在現代的無線通訊中，正交分頻多工系統 (Orthogonal Frequency-Division Multiplexing, OFDM) 已經被廣泛使用於各種裝置中-例如數位電視廣播系統。在這種情況下，當然也就產生了一些問題，其中就是頻帶使用效率的部分-如何去提高頻帶的使用效率是一大問題。為此科學家提出了感知無線電的理論(Cognitive Radio)來改善這些問題。感知無線電主要可分為頻譜檢測(Spectrum Sensing)、電源控制(Power Control)、頻帶分配(Spectrum Management) 三大部分。本篇論文主要屬於頻譜檢測的部分，並著重在第二代數位電視廣播系統 (DVB-T2) 上。藉由分析其特殊的領航訊號特性，來檢測其頻譜。

In modern wireless communications, Orthogonal Frequency-Division Multiplexing is widely used in a variety of systems such as digital video broadcasting. It turns out that the problem of how to improve the spectrum efficiency is mentioned for real applications. To solve this problem, the cognitive radio schemes are rapidly increasing in the literature. There are three main categories in cognitive radio: spectrum sensing, power control, and spectrum management. This paper studies the spectrum sensing method for DVB-T2 based on pilots to be used with a short cyclic prefix length. The DVB-T2 spectrum is sensed through the specific pilot patterns that are designed in DVB-T2.

參 考 文 獻
[1] ETSI EN 300 744 v1.6.1 (2009-01), “Digital video broadcasting (DVB);framing structure, channel coding and modulation for digital terrestrial television.''
[2] ETSI EN 302 755 v1.3.1 (2012-04), “Digital video broadcasting (DVB);frame structure channel coding and modulation for a second generation digital terrestrial television broadcasting system (DVB-T2).''
[3] S. Haykin, “Cognitive radio: Brain-empowered wireless communications,”IEEE Journal on Selected Areas in Communications, vol. 23, no. 2, pp. 201–220, Feb. 2005.
[4] J. Ma and B. H. Juang, “Signal processing in cognitive radio,”Proceedings of the IEEE, vol. 97, no. 5, pp. 805–823, May 2009.
[5] F. F. Digham, M.-S. Alouin, and M. K. Simon, “On the energy detection of unknown signals over fading channels,”in Proc. IEEE Transactions on Communications, vol. 55, no. 1, Jan. 2007, pp. 21–24.
[6] V. I. Kostylev, “Energy detection of a signal with random amplitude,”in Proc. IEEE International Conference on Communications, vol. 3, 2002, pp. 1606–1610.
[7] S. Shellhammer and R. Tandra, “Performance of the power detector with noise uncertainty,”IEEE 802.22-06/0134r0 Wireless RANs, July 2006.
[8] R. Tandra and A. Sahai, “Snr walls for signal detection,”IEEE Journal of Selected Topics in Signal Processing, vol. 2, no. 1, pp. 4–17, Feb. 2008.
[9] –––, “Fundamental limits on detection in low snr under noise uncertainty,”in Proc. IEEE International Conference on Wireless Networks, Communications and Mobile Computing, vol. 1, June 2005, pp. 464–469.
[10] G. Noh, J. Lee, H. Wang, S. You, and D. Hong, “A new spectrum sensing scheme using cyclic prefix for ofdm-based cognitive radio systems,”in Proc. IEEE Vehicular Technology Conference, Singapore, May 2008, pp. 1891–1895.
[11] A. Jayaprakasam, V. Sharma, C. R. Murthy, and P. Narayanan,“Cyclic prefix based cooperative sequential spectrum sensing algorithms for ofdm,”in Proc. IEEE International Conference on Communications, Cape Town, May 2010, pp. 1–6.
[12] N. Khambekar, L. Dong, and V. Chaudhary, “Utilizing ofdm guardinterval for spectrum sensing,”in Proc. IEEE Wireless Communications and Networking Conference, Kowloon, March 2007, pp. 38–42.
[13] N. Han, G. Zheng, S. H. Sohn, and J. M. Kim, “Cyclic autocorrelation based blind ofdm detection and identification for cognitive radio,”in Proc. IEEE WiCOM '08. 4th International Conference on Wireless Communications, Networking and Mobile Computing, Dalian, Oct. 2008, pp. 1–5.
[14] T. Yucek and H. Arslan, “Ofdm signal identification and transmission parameter estimation for cognitive radio applications,”in Proc. IEEE Global Telecommunications Conference, Washington, DC, Nov. 2007, pp. 4056 –4060.
[15] H. Li, X. Wang, and J. Nadeau, “Robust spectrum sensing for orthogonal frequency division multiplexing signal without synchronization and prior noise knowledge,”Wireless Communications and Mobile Computing, March 2012, online library.
[16] C. Wang, X. Wang, H. Li, and P. Ho, “Multi-window spectrum sensing of unsynchronized ofdm signal at very low snr,”in Proc. IEEE Global Telecommunications Conference, Honolulu, HI, Dec. 2009, pp. 1–5.
[17] H.-W. Chen, X. Wang, C.-L. Wang, and H. Lin, “Spectrum sensing of unsynchronized ofdm signals for cognitive radio communications,”in Proc. IEEE 70th Vehicular Technology Conference Fall, Anchorage, AK, Sep. 2009, pp. 1–5.
[18] H.-S. Chen, W. Gao, and D. G. Daut, “Spectrum sensing for ofdm systems employing pilot tones,”IEEE Transactions on Wireless Communications, vol. 8, no. 12, pp. 5862–5870, Dec. 2009.
[19] –––, “Spectrum sensing for ofdm systems employing pilot tones and application to dvb-t ofdm,”in Proc. IEEE International Conference on Communications, Beijing, May 2008, pp. 3421–3426.
[20] K. Dhuness and B. T. Maharaj, “A cognitive radio application of om-ofdm for implementation in dvb-t2,”in Proc. IEEE AFRICON Conference, Livingstone, Sep. 2011, pp. 1–6.
[21] H. Khoshnevis, “Pilot signature based detection of dvb-t2 broadcasting signal for cognitive radio,”2012 Third International Conference on the Network of the Future (NOF), pp. 1–5, Nov. 2012.
[22] H. V. Poor, An Introduction To Signal Detection And Estimation. Springer, 1998.
[23] S. Kay, Fundamentals of Statistical Signal Processing, Volume II: Detection Theory. Prentice Hall, 1998.
[24] Y. Chen and C. Tellambura, “Infinite series representations of the trivariate and quadrivariate rayleigh distribution and their applications,”IEEE Transactions on Communications, vol. 53, no. 12, pp. 2092–2101, Dec. 2005.