Skip to main content
Top
Published in:
Cover of the book

2019 | OriginalPaper | Chapter

1. Introduction

Authors : Yue Gao, Zhijin Qin

Published in: Data-Driven Wireless Networks

Publisher: Springer International Publishing

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Radio frequency (RF) spectrum is a valuable but tightly regulated resource due to its unique and important role in wireless communications. The demand for RF spectrum is increasing due to a rapidly expanding market of multimedia wireless services, while the usable spectrum is becoming scarce due to current rigid spectrum allocation policies.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Literature
go back to reference Akyildiz, I. F., Lee, W.-Y., Vuran, M. C., & Mohanty, S. (2006). Next generation/dynamic spectrum access/cognitive radio wireless networks: A survey. Computer Network, 50, 2127–2159.CrossRef Akyildiz, I. F., Lee, W.-Y., Vuran, M. C., & Mohanty, S. (2006). Next generation/dynamic spectrum access/cognitive radio wireless networks: A survey. Computer Network, 50, 2127–2159.CrossRef
go back to reference Akyildiz, I. F., Lo, B. F., & Balakrishnan, R. (2011). Cooperative spectrum sensing in cognitive radio networks: A survey. Physical Communication, 4, 40–62.CrossRef Akyildiz, I. F., Lo, B. F., & Balakrishnan, R. (2011). Cooperative spectrum sensing in cognitive radio networks: A survey. Physical Communication, 4, 40–62.CrossRef
go back to reference Candes, E. (2006). Compressive sampling. In Proceedings of the International Congress of Mathematicians, Madrid, Spain (vol. 3, pp. 1433–1452) Candes, E. (2006). Compressive sampling. In Proceedings of the International Congress of Mathematicians, Madrid, Spain (vol. 3, pp. 1433–1452)
go back to reference Farhang-Boroujeny, B. (2008). Filter bank spectrum sensing for cognitive radios. IEEE Transactions on Signal Processing, 56, 1801–1811.MathSciNetCrossRef Farhang-Boroujeny, B. (2008). Filter bank spectrum sensing for cognitive radios. IEEE Transactions on Signal Processing, 56, 1801–1811.MathSciNetCrossRef
go back to reference Federal Communications Commission (FCC). (2008). Second report and order and memorandum opinion and order in matter of unlicensed operation in the TV broadcast bands, additional spectrum for unlicensed devices below 900 MHz and in the 3 GHz band, Document 08-260. Federal Communications Commission (FCC). (2008). Second report and order and memorandum opinion and order in matter of unlicensed operation in the TV broadcast bands, additional spectrum for unlicensed devices below 900 MHz and in the 3 GHz band, Document 08-260.
go back to reference Gao, Y., Qin, Z., Feng, Z., Zhang, Q., Holland, O., & Dohler, M. (2016). Scalable and reliable IoT enabled by dynamic spectrum management for M2M in LTE-A. IEEE Internet of Things Journal, 3, 1135–1145.CrossRef Gao, Y., Qin, Z., Feng, Z., Zhang, Q., Holland, O., & Dohler, M. (2016). Scalable and reliable IoT enabled by dynamic spectrum management for M2M in LTE-A. IEEE Internet of Things Journal, 3, 1135–1145.CrossRef
go back to reference Ghasemi, A., & Sousa, E. (2005). Collaborative spectrum sensing for opportunistic access in fading environments. In Proceedings of the IEEE International Symposium on Dynamic Spectrum Access Networks (DYSPAN), Baltimore, MD (pp. 131–136) Ghasemi, A., & Sousa, E. (2005). Collaborative spectrum sensing for opportunistic access in fading environments. In Proceedings of the IEEE International Symposium on Dynamic Spectrum Access Networks (DYSPAN), Baltimore, MD (pp. 131–136)
go back to reference Kolodzy, P., & Avoidance, I. (2002). Spectrum policy task force. Federal Communications Commission, Washington, DC, Rep. ET Docket. Kolodzy, P., & Avoidance, I. (2002). Spectrum policy task force. Federal Communications Commission, Washington, DC, Rep. ET Docket.
