隨著無線服務的快速發展，有限的頻譜資源越來越短缺。而根據美國聯邦通訊委員會最新的報告，現有的固定頻譜分配方法極度地浪費有限的頻譜資源。感知無線電因此被提出來用以有效率地使用頻譜資源。頻譜感測是感知無線電中重要的一環。合作式頻譜感測可以有效地降低頻譜感測的假警報機率和錯誤偵測機率。大部分先前的文獻都假定回報通道是完美的，已提出並比較多個硬決策規則。但回報通道的傳輸錯誤不能夠被簡單的忽略掉。因此本論文欲探討在不完美的回報通道下，融合中心應該使用何種決策規則才能提高頻譜感測的準確度。
本論文提出並比較數個基於通道狀況的類MRC(maximal ratio combining)決策規則。其中一個選擇性類MRC決策規則—選取監聽通道狀況良好的二次使用者參與合作，能有最好的表現，即達到最低的總錯誤率。我們也發現存在一個監聽通道的選取門檻值，能達到最低的總錯誤率。最後本論文亦將提出的決策規則與傳統的決策規則相比，發現提出的選擇性類MRC決策規則依舊表現最好。

With the rapid growth of wireless service, the limited spectrum resource is becoming more and more deficient. According to Federal Communications Commission’s (FCC) latest report, the existing fixed spectrum allocation policy severely underutilized the finite spectrum resource. Cognitive Radio (CR) is therefore proposed to serve as an alternative approach to utilize spectrums efficiently and spectrum sensing (SS) is an important element in CR. Cooperative Spectrum Sensing (CSS) can effectively reduce the false alarm and miss detection probabilities of spectrum sensing. However, most previous literatures propose and compare several traditional hard decision rules under the assumption that the reporting channel is perfect while the transmission error in the reporting channel can’t be simply ignored. Therefore, we investigate on how to choose suitable decision rules spectrum sensing’s detection performance under imperfect reporting channels in this paper.
In this study, we propose and investigate several channel information based Maximal Ratio Combining (MRC) decision rules over flat Rayleigh fading listening and reporting channels. Moreover, a novel channel Selection-based MRC decision rule which selects secondary users (SUs) with good listening channel qualities to coordinate is put forward and it can achieve the best performance: the lowest total error rate. Furthermore, a suboptimal listening channel threshold exists and helps Selection-based MRC decision rule achieve the lowest total error rate. Finally, our proposed decision rules are compared with traditional hard decision rules and Selection-based MRC decision rule still performs best.

[1]F. C. Committee, "United States Frequency Allocations: The Radio Spectrum," 2011.
[2]W. I. L. o. t. I. I. o. T. Shared Spectrum Company, "Spectrum Occupancy Measurements: Chicago, Illinois.," November 16 to 18 2005.
[3]J. Mitola, "Cognitive radio for flexible mobile multimedia communications," in Mobile Multimedia Communications, 1999. (MoMuC '99) 1999 IEEE International Workshop on, 1999, pp. 3-10.
[4]S. Haykin, "Cognitive radio: brain-empowered wireless communications," Selected Areas in Communications, IEEE Journal on, vol. 23, pp. 201-220, 2005.
[5]Ofcom, "Ofcom Consultation," Feb.16 2009.
[6]I. F. Akyildiz, W.-Y. Lee, M. C. Vuran, and S. Mohanty, "NeXt generation/dynamic spectrum access/cognitive radio wireless networks: A survey," Computer Networks, vol. 50, pp. 2127-2159, 9/15/ 2006.
[7]D. D. Ariananda, M. K. Lakshmanan, and H. Nikookar, "A survey on spectrum sensing techniques for cognitive radio," in Cognitive Radio and Advanced Spectrum Management, 2009. CogART 2009. Second International Workshop on, 2009, pp. 74-79.
[8]T. Yucek and H. Arslan, "A survey of spectrum sensing algorithms for cognitive radio applications," Communications Surveys & Tutorials, IEEE, vol. 11, pp. 116-130, 2009.
[9]G. Ganesan and L. Ye, "Cooperative Spectrum Sensing in Cognitive Radio, Part I: Two User Networks," Wireless Communications, IEEE Transactions on, vol. 6, pp. 2204-2213, 2007.
[10]K. Letaief and W. Zhang, "Cooperative Spectrum Sensing," in Cognitive Wireless Communication Networks, E. Hossain and V. Bhargava, Eds., ed: Springer US, 2007, pp. 115-138.
[11]I. F. Akyildiz, W.-Y. Lee, and K. R. Chowdhury, "CRAHNs: Cognitive radio ad hoc networks," Ad Hoc Netw., vol. 7, pp. 810-836, 2009.
[12]L. Zhiqiang, F. R. Yu, and H. Minyi, "A Distributed Consensus-Based Cooperative Spectrum-Sensing Scheme in Cognitive Radios," Vehicular Technology, IEEE Transactions on, vol. 59, pp. 383-393, 2010.
[13]S. Atapattu, C. Tellambura, and J. Hai, "Relay Based Cooperative Spectrum Sensing in Cognitive Radio Networks," in Global Telecommunications Conference, 2009. GLOBECOM 2009. IEEE, 2009, pp. 1-5.
[14]N. Armi, Saad, N.M., Arshad, M., "Hard Decision Combining-based Cooperative Spectrum Sensing in Cognitive Radio Systems," ITB Journal of Information and Communication Technology, vol. 3, p. 14, 2009.
[15]M. Jun and L. Ye, "Soft Combination and Detection for Cooperative Spectrum Sensing in Cognitive Radio Networks," in Global Telecommunications Conference, 2007. GLOBECOM '07. IEEE, 2007, pp. 3139-3143.
[16]A. Paula and C. Panazio, "Cooperative spectrum sensing under unreliable reporting channels," Wireless Networks, pp. 1-9, 2014/01/03 2014.
[17]C. Altay, H. B. Yilmaz, and T. Tugcu, "Cooperative sensing analysis under imperfect reporting channel," in Computers and Communications (ISCC), 2012 IEEE Symposium on, 2012, pp. 000770-000775.
[18]H. Sakran and M. Shokair, "Hard and softened combination for cooperative spectrum sensing over imperfect channels in cognitive radio networks," Telecommunication Systems, vol. 52, pp. 61-71, 2013/01/01 2013.
[19]S. Chaudhari, J. Lunden, and V. Koivunen, "BEP walls for collaborative spectrum sensing," in Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on, 2011, pp. 2984-2987.
[20]S. Chaudhari, J. Lunden, V. Koivunen, and H. V. Poor, "Cooperative Sensing With Imperfect Reporting Channels: Hard Decisions or Soft Decisions?," Signal Processing, IEEE Transactions on, vol. 60, pp. 18-28, 2012.
[21]S. Chaudhari, J. Lundén, V. Koivunen, and H. V. Poor, "BEP walls for cooperative sensing in cognitive radios using K-out-of-N fusion rules," Signal Processing, vol. 93, pp. 1900-1908, 7// 2013.
[22]F. F. Digham, M. S. Alouini, and M. K. Simon, "On the energy detection of unknown signals over fading channels," in Communications, 2003. ICC '03. IEEE International Conference on, 2003, pp. 3575-3579 vol.5.
[23]M. K. Simon and M. S. Alouini, Digital Communication over Fading Channels: A Unified Approach to Performance Analysis: Wiley, 2000.