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Performance analysis of Doppler shift effects on OFDM-based and MC-CDMA-based cognitive radios

Authors:

Salem Bindhaiq,

Sharifah Kamilah Syed-Yusof,

Haleh HosseiniAuthors Info & Claims

International Journal of Communication Systems, Volume 27, Issue 11

Pages 2658 - 2669

https://doi.org/10.1002/dac.2497

Published: 01 November 2014 Publication History

Abstract

The present development of high data rate wireless applications has led to extra bandwidth demands. However, finding a new spectrum bandwidth to accommodate these applications and services is a challenging task because of the scarcity of spectrum resources. In fact, the spectrum is utilized inefficiently for conventional spectrum allocation, so Federal Communications Commission has proposed dynamic spectrum access mechanism in cognitive radio, where unlicensed users can opportunistically borrow unused licensed spectrum, which is a challenge to obtain contiguous frequency spectrum block. This also has a significant impact on multicarrier transmission systems such as orthogonal frequency division multiplexing OFDM and multicarrier code division multiple access MC-CDMA. As a solution, this paper develops non-contiguous OFDM NC-OFDM and non-contiguous MC-CDMA NC-MC-CDMA cognitive system. The implementation of NC-OFDM and NC-MC-CDMA systems provides high data rate via a large number of non-contiguous subcarriers without interfering with the existing transmissions. The system performance evaluates NC-OFDM and NC-MC-CDMA for mobile scenario where each propagation path will experience Doppler frequency shift because of the relative motion between the transmitter and receiver. The simulation results of this paper proved that NC-OFDM system is a superior candidate than NC-MC-CDMA system considering the mobility for cognitive users. Copyright © 2013 John Wiley & Sons, Ltd.

References

[1]

Spectrum Efficiency Working Group. Report of the Spectrum Efficiency Working Group, Federal Communications Commission Spectrum Policy Task Force. Tech. Rep., Nov 2000.

[2]

Marcus MJ. Unlicensed cognitive sharing of TV spectrum: the controversy at the Federal Communications Commission. IEEE Communication Magazine 2005; Volume 5: pp.24-25.

[3]

Federal Communications Commission. Unlicensed operation in the TV broadcast bands, ET Docket; No. 04-186, 2004.

[4]

Mitola JIII. Cognitive radio for flexible mobile multimedia communications, in Proc. IEEE International workshop on Mobile Multimedia communications; San Diego, CA, USA, Nov. 1999; Volume 1: pp.3-10.

[5]

Dhar Roy S, Kundu S, Ferrari G, Raheli R. Cognitive radio CDMA networking with spectrum sensing. International Journal of Communication Systems 2012. 2421.

[6]

Poston JD, Horne WD. Discontiguous OFDM considerations for dynamic spectrum access in idle TV channels. IEEE International Symposium on New Frontiers Dynamic Spectrum Access Networks; Baltimore, MD, USA, Nov. 2005; Volume 1: pp.607-610.

[7]

Wylie-Green MP. Dynamic spectrum sensing by multiband OFDM radio for interference mitigation. IEEE International Symposium on New Frontiers Dynamic Spectrum Access Networks, Baltimore, MD, USA, Nov. 2005; Volume 1: pp.619-625.

[8]

Weiss TA, Jondral FK. Spectrum pooling: an innovative strategy for the enhancement of spectrum efficiency. IEEE Communication Magazine 2004; Volume 43: pp.S8-14.

[9]

Arslan H, Sahin ME. UWB Cognitive Radio, Cognitive Radio, Software Defined Radio, and Adaptive Wireless Systems. Springer, 2007.

[10]

El-Saleh AA, Ismail M, Ali MDAM, Alnuaimy ANH. Capacity optimization for local and cooperative spectrum sensing in cognitive radio networks, World Academy of Science, Engineering and Technology, 2009; Volume 50.

[11]

Haykin S. Cognitive radio: brain-empowered wireless communications. IEEE Journal on Selected Areas in Communications 2005; Volume 23 Issue 2: pp.201-220.

