Abstract
The detection of active Primary Users (PUs) in practical wireless channels with a single Cognitive Radio (CR) sensor is challenging due to several issues such as the hidden node problem, path loss, shadowing, multipath fading, and receiver noise/interference uncertainty. In this context, Cooperative Spectrum Sensing (CSS) is considered a promising technique in order to enhance the overall sensing efficiency. Existing CSS methods mostly focus on homogeneous cooperating nodes considering identical node capabilities, equal number of antennas, equal sampling rate and identical Signal to Noise Ratio (SNR). However, in practice, nodes with different capabilities can be deployed at different stages and are very much likely to be heterogeneous in terms of the aforementioned features. In this context, we propose a novel decision statistics-based centralized CSS technique using the joint Probability Distribution Function (PDF) of the multiple decision statistics resulting from different processing capabilities at the sensor nodes and compare its performance with various existing cooperative schemes. Further, we provide a design guideline for the network operators to facilitate decision making while upgrading a sensor network.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Goldsmith, A., et al.: Breaking spectrum gridlock with cognitive radios: An information theoretic perspective. Proc. IEEE 97(5), 894–914 (2009)
Sharma, S.K., Chatzinotas, S., Ottersten, B.: Satellite cognitive communications: interference modeling and techniques selection. In: 6th ASMS and 12th SPSC, pp. 111–118, September 2012
Axell, E., et al.: Spectrum sensing for cognitive radio: State-of-the-art and recent advances. IEEE Signal Process. Magazine 29(3), 101–116 (2012)
Zeng, Y., Liang, Y.C.: Eigenvalue-based spectrum sensing algorithms for cognitive radio. IEEE Trans. Commun. 57(6), 1784–1793 (2009)
Chatzinotas, S., Sharma, S.K., Ottersten, B.: Asymptotic analysis of eigenvalue-based blind spectrum sensing techniques. In: IEEE ICASSP, pp. 4464–4468, May 2013
Akyildiz, I., Lo, B., Balakrishnan, R.: Coperative spectrum sensing in cognitive radio networks: A survey. Physical Commun. 4, 40–62 (2011)
Chen, X., Chen, H.H., Meng, W.: Cooperative communications for cognitive radio networks-from theory to applications. IEEE Comm. Surveys & Tutorials (99), 1–13 (2014)
Quan, Z., et al.: Collaborative wideband sensing for cognitive radios. IEEE Signal Process. Mag. 25(6), 60–73 (2008)
Teguig, D., et al.: Data fusion schemes for cooperative spectrum sensing in cognitive radio networks. In: Commun. and Info. Systems Conf., 2012 Military, pp. 1–7, October 2012
Liang, Y.C., et al.: Sensing-throughput tradeoff for cognitive radio networks. IEEE Trans. Wireless Commun. 7(4), 1326–1337 (2008)
Digham, F.F., Alouini, M.S., Simon, M.K.: On the energy detection of unknown signals over fading channels. IEEE Trans. Commun. 55(1), 21–24 (2007)
Sharma, S.K., Chatzinotas, S., Ottersten, B.: Exploiting polarization for spectrum sensing in cognitive SatComs. In: Porc. CROWNCOM, pp. 36–41, September 2012
Sharma, S.K., Chatzinotas, S., Ottersten, B.: Spectrum sensing in dual polarized fading channels for cognitive satcoms. In: 2012 IEEE GLOBECOM, pp. 3419–3424, December 2012
Wang, P., et al.: Multiantenna-assisted spectrum sensing for cognitive radio. IEEE Trans. Veh. Technol. 59(4), 1791–1800 (2010)
Sharma, S.K., Chatzinotas, S., Ottersten, B.: Eigenvalue based sensing and SNR estimation for cognitive radio in presence of noise correlation. IEEE Trans. Veh. Technol. 62(8), 1–14 (2013)
Sharma, S.K., Chatzinotas, S., Ottersten, B.: SNR estimation for multi-dimensional cognitive receiver under correlated channel/noise. IEEE Trans. Wireless Commun. 12(12), 6392–6405 (2013)
Sharma, S.K., Chatzinotas, S., Ottersten, B.: Maximum eigenvalue detection for spectrum sensing under correlated noise. In: Proc. IEEE ICASSP, pp. 4464–4468, May 2014
Nallagonda, S., et al.: Performance of cooperative spectrum sensing with soft data fusion schemes in fading channels. In: IEEE Annual India Conf. (INDICON), 2013 Annual IEEE, pp. 1–6, December 2013
Tandra, R., Sahai, A.: SNR walls for signal detection. IEEE J. Sel. Topics Signal Porcess. 2(1), 4–17 (2008)
Gatignon, H.: Statistical Analysis of Management Data, chap. 2. Springer (2010)
Kay, S., Ding, Q., Emge, D.: Joint pdf construction for sensor fusion and distributed detection. In: 13th Conf. Info. Fusion (FUSION), pp. 1–6, July 2010
Shakir, M.Z., Rao, A., Alouini, M.S.: On the decision threshold of eigenvalue ratio detector based on moments of joint and marginal distributions of extreme eigenvalues. IEEE Trans. Wireless Commun. 12(3), 974–983 (2013)
Wickens, T.D.: Elementary Signal Detection Theory, chap. 10. Oxford University Press (2001)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Institute for Computer Science, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Sharma, S.K., Chatzinotas, S., Ottersten, B. (2015). Cooperative Spectrum Sensing for Heterogeneous Sensor Networks Using Multiple Decision Statistics. In: Weichold, M., Hamdi, M., Shakir, M., Abdallah, M., Karagiannidis, G., Ismail, M. (eds) Cognitive Radio Oriented Wireless Networks. CrownCom 2015. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 156. Springer, Cham. https://doi.org/10.1007/978-3-319-24540-9_26
Download citation
DOI: https://doi.org/10.1007/978-3-319-24540-9_26
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-24539-3
Online ISBN: 978-3-319-24540-9
eBook Packages: Computer ScienceComputer Science (R0)