Sensing-throughput tradeoff for OFDM-based cognitive radio under outage constraints

Sensing-throughput tradeoff under outage constraints has been studied before with an energy detector (ED). However, the ED does not work well in the presence of noise power uncertainty. So we study sensing-throughput tradeoff by using an autocorrelation detector (AD) for an OFDM signal. In this paper, we derive a closed form expression for the false alarm probability over both Nakagami-m and Rician fading channels. This false alarm probability relies upon a new threshold which takes into account an outage constraint on the probability of detection due to fading environments. The results show that the throughput improves with an increase in the Nakagami-m fading parameter and the Rician factor. In addition, the throughput improves dramatically with an initial increase of the number of multipath and then levels out.

[1]  Ha H. Nguyen,et al.  Blind Spectrum Sensing for OFDM-Based Cognitive Radio Systems , 2011, IEEE Transactions on Vehicular Technology.

[2]  Mounir Ghogho,et al.  Spectrum Sensing and Throughput Trade-off in Cognitive Radio under Outage Constraints over Nakagami Fading , 2011, IEEE Communications Letters.

[3]  Chandra R. Murthy,et al.  Performance comparison of energy, matched-filter and cyclostationarity-based spectrum sensing , 2010, 2010 IEEE 11th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC).

[4]  Y. Zeng,et al.  Reliability of Spectrum Sensing Under Noise and Interference Uncertainty , 2009, 2009 IEEE International Conference on Communications Workshops.

[5]  Hüseyin Arslan,et al.  A survey of spectrum sensing algorithms for cognitive radio applications , 2009, IEEE Communications Surveys & Tutorials.

[6]  H. Vincent Poor,et al.  Autocorrelation-Based Decentralized Sequential Detection of OFDM Signals in Cognitive Radios , 2009, IEEE Transactions on Signal Processing.

[7]  Simon Haykin,et al.  Cognitive radio: brain-empowered wireless communications , 2005, IEEE Journal on Selected Areas in Communications.

[8]  Mounir Ghogho,et al.  Spectrum sensing and data transmission trade-off in cognitive radio under outage constraints , 2011 .

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

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

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

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

[13]  Erik G. Larsson,et al.  Linköping University Post Print Optimal and Sub-optimal Spectrum Sensing of Ofdm Signals in Known and Unknown Noise Variance Optimal and Sub-optimal Spectrum Sensing of Ofdm Signals in Known and Unknown Noise Variance , 2022 .