Study on soft combination for spectrum sensing in cognitive vehicular ad hoc networks

The increasing demand of vehicular network oriented applications (both safety and non-safety related services) would undoubtedly lead to shortage of spectral resource which is a challenge for vehicle-to-vehicle (V2V) communication networks. As a promising solution to meet the increasing demand of spectrum resource, cognitive radio (CR) technology has attracted much attention. Compared with general communication environment, vehicle environment has its own features such as movement of second users (SU) that can be negative to the performance of spectrum sensing. In this paper, we introduce a cooperative spectrum sensing (CSS) scheme in vehicle environment where we reduce the spatial correlation between samples and improve detection probability in region with low signal-to-noise (SNR) and a soft combination rule is proposed where different ways are used to aggregate samples. Simulation results show that our scheme can significantly increase the detection probability in low SNR region with a slight loss in region with high SNR.

[1]  Luciano Bononi,et al.  Cooperative spectrum management in cognitive Vehicular Ad Hoc Networks , 2011, 2011 IEEE Vehicular Networking Conference (VNC).

[2]  Anant Sahai,et al.  Cooperative Sensing among Cognitive Radios , 2006, 2006 IEEE International Conference on Communications.

[3]  Hassan Artail,et al.  Data delivery guarantees in congested Vehicular ad hoc networks using cognitive networks , 2011, 2011 7th International Wireless Communications and Mobile Computing Conference.

[4]  R.W. Brodersen,et al.  Implementation issues in spectrum sensing for cognitive radios , 2004, Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, 2004..

[5]  Geoffrey Ye Li,et al.  Soft Combination and Detection for Cooperative Spectrum Sensing in Cognitive Radio Networks , 2008, IEEE GLOBECOM 2007 - IEEE Global Telecommunications Conference.

[6]  Chunyan Feng,et al.  User correlation and double threshold based cooperative spectrum sensing in dense cognitive vehicular networks , 2016, 2016 International Symposium on Wireless Communication Systems (ISWCS).

[7]  A. Ghasemi,et al.  Collaborative spectrum sensing for opportunistic access in fading environments , 2005, First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005..

[8]  Luciano Bononi,et al.  Analyzing the potential of cooperative Cognitive Radio technology on inter-vehicle communication , 2010, 2010 IFIP Wireless Days.

[9]  Luciano Bononi,et al.  Integrating Spectrum Database and Cooperative Sensing for Cognitive Vehicular Networks , 2013, 2013 IEEE 78th Vehicular Technology Conference (VTC Fall).

[10]  Alexander M. Wyglinski,et al.  Characterization of vacant UHF TV channels for vehicular dynamic spectrum access , 2009, 2009 IEEE Vehicular Networking Conference (VNC).

[11]  Kang G. Shin,et al.  Impact of mobility on spectrum sensing in cognitive radio networks , 2009, CoRoNet '09.

[12]  Ian F. Akyildiz,et al.  Cooperative spectrum sensing in cognitive radio networks: A survey , 2011, Phys. Commun..

[13]  Jean-Marie Bonnin,et al.  Cognitive radio for vehicular ad hoc networks (CR-VANETs): approaches and challenges , 2014, EURASIP J. Wirel. Commun. Netw..