[12]

Demestichas P, Katidiotis A, Tsagkaris KA, Adamopoulou EF, Demestichas KP. Enhancing Channel Estimation in Cognitive Radio Systems by Means of Bayesian Networks. Springer: Netherlands, 2008.

[13]

Lu D, Huang X, Zhang W, Fan J. Interference-aware spectrum handover for cognitive radio networks, International Journal of Communication Systems 2012.

[14]

Gilhousen KS, Jacbs IM, Padovani R, Viterbi AJ, <author>Weaver Jr., LA</author>, Wheatley CE. On the capacity of a cellular CDMA system. IEEE Transaction on Vehicle Technology 1991; Volume 40: pp.303-312.

[15]

Menon R, Buehrer RM, Reed JH, Outage probability based comparison of underlay and overlay spectrum sharing techniques. IEEE International Symposium on New Frontiers Dynamic Spectrum Access Network, Baltimore. MD, USA; 2005; Volume 1: pp.101-109.

[16]

Berthold U, Jondral FK. Guidelines for designing OFDM overlay system. IEEE International Symposium on New Frontiers Dynamic Spectrum Access Network, Baltimore. MD; 2005; Volume 1: pp.626-629.

[17]

Agarwal DP, Zeng Q-A. Introduction to Wireless and Mobile Systems. Nelson, India: Thomson Learning, 2007.

[18]

Fazel K, Kaiser S. Multi-Carrier and Spread Spectrum Systems. John Wiley & Sons, 2003.

Digital Library

[19]

Bingham JAC. Multicarrier modulation for data transmission: an idea whose time has come. IEEE Communication Magazine 1990; Volume 28: pp.5-14.

[20]

Saltzberg BR. Comparison of single-carrier and multitone digital modulation for ADSL applications. IEEE Communication Magazine 1998; Volume 36: pp.114-121.

[21]

Hanzo L, Munster M, Choi BJ, Keller T. OFDM and MC-CDMA for broadband multi-user communications. WLANs and Broadcasting. IEEE Press, 2003.

Digital Library

[22]

Choi B-J, Kuan E-L, Hanzo L. Crest-factor study of MC-CDMA and OFDM. 50th IEEE Vehicle Technology Conference 1999; Volume 1: pp.233-237.

Cited By

Khan MJamali M(2018)QoS optimization‐based dynamic secondary spectrum access modelTransactions on Emerging Telecommunications Technologies10.1002/ett.345529:8Online publication date: 6-Aug-2018
https://dl.acm.org/doi/10.1002/ett.3455
Zhang HRuyet DRoviras DSun H(2016)Polyphase filter bank based multi-band spectrum sensing in cognitive radio systemsInternational Journal of Communication Systems10.1002/dac.279829:12(1844-1862)Online publication date: 1-Aug-2016
https://dl.acm.org/doi/10.1002/dac.2798

Index Terms

Performance analysis of Doppler shift effects on OFDM-based and MC-CDMA-based cognitive radios
1. Networks
  1. Network types
    1. Mobile networks

Index terms have been assigned to the content through auto-classification.

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Published In

cover image International Journal of Communication Systems

International Journal of Communication Systems Volume 27, Issue 11

November 2014

1060 pages

ISSN:1074-5351

EISSN:1099-1131

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John Wiley and Sons Ltd.

United Kingdom

Publication History

Published: 01 November 2014

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Cited By

Khan MJamali M(2018)QoS optimization‐based dynamic secondary spectrum access modelTransactions on Emerging Telecommunications Technologies10.1002/ett.345529:8Online publication date: 6-Aug-2018
https://dl.acm.org/doi/10.1002/ett.3455
Zhang HRuyet DRoviras DSun H(2016)Polyphase filter bank based multi-band spectrum sensing in cognitive radio systemsInternational Journal of Communication Systems10.1002/dac.279829:12(1844-1862)Online publication date: 1-Aug-2016
https://dl.acm.org/doi/10.1002/dac.2798

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