近年來，感知無線電被視為可解決頻譜使用效率不高和日漸增加的頻譜需求的方法。在本論文中提出了一個具備頻譜掃描以及傳送參數調整的感知無線電系統。在感知無線電中，因為次要使用者(Secondary User)不能影響到主要使用者(Primary User)，所以頻譜掃描是一項非常重要的議題。因此，在本論文中應用了Thomson所提出的適應性多訊窗頻譜(Adaptive Multi-taper Spectrum Estimation)偵測器。此偵測器根據Neyman-Pearson的理論，在一個固定的虛警報機率(False Alarm Rate)下，去達到一個最大的偵測率。就效能來講，可以高出能量接收機40%以上，同時在虛警報機率為0.001，偵測率要達到0.9的條件下，可以減少60%的觀察次數。

在頻譜掃描之後，傳送參數的調整可以讓次要使用者能在不影響主要使用者的情況下去傳輸。在本論文中，考慮一個主要使用者為2x2的閉迴路多輸入多輸出(Close-loop Multiple Input Multiple Output)系統操作在分時雙工(TDD)下。藉由分時雙工，次要使用者可以估測對主要使用者的干擾通道。因此，用在多使用者多輸入多輸出的區塊對角化(Block Diagonalization)可以用來消除對主要使用者的干擾。此方法相較於直接奇異值分解(Direct-Singular Value Decomposition)在訊雜比(Signal to Noise Ratio)14 dB以上、主要使用者的訊雜比0 dB的時候達到更好的通道容量。當主要使用者不在的時候，次要使用者可以直接去使用同個頻帶，並可利用天線選擇來改善效能。

再來，論文中實作了多訊窗頻譜偵測器。透過TSMC90 1P9M製程，此晶片最高可操作在122 MHz下，相對的功率消耗為30.9 mW。電路核心佔的面積為1.057 x 1.057 mm^2，晶片面積為1.56 x 1.56 mm^2。

In recent years, cognitive radios are regarded as a valid solution to solve the problem of inefficient spectrum utilization and increasing spectrum demand. A cognitive radio system which has the ability of spectrum sensing and transmission adjustment is proposed in this thesis. The spectrum sensing is an important issue because the spirit of cognitive radio is that secondary user’s transmission can not affect primary user. Therefore, an optimal detector
applied for Thomson’s adaptive multitaper spectrum estimation (AMTSE) is presented. The detector is based on Neyman-Pearson Theorem and it can adjust the detection threshold according to the environment change. Also, this detector can reduce the number of observation time and has higher detection rate for a given false alarm rate compared with other methods. The simulation shows that the detection rate can outperform energy detection by 40%. Besides, it reduces the observation time about 60% than energy detection when achieving detection rate 0.9 at false alarm rate 0.001.

Adjusting the transmission parameter is required after spectrum sensing. Here, a primary user which is 2×2 close-loop MIMO system and operates in TDD mode is taken into consideration. The assumption of TDD mode is that the secondary user can estimate the interference channel between its Tx and primary user’s Rx. By knowing the interference channel, block diagonalization which usually used in multiuser MIMO system is applied for canceling the
interference when primary user exists. The limitation of block diagonalization is that the number of transmit antennas should be larger than the total number of receive antennas, so the secondary user needs extra 2 antennas for the cancelation of interference. By the precoding method, the interference to primary user can be eliminated when the CSI is perfectly known by secondary user. The capacity will exceed the Direct-Singular Value Decomposition (D-SVD) when SNR is larger than 14 dB and the SNR of primary user equals to 0 dB. If the primary user is idle, the secondary user’s Tx may can estimate the channel state information (CSI) due to the channel reciprocity. So the extra antennas can be used to antenna selection to improve the secondary user’s BER performance.

Further, the AMTSE spectral detector is implemented by ASIC. We choose the DPSS number K = 2 to reduce the hardware cost. To deal with two paths of spectrum estimation, a novel FFT architecture is proposed. The 1024-point adopts the radix-2 and radix-2/4/8/16 to efficiently reduce the number of nontrivial twiddle factor multipliers. By using timing sharing techniques, the trivial twiddle factor multiplier can be realized by using some adders and
shifters. The chip is implemented by TSMC 90 nm, and the power consumption of this detector is 30.9 mW at 122 MHz. The core area is 1057 × 1057 mm^2 and total chip area is 1557 × 1557 mm^2.

