隨著行動與無線通訊技術與日俱進的快速發展，應用於不同範圍的無線通訊標準
也如雨後春筍萌生。然而隨著數位電視的崛起，類比電視大部份的頻帶使用率並
不高。
綠能科技的提出，使得感知無線電成為下一世代有效增進頻譜效能的通訊技術。
頻譜偵測為感知無線電的其中一個重要議題，感知使用者偵測主要使用者是否有
傳輸資料後，擷取並用來傳輸資料。藉由感知無線電和合作式通信兩種技術來達
成高可靠、高品質及高效率之通訊服務，來克服傳輸通道衰落並提升機會傳輸量；
兩者的結合將會對未來的無線行動通信系統帶來重大影響。目前的文獻大多利用
能量檢測器當作頻譜偵測的方法，但在低訊雜比時，辨識率並不高。因此本研究
基於高階統計量為基礎設計一套檢測器，可有效消除高斯白雜訊在低訊雜比的影
響；此外，高階統計量所需的複雜度較高，因此我們利用序列式檢測法降低偵測
時間。為了抵抗遮蔽效應，我們利用合作式通訊增加偵測可靠度。本演算法的優點不僅能應用於大多通訊系統，也能有效抵抗雜訊及衰落通道。

In cognitive radio, spectrum sensing is a key enabling functionality to identify the
vacant spectrum which is not occupied by primary systems. With good sensing capability,
secondary users can effectively recycling the spectrum resource without
disturbing active primary users. Energy detectors are commonly used and relatively
simple spectrum sensing techniques. However, for low signal-to-noise ratio
(SNR) regimes, the performance of energy detectors degrades dramatically as the
signal and noise could be mixed together after the operation of energy calculation.
In addition, the outputs of the energy detectors are often assumed as Gaussian
distribution, which is not necessarily guaranteed in realistic cases. In this paper,
a high-order statistics (HOS) based sequential test detector is investigated for
sensing spectrum, particularly for low-SNR applications. We resort to high-order
statistics, in terms of cumulant statistics, for overwhelming the Gaussian noise effect
and improving the spectrum sensing reliability. Based on these cumulants, a
binary hypothesis testing problem is formulated and a low-complexity sequential
probability ratio test (SPRT) is developed for efficiently detecting underutilized
spectrum. Our numerical results show that the proposed detector outperforms
more than 10dB detection probability than the conventional energy detectors.

[1] (2007, April 16-18)Spectrum Occupancy Measurements: Dublin,
Ireland[Online]. Available: http://www.sharedspectrum.com/wpcontent/
uploads/Ireland Spectrum Occupancy Measurements v2.pdf
.
[2] J. III. Mitola, ”Cognitive radio for flexible mobile multimedia communications,”
International Workshop on Mobile Multimedia Communications,
IEEE, pp.3-10, 1999.
[3] (2009, December)Standard ECMA-392[Online]. Available:
http://www.ecma-international.org/publications/standards/Ecma-392.htm.
[4] C. Stevenson, G. Chouinard, Z. D. Lei, W. D. Hu, S. Shellhammer, and W.
Caldwell, ”IEEE 802.22: The first cognitive radio wireless regional area network
standard,” IEEE Commun. Mag., vol.47, no.1, pp.130-138, Jan. 2009.
[5] S. J. Shellhammer, ”Spectrum sensing in IEEE 802.22,” Proc. CIP,
EURASIP, pp. 1 2008.
[6] W. Y. Lee, and I. F. Akyldiz, ”A Spectrum Decision Framework for Cognitive
Radio Networks,” IEEE Trans.Mobile Computing ,vol.10, no.2, pp.161-
174, Feb. 2011.
[7] S. Haykin, ”Cognitive radio: brain-empowered wireless communications,”
IEEE J. Sel. Areas Commun., vol. 23. no. 2. Feb. 2005.
[8] F. F. Digham, M. S. Alouini, and M. K. Simon, ”On the Energy Detection of
Unknown Signals Over Fading Channels,” IEEE Trans. Commun., vol.55,
no.1, pp.21-24, Jan. 2007.
[9] T. Yucek and H. Arslan, ”A survey of spectrum sensing algorithms for cognitive
radio applications,” IEEE Commun. Mag., vol.11, no.1, pp.116-130,
First Quarter 2009.