go back to reference Landau, H. (1967). Necessary density conditions for sampling and interpolation of certain entire functions. Acta Mathematica, 117, 37–52.MathSciNetCrossRef Landau, H. (1967). Necessary density conditions for sampling and interpolation of certain entire functions. Acta Mathematica, 117, 37–52.MathSciNetCrossRef
go back to reference Mitola, J., & Maguire, G. Q. (1999). Cognitive radio: Making software radios more personal. IEEE Personal Communications, 6, 13–18.CrossRef Mitola, J., & Maguire, G. Q. (1999). Cognitive radio: Making software radios more personal. IEEE Personal Communications, 6, 13–18.CrossRef
go back to reference Qin, Z., Gao, Y., & Parini, C. G. (2016a). Data-assisted low complexity compressive spectrum sensing on real-time signals under sub-Nyquist rate. IEEE Transactions on Wireless Communications, 15, 1174–1185.CrossRef Qin, Z., Gao, Y., & Parini, C. G. (2016a). Data-assisted low complexity compressive spectrum sensing on real-time signals under sub-Nyquist rate. IEEE Transactions on Wireless Communications, 15, 1174–1185.CrossRef
go back to reference Qin, Z., Gao, Y., Plumbley, M., & Parini, C. (2014). Efficient compressive spectrum sensing algorithm for M2M devices. In IEEE Global Conference on Signal and Information Processing (GlobalSIP), Atlanta, GA (pp. 1170–1174). Qin, Z., Gao, Y., Plumbley, M., & Parini, C. (2014). Efficient compressive spectrum sensing algorithm for M2M devices. In IEEE Global Conference on Signal and Information Processing (GlobalSIP), Atlanta, GA (pp. 1170–1174).
go back to reference Qin, Z., Gao, Y., & Plumbley, M. D. (2018). Malicious user detection based on low-rank matrix completion in wideband spectrum sensing. IEEE Transactions on Signal Processing, 66, 5–17.MathSciNetCrossRef Qin, Z., Gao, Y., & Plumbley, M. D. (2018). Malicious user detection based on low-rank matrix completion in wideband spectrum sensing. IEEE Transactions on Signal Processing, 66, 5–17.MathSciNetCrossRef
go back to reference Qin, Z., Gao, Y., Plumbley, M. D., & Parini, C. G. (2016b). Wideband spectrum sensing on real-time signals at sub-Nyquist sampling rates in single and cooperative multiple nodes. IEEE Transactions on Signal Processing, 64, 3106–3117.MathSciNetCrossRef Qin, Z., Gao, Y., Plumbley, M. D., & Parini, C. G. (2016b). Wideband spectrum sensing on real-time signals at sub-Nyquist sampling rates in single and cooperative multiple nodes. IEEE Transactions on Signal Processing, 64, 3106–3117.MathSciNetCrossRef
go back to reference Qin, Z., Liu, Y., Gao, Y., Elkashlan, M., & Nallanathan, A. (2017). Wireless powered cognitive radio networks with compressive sensing and matrix completion. IEEE Transactions on Communications, 65, 1464–1476.CrossRef Qin, Z., Liu, Y., Gao, Y., Elkashlan, M., & Nallanathan, A. (2017). Wireless powered cognitive radio networks with compressive sensing and matrix completion. IEEE Transactions on Communications, 65, 1464–1476.CrossRef
go back to reference Qin, Z., Wei, L., Gao, Y., & Parini, C. (2015). Compressive spectrum sensing augmented by geo-location database. In Proceedings of the International Workshop on Smart Spectrum at IEEE Wireless Communications and Networking Conference (WCNC), New Orleans, LA (pp. 170–175). Qin, Z., Wei, L., Gao, Y., & Parini, C. (2015). Compressive spectrum sensing augmented by geo-location database. In Proceedings of the International Workshop on Smart Spectrum at IEEE Wireless Communications and Networking Conference (WCNC), New Orleans, LA (pp. 170–175).