1 Introduction 1
1.1 Backgrounds ......................................... 1
1.1.1 Spectrum Sensing .................................. 2
1.1.2 Transmission Adjustment ........................... 3
1.2 Motivation .......................................... 5
1.3 Main Contributions .................................. 5
1.4 Thesis Organization ................................. 6
2 Overview of Cognitive Radios Techniques 7
2.1 Spectrum Sensing Techniques ......................... 7
2.1.1 Energy Detection .................................. 7
2.1.2 Matched-Filtering Detection ....................... 9
2.1.3 Autocorrelation-Based Detection ................... 10
2.2 MIMO Techniques ..................................... 12
2.2.1 Capacity .......................................... 13
2.2.2 Spatial Multiplexing .............................. 15
2.3 Linear Precoding Techniques in Cognitive Radios ..... 15
2.3.1 Zero Forcing ...................................... 15
2.3.2 Block Diagonalization ............................. 16
2.3.3 Active Interference Alignment ..................... 17
3 System Design 19
3.1 System Description .................................. 19
3.1.1 Spectrum Sensing .................................. 21
3.1.2 Channel Estimation ................................ 21
3.1.3 Precoding ......................................... 23
4 Adaptive Multitaper Spectral Detector 25
4.1 System Description .................................. 25
4.1.1 Adaptive Multitaper Spectral Estimation (AMTSE) ... 26
4.1.2 Spectral Detector ................................. 27
4.1.3 Threshold Calculation ............................. 30
4.2 System Performance .................................. 31
4.2.1 Detection Rate .................................... 31
4.2.2 Complexity Comparison ............................. 38
4.3 Simulation Results .................................. 40
4.3.1 Single Band Sensing ............................... 40
4.3.2 Multi-band Sensing ................................ 41
5 Interference Cancelation Method in Cognitive Radios 43
5.1 System Model ........................................ 43
5.2 Block Diagonalization with Primary User ............. 45
5.3 Antenna Selection without Primary User .............. 50
5.4 Simulation Result with Spectrum Sensing ............. 53
6 Implementation of AMTSE Spectral Detector 55
6.1 Design Flow ......................................... 55
6.2 Word-Length Determination ........................... 56
6.3 Architecture Design ................................. 59
6.3.1 Initial PSD Estimation ............................ 61
6.3.2 Detector .......................................... 66
6.4 ASIC Implementation ................................. 67
6.4.1 Design for Test (DFT) Insertion ................... 67
6.4.2 Automatic Place and Route (APR) ................... 69
6.4.3 Post-Layout Simulation Result ..................... 71
6.4.4 Chip Summary and Measurement Result ............... 73
7 Conclusions and FutureWorks 81
7.1 Conclusion .......................................... 81
7.2 Future Works ........................................ 82

