在合作式感知無線電(cooperative CR network)中,時間頻譜洞(TSHs)使得頻譜使用有了更多的彈性。由於時間頻譜洞資源有限,利用波束成型技術(beamforming)存取空間頻譜洞(SSHs)且同時避免對鄰近的主要使用者(PUs)造成過度的干擾成為一項重要的技術。然而,在很多情況之下,可用的時間頻譜洞和空間頻譜洞數量隨著環境變化,以致於資源節點到中繼節點(S-to-R)和中繼節點到目的節點(R-to-D)之間的傳輸時間以及通道容量不均衡,造成此中繼傳輸系統的瓶頸效應更加嚴重。在我們的研究中,在轉送解碼(decode-and-forward)的合作式感知無線電中藉由可適性空間多工(spatial multiplexing)交互的使用時間頻譜洞和空間頻譜洞。主要的概念為利用投影奇異值分解(P-SVD)及直接奇異值分解(D-SVD)分別在主要使用者存在及不存在時存取頻譜。此外,根據主要使用者出現的情況調整傳輸時間可有效的消除瓶頸效應以及提高點對點的通道容量。模擬結果以點對點通道容量呈現出我們提出的時間分配法帶來的增益。

In the cooperative cognitive radio (CR) network, the temporal spectrum holes (TSHs) can be used to activate the utilization of the spectrum resources. Owing to the limited TSHs, the beamforming techniques are usually designed to utilize the spatial spectrum holes (SSHs) so as to avoid the excessive amount of interference to the nearby primary users (PUs). However, in many situations, the available TSHs and SSHs may be variant and consequently, the transmission time interval as well as the capacity during two phases, i.e. source-to-relay (S-to-R) and relay-to-destination (R-to-D), may not always be balanced. As a result, the so called bottleneck effects in the two-hop relay may become more serious. In this thesis, we apply the adaptive spatial multiplexing for the purpose of jointly utilizing the TSHs and SSHs in the decode-and-forward (DaF) cooperative CR network. The key idea is to utilize the projected-channel singular-value-decomposition (P-SVD) when the nearby PUs are active; while the direct-channel SVD (D-SVD) is used when there are no active PUs in the neighboring areas. Furthermore, the transmission time intervals during two phases are adjusted according to PU’s activity such that the so-called bottleneck effect can be effectively eliminated and a higher average end-to-end capacity can be achieved. In addition to the simulation results, the advantages of the proposed scheme will also be proved via analytical approach in terms of average end-to-end capacity.

[1] S. Haykin, “Cognitive radio: Brain-empowered wireless communications,” IEEE Journal on Selected Areas in Communications, vol. 23, pp. 201–220, Feburary 2005.
[2] Federal Communications Commission (FCC), “Facilitating opportinities for flexible, efficient, and reliable spectrum use employing cognitive radio technologies, notice of proposed rule making and order,” ET Docket no. 03-322, December 2003.
[3] J. Mitola and G. Q. Maguire, “Cognitive radio: Making software radio more personal,” IEEE Pers. Commun., vol. 6, no. 3, pp. 13–18, August 1999.
[4] N.-E. Wu, W.-C. Huang, and H.-J. Li, “A novel relay selection algorithm for relaying networks,” in IEEE Vehicular Technology Conference, Anchorage, Alaska,
September 2009, pp. 1–5.
[5] L. Musavian and S. A¨ıssa, “Cross-layer analysis of cognitive radio relay networks under quality of service constraints,” in IEEE Vehicular Technology Conference,
Barcelona, Spain, April 2009, pp. 1–5.
[6] Y. Han, A. Pandharipande, and S. H. Ting, “Cooperative decode-and-forward relaying for secondary spectrum access,” IEEE Transaction on Wireless Communications, vol. 8, no. 10, pp. 4945–4950, October 2009.
[7] G.-D. Zhao, J. Ma, G. Y. Li, T. Wu, Y. Kwon, A. Soong, and C.-Y. Yang, “Spatial spectrum holes for cognitive radio with relay-assisted directional transmission,” IEEE Transaction on Wireless Communications, vol. 8, no. 10, pp. 5270–5279, October 2009.
51[8] S. Huang, Z. Ding, and X. Liu, “Non-intrusive cognitive radio networks based on smart antenna technology,” in IEEE Global Telecommunications Conference, Washington, D.C., December 2007, pp. 4862–4867.
