Spectrum Sensing of OFDM Waveforms Using Embedded Pilot Subcarriers

Reliable spectrum sensing is the key requirement for secondary users to utilize the spectrum in the absence of primary users. Given the widespread deployment of OFDM modulation in recent and future multimedia broadcasting and wireless broad-band services, reliable spectrum sensing of OFDM waveforms is of great interest for future cognitive radio systems. This paper presents a new detection method for OFDM waveforms that exploits the available embedded pilot tones without any simplifying assumption or constraints on the pilots. Analytical performance characterization is presented and supported by simulation results for both AWGN and fading channels. This study shows that the new method can improve the performance by 5dB in comparison with other feature detectors.

[1]  Kwang-Cheng Chen,et al.  Spectrum Sensing of OFDMA Systems for Cognitive Radios , 2007, 2007 IEEE 18th International Symposium on Personal, Indoor and Mobile Radio Communications.

[2]  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..

[3]  Visa Koivunen,et al.  Nonparametric Cyclic Correlation Based Detection for Cognitive Radio Systems , 2008, 2008 3rd International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CrownCom 2008).

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

[5]  David G. Daut,et al.  Spectrum Sensing for OFDM Systems Employing Pilot Tones and Application to DVB-T OFDM , 2008, 2008 IEEE International Conference on Communications.

[6]  Ning Han,et al.  Enhanced Energy Detector for IEEE 802.22 WRAN Systems Using Maximal-to-Mean Power Ratio , 2007, 2007 4th International Symposium on Wireless Communication Systems.

[7]  Anant Sahai,et al.  SNR Walls for Signal Detection , 2008, IEEE Journal of Selected Topics in Signal Processing.

[8]  Young Min Kim,et al.  An Alternative Energy Detection Using Sliding Window for Cognitive Radio System , 2008, 2008 10th International Conference on Advanced Communication Technology.

[9]  Ning Han,et al.  OFDM Signal Sensing Method Based on Cyclostationary Detection , 2007, 2007 2nd International Conference on Cognitive Radio Oriented Wireless Networks and Communications.

[10]  William A. Gardner,et al.  Signal interception: a unifying theoretical framework for feature detection , 1988, IEEE Trans. Commun..

[11]  Shuguang Cui,et al.  Collaborative wideband sensing for cognitive radios , 2008, IEEE Signal Processing Magazine.

[12]  W. A. Brown,et al.  Computationally efficient algorithms for cyclic spectral analysis , 1991, IEEE Signal Processing Magazine.

[13]  Friedrich K. Jondral,et al.  Air interface identification for software radio systems , 2007 .

[14]  S. Kay.  Fundamentals of statistical signal processing: estimation theory , 1993 .

[15]  R.W. Brodersen,et al.  Cyclostationary Feature Detector Experiments Using Reconfigurable BEE2 , 2007, 2007 2nd IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks.

[16]  Hang Liu,et al.  A New Approach to Improve Signal Classification in Low SNR Environment in Spectrum Sensing , 2008, 2008 3rd International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CrownCom 2008).

[17]  Joseph Mitola,et al.  Cognitive radio: making software radios more personal , 1999, IEEE Wirel. Commun..