[1] FCC, "Spectrum Policy Task Force," Tech. Rep. ET Docket, no. 02-135, Nov. 2002.
[2] J. Mitola, "Software Radios: Survey, Critical Evaluation and Future Directions," IEEE Aerosp. Electron. Syst. Mag., vol. 8, pp. 25–36, Apr. 1993.
[3] ——, "The Software Radio Architecture," IEEE Commun. Mag., vol. 33, pp. 26–38, May 1995.
[4] J. Mitola and G. Q. Maguire, "Cognitive Radio: Making Software Radios More Personal," IEEE Personal Commun. Mag., vol. 6, pp. 13–18, Aug. 1999.
[5] J. Mitola, "Software Radio Architecture: A Mathematical Perspective," IEEE J. Sel. Areas Commun., vol. 17, pp. 514–538, Apr. 1999.
[6] ——, "Cognitive Radio for Flexible Mobile Multimedia Communications," in Proc. IEEE MoMuC '99, Nov. 1999, pp. 3–10.
[7] S. Haykin, "Cognitive Radio: Brain-Empowered Wireless Communications," IEEE J. Sel. Areas Commun., vol. 23, no. 3, pp. 201–205, Feb. 2005.
[8] D. Cabric and R. W. Brodersen, "Physical Layer Design Issues Unique to Cognitive Radio Systems," in Proc. IEEE PIMRC '05, vol. 2, Berlin, Germany, Sep. 2005, pp. 759–763.
[9] M. Shafi, L. J. Greenstein, and A. F. Molisch, "Propagation Issues for Cognitive Radio," Proc. IEEE, vol. 97, pp. 787–804, May 2009.
[10] S. Haykin, D. J. Thomson, and J. H. Reed, "Spectrum Sensing for Cognitive Radio," Proc. IEEE, vol. 97, pp. 849–877, May 2009.
[11] B. H. Juang, G. Y. Li, and M. Jun, "Signal Processing in Cognitive Radio," Proc. IEEE, vol. 97, pp. 805–823, May 2009.
[12] H. V. Poor, An Introduction to Signal Detection and Estimation. Berlin, Germany: Springer-Verlag, 1994, 2nd ed.
[13] S. M. Kay, Fundamentals of Statistical Signal Processing: Detection Theory. Englewood Cliffs, NJ: Prentice-Hall PTR, 1998.
[14] F. Digham, M. Alouini, and M. Simon, "On the Energy Detection of Unknown Signals Over Fading Channels," in Proc. IEEE ICC '03, vol. 5, Seattle, Washington, USA, May
2003, pp. 3575–3579.
[15] A. Sonnenschein and P. M. Fishman, "Radiometric Detection of Spread-Spectrum Signals in Noise of Uncertain Power," IEEE Trans. Aerosp. Electron. Syst., vol. 28, pp.
654–660, Jul. 1992.
[16] D. Cabric, "Cognitive Radios: System Design Perspective," Ph.D. dissertation, University of California, Berkeley, California, USA, 2007.
[17] D. Cabric, A. Tkachenko, and R. W. Brodersen, "Spectrum Sensing Measurements of Pilot, Energy, and Collaborative Detection," in Proc. IEEE MILCOM '06, Washington, DC, Oct. 2006, pp. 1–7.
[18] T. Ikuma and M. Naraghi-Pour, "A Comparison of Three Classes of Spectrum Sensing Techniques," in Proc. IEEE GLOBECOM '08, New Orleans, LO, Nov. 2008, pp. 1–5.
[19] Y. Zeng and Y. C. Liang, "Covariance Based Signal Detections for Cognitive Radio," in Proc. IEEE DySPAN '07, Dublin, Ireland, 2007, pp. 202–207.
[20] T. Ikuma and M. Naraghi-Pour, "Autocorrelation-Based Spectrum Sensing Algorithms for Cognitive Radios," in Proc. IEEE ICCCN '08, Dublin, Ireland, Aug. 2008, pp. 1–6.
[21] S. Chaudhari, J. Lunden, and V. Koivunen, "Collaborative Autocorrelation-Based
Spectrum Sensing of OFDM Signals in Cognitive Radios," in Proc. IEEE ICIS '08, Princeton, USA, Mar. 2008, pp. 19–21.
[22] S. Chaudhari, V. Koivunen, and H. V. Poor, "Distributed Autocorrelation-Based Sequential Detection of OFDM Signals in Cognitive Radios," in Proc. IEEE CrownCom '07, Singapore, May 2008, pp. 1–6.
[23] T. Yucek and H. Arslan, "A Survey of Spectrum Sensing Algorithms for Cognitive Radio Applications," IEEE Commun. Surveys Tuts., vol. 11, no. 1, pp. 116–130, 2009.
[24] R. Zhang and Y. C. Liang, "Exploiting Multi-Antennas for Opportunistic Spectrum Sharing in Cognitive Radio Networks," IEEE J. Sel. Topics Signal Process., vol. 2, no. 1, pp. 88–102, Feb. 2008.
[25] R. Prasad and A. Chockalingam, "Precoder Optimization in Cognitive Radio with Interference Constraints," in Proc. IEEE ICC '11, Kyoto, Japan, Jun. 2011, pp. 1–6.
[26] W. Wang, T. Peng, and W. Wang, "Optimal Power Control Under Interference Temperature Constraints in Cognitive Radio Network," in Proc. IEEE WCNC '07, Hong Kong, Mar. 2007, pp. 116–120.
[27] R. Zhang, "On Peak versus Average Interference Power Constraints for Spectrum Sharing in Cognitive Radio Networks," in Proc. IEEE DySPAN '08, Chicago, Illinois, USA,