go back to reference Quan, Z., Cui, S., Sayed, A. H., & Poor, H. V. (2009). Optimal multiband joint detection for spectrum sensing in cognitive radio networks. IEEE Transactions on Signal Processing, 57, 1128–1140.MathSciNetCrossRef Quan, Z., Cui, S., Sayed, A. H., & Poor, H. V. (2009). Optimal multiband joint detection for spectrum sensing in cognitive radio networks. IEEE Transactions on Signal Processing, 57, 1128–1140.MathSciNetCrossRef
go back to reference Sun, H., Laurenson, D. I., & Wang, C. X. (2010). Computationally tractable model of energy detection performance over slow fading channels. IEEE Communications Letters, 14, 924–926.CrossRef Sun, H., Laurenson, D. I., & Wang, C. X. (2010). Computationally tractable model of energy detection performance over slow fading channels. IEEE Communications Letters, 14, 924–926.CrossRef
go back to reference Sun, H., Nallanathan, A., Wang, C.-X., & Chen, Y. (2013). Wideband spectrum sensing for cognitive radio networks: A survey. IEEE Wireless Communications, 20, 74–81. Sun, H., Nallanathan, A., Wang, C.-X., & Chen, Y. (2013). Wideband spectrum sensing for cognitive radio networks: A survey. IEEE Wireless Communications, 20, 74–81.
go back to reference Tian, Z., & Giannakis, G. (2007). Compressed sensing for wideband cognitive radios. In IEEE International Conference on Acoustics, Speech, and Signal Processing, Honolulu, HI (ICASSP) (pp. 1357–1360). Tian, Z., & Giannakis, G. (2007). Compressed sensing for wideband cognitive radios. In IEEE International Conference on Acoustics, Speech, and Signal Processing, Honolulu, HI (ICASSP) (pp. 1357–1360).
go back to reference Treichler, J., Davenport, M., & Baraniuk, R. (2009). Application of compressive sensing to the design of wideband signal acquisition receivers. In US/Australia Joint Work. Defense Apps of Signal Processing (DASP) (vol. 5). Treichler, J., Davenport, M., & Baraniuk, R. (2009). Application of compressive sensing to the design of wideband signal acquisition receivers. In US/Australia Joint Work. Defense Apps of Signal Processing (DASP) (vol. 5).
go back to reference UK Office of Communications (Ofcom). (2009). Statement on cognitive access to interleaved spectrum. UK Office of Communications (Ofcom). (2009). Statement on cognitive access to interleaved spectrum.
go back to reference UK Office of Communications (Ofcom). (2015). Decision to make the wireless telegraphy (White Space Devices). UK Office of Communications (Ofcom). (2015). Decision to make the wireless telegraphy (White Space Devices).
go back to reference Wang, Y., Tian, Z., & Feng, C. (2012). Collecting detection diversity and complexity gains in cooperative spectrum sensing. IEEE Wireless Communications, 11, 2876–2883. Wang, Y., Tian, Z., & Feng, C. (2012). Collecting detection diversity and complexity gains in cooperative spectrum sensing. IEEE Wireless Communications, 11, 2876–2883.
go back to reference Zhang, X., Ma, Y., Gao, Y., & Zhang, W. (2018). Autonomous compressive sensing augmented spectrum sensing. IEEE Transactions on Vehicular Technology, 67, 6970–6980.CrossRef Zhang, X., Ma, Y., Gao, Y., & Zhang, W. (2018). Autonomous compressive sensing augmented spectrum sensing. IEEE Transactions on Vehicular Technology, 67, 6970–6980.CrossRef
go back to reference Zhang, X., Qin, Z., & Gao, Y. (2014). Dynamic adjustment of sparsity upper bound in wideband compressive spectrum sensing. In Proceedings of the IEEE Global Conference on Signal and Information Processing (GlobalSIP), Atlanta, GA (pp. 1214–1218). Zhang, X., Qin, Z., & Gao, Y. (2014). Dynamic adjustment of sparsity upper bound in wideband compressive spectrum sensing. In Proceedings of the IEEE Global Conference on Signal and Information Processing (GlobalSIP), Atlanta, GA (pp. 1214–1218).
Metadata
Title
Introduction
Authors
Yue Gao
Zhijin Qin
Copyright Year
2019
DOI
https://doi.org/10.1007/978-3-030-00290-9_1