419-0673-1

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Navigation