[10] D. D. Ariananda,M. K. Lakshmanan, and H. Nikookar, ”A study on application
of wavelets and filter banks for Cognitive Radio spectrum estimation,”
Wireless Technology Conference, European , pp.218-221, 28-29 Sep. 2009.
[11] Sai Shankar, ”Overview of Blind Sensing Techniques Considered in IEEE
802.22WRANs,” Sensor, Mesh and Ad Hoc Communications and Networks
Workshops, 2008. 5th IEEE Annu. Commun. Soc. Conf., pp.1-4, 16-20 Jun.
2008.
[12] D. D. Ariananda, M. K. Lakshmanan, and H. Nikoo, ”A survey on spectrum
sensing techniques for cognitive radio,” Cognitive Radio and Advanced
Spectrum Management, 2nd International Workshop on, pp.74-79, 18-20
May 2009.
[13] J. Proakis, ”Digital Communications,” McGraw Hill .
[14] S. M. Kay, ”Fundamentals of Statistical Signal Processing, Volume 2: Detection
Theory,” Prentice Hall, pp. 60-81.
[15] A. Wald, ”Sequential Tests of Statistical Hypotheses,” Ann. of Math. Stat.,
vol. 16. no. 2. pp. 122-141, Jun. 1945.
[16] J.-C. Lin, ”Noncoherent SPRT-based acquisition scheme for DSSS,” IEEE
Electron. Lett., vol.34, no.13, pp.1290-1291, 25 Jun. 1998.
[17] J.-C. Lin, Noncoherent sequential PN code acquisition using sliding correlation
for chip-asynchronous direct-sequence spread-spectrum communications,
IEEE Trans. Commun., vol. 50, no. 4, pp. 664-676, Apr. 2002.
[18] J.-C. Lin, A modified sequential acquisition scheme in direct-sequence
spreadspectrum communications over a fading channel, IEICE Trans. Commun.,
vol.E83-B, no. 10, pp. 2442-2446, Oct. 2000.
[19] F. M. Xu, X. F. Zheng, and Z. Zhou, ”Accurate spectrum sensing based on
high order statistical analyse,” International Symposium on Communications
and Information Technologies, IEEE, 2009.
[20] Y. P. Lin, C. He, L. G. Jiang, and D. He, ”A spectrum sensing method in
cognitive radio based on the third order cyclic cumulant,” in Proc. IEEE International
Conference on Wireless Communications and Signal Processing,
2009.
[21] G. B. Giannakis, and M. K. Tsatsanus, ”Signal detection and classification
using matched filtering and higher order statistics,” IEEE Trans. Acoust.,
Speech, Signal Process., vol.38. no.7. Jul. 1990.
[22] H. Wu, X. G. Qiao, and H. S. Zhao, ”A new approach to improve the spectrum
sensing in distributed multi-sensor networks,” International Conference
on Wireless Communications, Networking and Information Security,
IEEE, pp.514-518, 25-27 Jun. 2010.
[23] B. M. Sadler, ”Sequential detection using high order statistics,” in Proc.
IEEE International Conference on Acoustics, Speech and Signal Processing,
IEEE, Apr. 1991.
[24] Z. Quan, S.J. Shellhammer, W. Y. Zhang, and A.H. Sayed, ”Spectrum Sensing
by Cognitive Radios at Very Low SNR,” Global Telecommunications
Conference, IEEE, , pp.1-6, Nov. 30 2009 - Dec. 4 2009.
[25] J. Wang, and G. G. Bi, ”Spectrum sensing in cognitive radios based on multiple
cumulants,” IEEE Signal Process. Lett., vol.17, no.8, pp.723-726, Aug.
2010.
[26] H. S. Chen, W. Gao, and D. G. Daut, ”Spectrum sensing using cyclostationary
properties and application to IEEE 802.22WRAN,” Global Telecommunications
Conference, IEEE ., pp.3133-3138, 26-30 Nov. 2007.
[27] Meng-Lin Ku, Qingchun Chen, S.S. Ghassemzadeh, V. Tarokh, and Li-Chun
Wang, ” Service coverage for cognitive radio networks with cooperative relays
in shadowed hotspot areas,” in Proc. IEEE Wireless Communications
and Networking Conference, pp. 1759-1764, 28-31 Mar. 2011.