研究生: |
王貞傑 Jen-Chieh Wang |
---|---|
論文名稱: |
在多頻帶OFDM 超寬頻帶系統下使用多重輸入多重輸出消除干擾之頻寬分享感知無線電技術 Spectrum Sharing Cognitive Radio with MIMO Interference Cancellation for MB-OFDM UWB System |
指導教授: |
吳仁銘
Jen-Ming Wu |
口試委員: | |
學位類別: |
碩士 Master |
系所名稱: |
電機資訊學院 - 通訊工程研究所 Communications Engineering |
論文出版年: | 2008 |
畢業學年度: | 96 |
語文別: | 英文 |
論文頁數: | 74 |
中文關鍵詞: | 感知無線電技術 、主動式多天線干擾消除理論 、超寬帶無線技術 、多頻帶正交多頻分工 |
外文關鍵詞: | Cognitive Radio, Active Interference Cancellation, UWB, MB-OFDM |
相關次數: | 點閱:2 下載:0 |
分享至: |
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報 |
為了能與主要使用者分享頻寬的利用,認知無線電的概念漸漸發展出來。認知無線電就是能夠偵測無線的環境來做適當的改變,提供足夠安全的傳輸,以改善無線頻寬使用的效率。可分成頻寬管理和適應瞬間頻寬的利用。
在這篇論文中,我們先介紹動態干擾消除。在保護頻帶被主要使用者使用中,它是如何能傳輸訊號而不影響主要使用者。動態干擾消除就是一種認知無線電。我們犧牲旁邊的一些頻寬進而換來壓制因傳輸訊號而對主要使用者造成的干擾。同時會展示關掉頻帶的方法,來對動態干擾消除的方法做一個比較。我們可以因此得知動態干擾消除的優點。
然後我們會引進多重輸出輸入系統。近來消息理論的研究已經指出使用多跟天線來傳輸會提高傳輸系統的容量,這也就是可以達到高傳輸率目的。我們會介紹垂直貝爾實驗室階層式時空碼。它是一個類似最小均方誤差的解法,但是能提供比最小均方差更好的效果。
有了上面兩個概念,我們把他們優點結合起來做傳輸,讓我們能在保護頻帶外傳輸而減少對保護頻帶的干擾。因此我們決定製造一個多輸入多輸出的傳輸系統;一根天線目的是傳輸訊號到別處,與主要使用者使用鄰近的頻帶;另一根天線目的就是在消除第一根天線對主要使用者所使用保護頻帶所造成的干擾。因此接收端看到這些干擾變得很少,在感應度以下,像雜訊一般。這樣傳輸很像是用秘密的方式,我們必須用垂直貝爾實驗室階層式時空碼才能解出我們傳輸的訊號。需要有正確的通道狀態和利用正確的解碼,才能解出我們傳輸的訊號。
In order to sharing the same frequency resource with primary users, the concept of “Cognitive Radio” is coming out. Cognitive radio defined as an intelligent wireless communication system for improving the utilization of the radio electromagnetic spectrum can be aware of its surrounding environment and then make some corresponding changes to adopt it to provide more highly reliable communication and efficient utilization of the radio spectrum. It caters dynamic spectrum management skills to prevent interference, and adapts to immediate spectrum availability.
In this paper, we first introduce the idea of active interference cancellation (AIC) that how it works under some protected bands used to transmit information sent by primary subscribers or other regular radios. In short, AIC is a cognitive method that we sacrifice the side tones beside the protected frequency bands to suppress the interference below the sensitivity threshold. We’ll also show the turn-off method and then compare the effects by those two methods, AIC and turn-off approach, so that we can find that AIC behaves more excellent.
Second, we bring in a multiple-input and multiple-output (MIMO) system. Recent information theory research has figured out that the employment of multiple antennas at the transmitter and the receiver induces enormous capacity increase. That is, it can meet high bit rate (or data rate) demand. That’s attractive nowadays for the deficiency of time resource and frequency resource. We mainly talk about V-BLAST (vertical Bell Laboratories Layered Space-Time), one of the BLAST techniques. V-BLAST is a MMSE-like (minimum mean square error) solution by taking MMSE skill, but it has better performance because it has fewer interferences than pure MMSE solution after the first result with MMSE. V-BLAST will make away with the first result and adapt MMSE again with left signals.