[9] S. Yiu, M. Vu, and V. Tarokh, “Interference and noise reduction by beamforming in cognitive networks,” IEEE Transaction on Communications, vol. 57, no. 10, pp. 3144–3153, October 2009.
[10] J. Liu, W. Chen, Z.-G. Cao, and Y.-J. Zhang, “A distributed beamforming approach for enhanced opportunistic spectrum access in cognitive radios,” in IEEE Global Telecommunications Conference, Honolulu, Hawaii, December 2009, pp. 1–6.
[11] 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: The Int. J. of computer and Telecommun. Networking, vol. 50, no. 13, pp. 2127–2159, September 2006.
[12] I. F. Akyildiz, W. Y. Lee, M. C. Vuran, and S. Mohanty, “A survey on spectrum management in cognitive radio networks,” IEEE Communications Magazine, vol. 46, pp. 40–48, April 2008.
[13] Q. Zhao and B. M. Sadler, “A survey of dynamic spectrum access,” IEEE Signal Process. Mag., vol. 24, pp. 79–89, May 2007.
[14] S. Srinivasa and S. Jafar, “Cognitive radios for dynamic spectrum access the throughput potential of cognitive radio: a theoretical perspective,” IEEE Communications Magazine, vol. 45, pp. 73–79, May 2007.
[15] T. M. Cover and A. A. E. Gamal, “Capacity theorems for the relay channel,” IEEE Transaction on Information Theory, vol. 25, no. 5, pp. 572–584, September 1979.
[16] A. Nosratinia, T. E. Hunter, and A. Hedayat, “Cooperative communication in wireless networks,” IEEE Communication Magazine, pp. 74–80, October 2004.
52[17] J. N. Laneman, D. N. C. Tse, and G. W. Wornell, “Cooperative diversity in wireless networks: Efficient protocols and outage behavior,” IEEE Transaction on
Information Theory, vol. 50, no. 12, pp. 3062–3080, December 2004.
[18] L.-Y. Li, X.-W. Zhou, H.-B. Xu, G. Y. Li, D.-D. Wang, and A. Soong, “Simplified relay selection and power allocation in cooperative cognitive radio systems,” IEEE
Transaction on Wireless Communications, vol. 10, no. 1, pp. 33–36, October 2010.
[19] R. Zhang and Y.-C. Liang, “Exploiting multi-antennas for opportunistic spectrum sharing in cognitive radio networks,” IEEE Journal of Selected Topics in Signal
Processing, vol. 2, no. 1, pp. 88–102, February 2008.
[20] K. Hamdi, W. Zhang, and K. B. Letaief, “Joint beamforming and scheduling in cognitive radio networks,” in IEEE Global Telecommunications Conference, Washington, D.C., December 2007, pp. 2977–2981.
[21] E. C. Y. Peh, Y.-C. Liang, and Y.-L. Guan, “Optimization of cooperative sensing in cognitive radio networks: A sensing-throughput tradeoff view,” IEEE Trans. on
Vehicular Technology, vol. 58, no. 9, pp. 5294–5299, November 2009.
[22] Y. Hu, Z.-Y. Feng, Z.-L. Wang, and J.-Q. Song, “A novel triggered asynchronous spectrum sensing scheme in cognitive radio networks,” in IEEE Vehicular Technology Conference, Ottawa, Canada, September 2010, pp. 1–5.
[23] H. Kim and K. G. Shin, “Efficient discovery of spectrum opportunities with maclayer sensing in cognitive radio networks,” IEEE Trans. on Mobile Computing,
vol. 7, no. 5, pp. 533–545, May 2008.
[24] B. Vujitic, N. Cackov, S. VujiCic, and L. Trajkovid, “Modeling and characterization of traffic in public safety wireless networks,” in Proc. Int. Symp. Performance
Evaluation of Comput. and Telecommun. Syst., Philadelphia, PA, July 2005, pp. 214–223.
[25] A. Papoulis, Probability, Random Variables, and Stochastic Processes, 4th ed. New York: McGraw-Hill, 2002.
53[26] G. L. St¨uber, Principles of mobile communication, 2nd ed. Norwell, MA: Kluwer Academic Publishers, 2001.
[27] Usage Models, IEEE 802.11n Working Group, IEEE 802.11-03/802r14, Mar. 2004.
[28] Indoor MIMO WLAN Channel Models, IEEE 802.11n Working Group, IEEE 802.11-03/162r2, Jul. 2003.
[29] S. P. Boyd and L. Vandenberghe, Convex Optimization. Cambridge, U.K.: Cambridge University Press, 2004.