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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 蘇炫榮 | |
dc.contributor.author | Chun-Yao Chen | en |
dc.contributor.author | 陳俊耀 | zh_TW |
dc.date.accessioned | 2021-05-20T20:09:53Z | - |
dc.date.available | 2010-08-04 | |
dc.date.available | 2021-05-20T20:09:53Z | - |
dc.date.copyright | 2009-08-04 | |
dc.date.issued | 2009 | |
dc.date.submitted | 2009-07-29 | |
dc.identifier.citation | [1] Y.-H. Yang, S.-C. Lin and H.-J. Su, 'Multiuser MIMO Downlink Beamforming Based on Group Maximum SINR Filtering', IEEE International Conference on Communications (ICC), May 2008, pp.3521-3525
[2] H.-J. Su and E. Geraniotis, 'Maximum signal-to-noise array processing for space time coded systems', IEEE Trans. Comm., vol. 50, pp. 1419-1422, Sep. 2002. [3] N. Jindal, 'MIMO Broadcast Channels with Finite Rate Feedback', IEEE Trans. Information Theory, Vol. 52, No. 11, pp. 5045-5059, Nov. 2006. [4] N. Ravindran and N. Jindal, 'Limited Feedback-based Block Diagonalization for the MIMO Broadcast Channel', IEEE Journal Sel. Areas in Communications, Vol. 26, No. 8, pp. 1473-1482, Oct. 2008. [5] Cheng WANG and Ross D. Murch, 'MU-MIMO decomposition transmission with limited feedback', in Proc. IEEE Wireless Communications and Networking Conference 2007 (WCNC07), Hong Kong, Mar. 2007. [6] J. H. Kim, W. Zirwas, and M. Haardt, 'Efficient feedback via subspace-based channel quantization for distributed cooperative antenna systems with temporally correlated channels', EURASIP Journal on Advances in Signal Processing, vol. 2008, 2008, Special Issue on MIMO Transmission with Limited Feedback, Article ID 847296, 13 pages, doi:10.1155/2008/847296 [7] C. B. Chae, D. Mazzarese, N. Jindal and R. W. Heath, Jr., 'Coordinated Beamforming with Limited Feedback in the MIMO Broadcast Channel', IEEE Journal on Sel. Areas in Comm., Special Issue on Exploiting Limited Feedback in To- morrow's Wireless Communication Networks, vol. 26, no. 8, pp. 1505-1515, Oct. 2008. [8] B. Song, F. Roemer, and M. Haardt, 'Efficient channel quantization scheme for multi-user MIMO broadcast channels with RBD precoding', in Proc. IEEE Int. Conf. Acoust., Speech, and Signal Processing (ICASSP), (Las Vegas, NV), pp. 2389-2392, Apr. 2008. [9] T. M. Cover and J. A. Thomas, Elements of Information Theory.-2nd ed. Wiley, 2005. [10] J. H. Conway, R. H. Hardin, and N. J. A. Sloane, 'Packing lines, planes, etc.: Packings in Grassmannian space', Exper. Math., vol. 5, pp. 139V 159, 1996. [11] A. Edelman. 'Eigenvalues and condition numbers of random matrices', SIAM Journal on Matrix Analysis and Applications 9 (1988), 543-560. [12] W. Dai, Y. Liu, and B. Rider, 'Quantization bounds on grassmann manifolds and applications in MIMO systems', IEEE Tran. on Inform. Theory, 2008. [13] B. Hassibi and M. Sharif, 'Fundamental limits on MIMO Broadcast Channels', submitted to IEEE Jour. on Selected Areas Communications, 2006. [14] H. V. Henderson and S. R. Searle. 'On Deriving the Inverse of a Sum of Matrices. SIAM Review', 23(1):53V60, January 1981 | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/9118 | - |
dc.description.abstract | 在多用戶多輸入多輸出下傳波束成形系統下,考慮各用戶有訊號雜訊干擾比的要求。在這樣的問題底下,我們假設傳輸端採用一個最佳化的演算法做傳輸,而傳輸端需要完美的通道資訊。在此系統底下,我們將之考慮在有限速率之通道回饋的情況中,每個接收端(用戶端)假設會量測出完美且即時的通道資訊,並將之量化成有限數量的位元,回饋給傳輸端,以供傳輸端設計其波束成形濾波器及功率分配。
此系統底下,我們提出了一套新的量化並回饋通道資訊的方法,可分成兩個部分。第一個部分,我們提出了一個新的通道矩陣,用戶端選擇回饋新的通道矩陣會是比較好的選擇。第二個部分,我們進一步將此新的通道矩陣分解成兩個部分分別作量化,讓我們可以自由地去調整在兩個通道資訊上的量化位元數。如此一方面在位元數有限的情況下通道資訊可以被更有效的量化,另一方面只要隨著系統功率線性增加分解後其中一個部分的位元數,就可將系統效能損失保持在一個定值不持續增大。 | zh_TW |