From the two aforesaid ideas, the AIC algorithm and the MIMO system with V-BLAST theory, we’d like to combine their advantages to make some different transmission. When using AIC algorithm, people always intercommunicate with each other outside the protected bands and try not to make interferences with the primary users. Here we want to dispose all the frequency bands, even the protected ones. We still need obey the major premise primary users could communicate without redundant interferences so that they can transmit reliably. So we’d desire to implement a MIMO system that in the transmitters some antennas can message with receivers by making use of all the spectrums, and the others attempt to send AIC signals to cancel the blanketing from the first kind of antennas. It exhibits that the power spectrum is still clean or below the sensitivity level and at the receivers the end users employ MIMO avenues, e.g. V-BLAST to resolve the information out. These make the transmission in a secret way and only consumers who know the channel-state and measure the signals with the right MIMO approach are able to get the correct information. Receivers which don’t have these prerequisites will view these signals as noise-like interferences so that they won’t bother the major consumers too much.
[1] “First report and order, revision of part 15 of the commission’s rules regarding ultra-wideband transmission systems,” FCC, ET Docket 98-153, February 14, 2002.
[2] R.W. Brodersen, A. Wolisz, D. Caabric, S.M. Mishra, D.Willkomm, 2004 White Paper: “CORVUS-A Cognitive Radio Approach for Usage of Virtual Unlicensed Spectrum”, available online. http://bwrc.eecs.berkeley.edu/Research/MCMA/CR_White_paper_final1.pdf
[3] FCC, Spectrum Policy Task Force Report, ET Docket No. 02-155, Nov 02, 2002.
[4] J. Mitola III, “Cognitive Radio: Making software radios more personal,” IEEE Pers. Commun. ,vol. 6, no. 4, pp. 13-18, Aug. 1999.
[5] J. Mitola III, “Cognitive radio for flexible mobile multimedia communications,” in 1999 IEEE International Workshop on Mobile Multimedia Communications, 15-17 Nov. 1999, pp. 3-10.
[6] J. Mitola III, “Cognitive radio an integrated agent architecture for software defined radio,” PHD thesis, KTH Royal Institute of Technology, Stockholm, Sweden, 2000.
[7] Simon Haykin, “Cognitive Radio: Brain-Empowered Wireless Communications” IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, vol. 23, no. 2, Feb. 2005.
[8] Batra, A. Lingam, S. Balakrishnan, “Multi-band OFDM: A Cognitive Radio for UWB,” in Circuits and Systems, 2006. ISCAS 2006. Proceedings. 2006 IEEE International Symposium on.
[9] H. Yamaguchi, “Active Interference Cancellation Technique for MB-OFDM Cognitive Radio,” Microwave Conference, 2004. 34th European Volume 2, pp.1105-1108, 13 Oct. 2004.
[10] J. Proakis, Digital Communications, 4th edition, McGraw Hill.
[11] Gordon L. Stuber, Principles of Mobile Communication, 2nd edition, Kluwer Academic Publ.
[12] P. W. Wolniasky, G. J. Foschini, G.D. Golden, and R. A. Valenzuela. “V-blast: An architecture for realizing very high data-rates over the rich-scattering wireless channel,” Proc. IEEE ICC-00, New Orleans, LA, USA, 18-22 June 2000.
[13] http://mimo.cm.nctu.edu.tw/Courses/Special_Topics_on_DSP_2007.htm, Ta-Sung Lee, Signal Processing for Wireless Communications, spring semester in 2007.
[14] Lin, Wen-Bin,”Channel Estimation/Equalization algorithm for NLOS WiMAX Communication Systems.” MBA thesis, Department of Electrical Engineering, National Tsing Hua University, 2006.
[15] A. Batra, J. Balakrishnan, G. Roberto Aiello, J. R. Foerster, and A. Dabak, “Design of a multiband OFDM system for realistic UWB channel environments,” IEEE Trans. Microwave Theory and Techniques, vol. 52, no. 9, Sept. 2004.