Collaborative Spectrum Sensing Based on a New SNR Estimation and Energy Combining Method

In order for collaborative spectrum sensing to be effective, the sensing data provided by each radio should be weighted in proportion to their reliability during data combining. The time and processing requirements of the weight estimation process, however, can make weighted data combining infeasible in practical systems. This paper presents a new collaborative sensing method that exploits the correlation of the sensing data provided by a given radio in successive sensing intervals to keep the requirements of weighted data combining at acceptable levels. It is shown that the proposed method offers an excellent tradeoff between reliability and complexity, compared with conventional collaborative sensing methods.

[1]  John G. Proakis,et al.  Probability, random variables and stochastic processes , 1985, IEEE Trans. Acoust. Speech Signal Process..

[2]  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.

[3]  A. M. Mathai.  Quadratic forms in random variables , 1992 .

[4]  Amir Ghasemi,et al.  Opportunistic Spectrum Access in Fading Channels Through Collaborative Sensing , 2007, J. Commun..

[5]  Shuguang Cui,et al.  Optimal Linear Cooperation for Spectrum Sensing in Cognitive Radio Networks , 2008, IEEE Journal of Selected Topics in Signal Processing.

[6]  Bruno O. Shubert,et al.  Random variables and stochastic processes , 1979 .

[7]  Carl W. Helstrom,et al.  Computing the distribution of sums of random sine waves and of Rayleigh-distributed random variables by saddle-point integration , 1997, IEEE Trans. Commun..

[8]  G. McLachlan,et al.  The EM Algorithm and Extensions: Second Edition , 2008 .

[9]  Yonghong Zeng,et al.  Sensing-Throughput Tradeoff for Cognitive Radio Networks , 2008, IEEE Trans. Wirel. Commun..

[10]  Przemyslaw Pawelczak,et al.  Multinode Spectrum Sensing Based on Energy Detection for Dynamic Spectrum Access , 2008, VTC Spring 2008 - IEEE Vehicular Technology Conference.

[11]  Masoumeh Nasiri-Kenari,et al.  Asymptotically optimum detection of primary user in cognitive radio networks , 2007, IET Commun..

[12]  Xiaojing Huang,et al.  The simulation of independent Rayleigh faders , 2002, IEEE Trans. Commun..

[13]  Marco Lops,et al.  Multiuser Detection in a Dynamic Environment– Part I: User Identification and Data Detection , 2007, IEEE Transactions on Information Theory.

[14]  Joarder Kamruzzaman,et al.  Weighted soft decision for cooperative sensing in cognitive radio networks , 2008, 2008 16th IEEE International Conference on Networks.

[15]  Yonghong Zeng,et al.  Optimization of Cooperative Sensing in Cognitive Radio Networks: A Sensing-Throughput Tradeoff View , 2009, IEEE Transactions on Vehicular Technology.

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

[17]  Claudio R. C. M. da Silva,et al.  Maximum-Likelihood Classification of Digital Amplitude-Phase Modulated Signals in Flat Fading Non-Gaussian Channels , 2011, IEEE Transactions on Communications.

[18]  Zhongding Lei,et al.  IEEE 802.22: The first cognitive radio wireless regional area network standard , 2009, IEEE Communications Magazine.

[19]  G. McLachlan,et al.  The EM algorithm and extensions , 1996 .

[20]  Yunfei Chen,et al.  Analytical Performance of Collaborative Spectrum Sensing Using Censored Energy Detection , 2010, IEEE Transactions on Wireless Communications.

[21]  Brian L. Mark,et al.  Joint Spatial–Temporal Spectrum Sensing for Cognitive Radio Networks , 2009, IEEE Transactions on Vehicular Technology.

[22]  Giuseppe Caire,et al.  Computing error probabilities over fading channels: A unified approach , 1998, Eur. Trans. Telecommun..

[23]  Geoffrey Ye Li,et al.  MIMO-OFDM for wireless communications: signal detection with enhanced channel estimation , 2002, IEEE Trans. Commun..

[24]  A. Stewart Fotheringham,et al.  Goodness-of-fit statistics , 1987 .

[25]  Xiao-Li Meng,et al.  Maximum likelihood estimation via the ECM algorithm: A general framework , 1993 .

[26]  Norman C. Beaulieu,et al.  A comparison of SNR estimation techniques for the AWGN channel , 2000, IEEE Trans. Commun..

[27]  Wha Sook Jeon,et al.  Collaborative Spectrum Sensing for Multiuser Cognitive Radio Systems , 2009, IEEE Transactions on Vehicular Technology.

[28]  Steven Kay,et al.  Fundamentals Of Statistical Signal Processing , 2001 .

[29]  Halim Yanikomeroglu,et al.  On the Feasibility of Wireless Shadowing Correlation Models , 2010, IEEE Transactions on Vehicular Technology.

[30]  Tracy Camp,et al.  A survey of mobility models for ad hoc network research , 2002, Wirel. Commun. Mob. Comput..