dc.description.abstract | Multi-user Multi-Input Multi-Output (MIMO) downlink beamforming problem with individual signal-to-interference-plus-noise ratio (SINR) constraints is considered. We consider a general algorithm for this problem, which has great performance, but needs perfect channel state information at transmitter (CSIT). For practical considerations, we consider a system with finite rate channel feedback. In this case each receiver measures perfect and instantaneous channel state information (CSI)
and quantizes it with a finite number of bits. The transmitter receives the quantized CSI to design the beamforming filters and power allocation. We first compress the CSI for this algorithm. A new channel matrix is generated by singular value decomposition. By this operation, the new CSI can be better quantized, and it is proved that feeding back the new CSI is equivalent to feeding back the original one. Secondly, based on this observation, a quantization scheme for the new CSI is proposed. We decompose the rotated channel matrix into two parts to quantize separately. As a result, we can adjust the quantization bit allocation between the two parts, according to the varying communication environment. On one hand, one can quantize the CSI more efficiently with a fixed number of bits. On the other hand, we show that linearly scaling the number of feedback bits on only one of the two parts is su±cient to maintain a bounded system performance loss. | en |
dc.description.provenance | Made available in DSpace on 2021-05-20T20:09:53Z (GMT). No. of bitstreams: 1 ntu-98-R96942049-1.pdf: 681562 bytes, checksum: 3383018518460631cedfe394aa8d6a95 (MD5) Previous issue date: 2009 | en |
dc.description.tableofcontents | 1 Introduction 1
1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Previous Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 2 System Model 4 2.1 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2.2 Problem Formulation . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.3 Finite Rate Channel feedback: Codebook-Based Quantization and Random Quantization Codebooks . . . . . . . . . . . . . . . . . . . . 8 3 Joint Beamforming and Power Allocation 10 3.1 Maximum SINR Beamforming . . . . . . . . . . . . . . . . . . . . . . 10 3.2 Group Power Allocation . . . . . . . . . . . . . . . . . . . . . . . . . 12 4 Compression of the Essential Channel State Information 18 4.1 De‾nition of the new CSI . . . . . . . . . . . . . . . . . . . . . . . . 18 4.2 Quantization of the New CSI . . . . . . . . . . . . . . . . . . . . . . 23 5 CSI Decomposition 30 5.1 CSI Decomposition for E±cient Quantization . . . . . . . . . . . . . 30 5.2 Random Quantization Codebook for Decomposed CSI . . . . . . . . . 33 5.3 Performance Analysis with Imperfect CSIT . . . . . . . . . . . . . . . 34 5.4 Quantization Bit Allocation . . . . . . . . . . . . . . . . . . . . . . . 40 6 Conclusion 49 Bibliography 50 | |
dc.language.iso | en | |
dc.title | 有限速率之通道回饋下的多用戶多輸入多輸出下傳波束成形技術 | zh_TW |
dc.title | Multiuser MIMO Downlink Beamforming with Finite Rate Channel Feedback | en |
dc.type | Thesis | |
dc.date.schoolyear | 97-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 林士駿,馮世邁,葉丙成,張縱輝 | |
dc.subject.keyword | 多用戶多輸入多輸出(multi-user MIMO),下傳通道,波束成形技術,用戶間干擾,有限速率之通道回饋,編碼本式量化,隨機量化編碼本,上限效應 (ceiling effect), | zh_TW |
dc.subject.keyword | multi-user Multi-Input Multi-Output (MIMO),downlink channel,beamforming,Inter-User Interference (IUI),finite rate channel feedback,codebook based quantization,random quantization codebook,ceiling effect, | en |
dc.relation.page | 51 | |
dc.rights.note | 同意授權(全球公開) | |
dc.date.accepted | 2009-07-29 | |
dc.contributor.author-college | 電機資訊學院 | zh_TW |
dc.contributor.author-dept | 電信工程學研究所 | zh_TW |
顯示於系所單位: | 電信工程學研究所 |
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