Oct. 2008, pp. 1–5.
[28] J. Zhou and J. Thompson, "Linear Precoding for The Downlink of Multiple Input Single Output Coexisting Wireless Systems," IET Commun., vol. 2, no. 6, pp. 742–752, Jul. 2008.
[29] M. Jung, K. Hwang, and S. Choi, "Interference Minimization Approach to Precoding Scheme in MIMO-Based Cognitive Radio Networks," IEEE Commun. Lett., vol. 15,
no. 8, pp. 789–791, Aug. 2011.
[30] J. Kim, S. Kim, O.-S. Shin, and Y. Shin, "A Cognitive Beamforming Scheme for Coexistence of Incumbent and Cognitive Radios," in Proc. IEEE CCNC '09, Las Vegas, Nevada, USA, Jan. 2009, pp. 1–4.
[31] K. J. Lee, H. Sung, and I. Lee, "Linear Precoder Designs for Cognitive Radio Multiuser MIMO Downlink Systems," in Proc. IEEE ICC '11, Kyoto, Japan, Jun. 2011, pp. 1–5.
[32] H. Yi, H. Hu, Y. Rui, K. Guo, and J. Zhang, "Null Space-Based Precoding Scheme for Secondary Transmission in a Cognitive Radio MIMO System Using Second-Order Statistics," in Proc. IEEE ICC '09, Dresden, Germany, Jun. 2009, pp. 1–5.
[33] R. Rajbanshi, A. M. Wyglinski, and G. J. Minden, "An Efficient Implementation of NC-OFDM Transceivers for Cognitive Radios," in Proc. IEEE CrownCom '06, Mykonos
Island, Greece, Jun. 2006, pp. 1–5.
[34] I.-G. Jang, Z.-Y. Piao, Z.-H. Dong, J.-G. Chung, and K.-Y. Lee, "Low-Power FFT Design for NC-OFDM in Cognitive Radio Systems," in Proc. IEEE ISCAS '11, Rio de Janerio,
Brazil, May 2011, pp. 2449–2452.
[35] Y. Zhang and C. Leung, "A Distributed Algorithm for Resource Allocation in OFDM Cognitive Radio Systems," in Proc. IEEE VTC '08-Fall, Calgary, Canada, Sep. 2008, pp. 1–5.
[36] J. M. Wu, T. F. Yang, and H. J. Chou, "MIMO Active Interference Alignment for Underlay Cognitive Radio," in Proc. IEEE ICC '10, Cape Town, South Africa, May 2010, pp. 1–5.
[37] Q. Gao, F. Qin, and S. Sun, "Utilization of Channel Reciprocity in Advanced MIMO System," in Proc. ICST HINACOM '10, Beijing, China, Aug. 2010, pp. 1–5.
[38] D. J. Thomson, "Spectrum Estimation and Harmonic Analysis," Proc. IEEE, vol. 20, pp. 1055–1096, Sep. 1982.
[39] T. S. Chiu, "An Optimal Multiband Spectral Detector in Cognitive Radios," Master’s thesis, Dept. Electron. Eng., National Tsing Hua University, HsinChu, Taiwan, Oct. 2010.
[40] D. Slepian, "Prolate Spheroidal Wave Functions, Fourier Analysis and Uncertainty - V: The Discrete Case," Bell Syst. Tech. J., vol. 57, pp. 1371–1429, 1978.
[41] D. B. Percival and A. T. Walden, Spectral Analysis for Physical Applications. Lon- don,U.K.: Cambridge University Press, 1993.
[42] T. W. Chiang, J. M. Lin, and H. P. Ma, "Optimal Detector for Multitaper Spectrum Estimator in Cognitive Radios," in Proc. IEEE GLOBECOM '09, Honolulu, Hawaii, USA, Dec. 2009, pp. 1–6.
[43] R. Blum, "Analysis of MIMO Capacity with interference," in Proc. IEEE ICC '03, vol. 5, Anchorage, Alaska, USA, May 2003, pp. 2991–2995.
[44] R. Zhang and Y. C. Liang, "Exploiting Multi-Antennas for Opportunistic Spectrum Sharing in Cognitive Radio Networks," in Proc. IEEE PIMRC '07, Sep. 2007, pp. 1–5.
[45] Y. Bae and J. Lee, "Antenna Selection for MIMO Systems with Sequential Nulling and Cancellation," in Proc. IEEE CISS '06, Princeton, New Jersey, USA, Mar. 2006, pp. 745 –749.
[46] J. L. Tzeng, C. J. Huang, H. P. Ma, and P. A. Ting, "A High Performance Low Complexity Joint Transceiver Design for MIMO Communications," in Proc. ICST CHINACOM '09, Xi'an, China, Aug. 2009, pp. 1–5.
[47] J. Park, T. Song, J. Hur, S. M. Lee, J. Choi, K. Kim, K. Lim, C. H. Lee, H. Kim, and J. Laskar, "A Fully Integrated UHF-Band CMOS ReceiverWith Multi-Resolution Spectrum Sensing (MRSS) Functionality for IEEE 802.22 Cognitive Radio Applications," IEEE J. Solid-State circuits, vol. 44, no. 1, pp. 258–268, Jan. 2009.
[48] T. H. Yu, O. Sekkat, S. Rodriguez-Parera, D. Markovic, and D. Cabric, "A Wideband Spectrum-Sensing Processor With Adaptive Detection Threshold and Sensing Time," IEEE Trans. Circuits Syst. I, Reg. Papers, vol. 58, no. 11, pp. 1–11, 2011.
[49] W. B. Chien, C. K. Yang, and Y. H. Huang, "Energy-Saving Cooperative Spectrum Sensing Processor for Cognitive Radio System," IEEE Trans. Circuits Syst. I, Reg. Papers, vol. 58, no. 4, pp. 711–723, Apr. 2011.