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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 蘇炫榮(Hsuan-Jung Su) | |
dc.contributor.author | Li-Lin Lin | en |
dc.contributor.author | 林俐泠 | zh_TW |
dc.date.accessioned | 2021-06-17T00:48:08Z | - |
dc.date.available | 2013-01-17 | |
dc.date.copyright | 2012-01-17 | |
dc.date.issued | 2011 | |
dc.date.submitted | 2011-12-15 | |
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[2] Z. Feng, W. Muqing, and L. Huixin, “Coordinated multi-point transmission and reception for LTE-Advanced,” in Wireless Communications, Networking and Mobile Computing, 2009. WiCom '09. 5th International Conference on, Sep. 2009, pp. 1–4. [3] M. Karakayali, G. Foschini, and R. Valenzuela, “Network coordination for spectrally efficient communications in cellular systems,” in Wireless Communications, IEEE, vol. 13, no. 4, Aug. 2006, pp. 56 – 61. [4] M. Schubert and H. Boche, “Solution of the multiuser downlink beamforming problem with individual SINR constraints,” IEEE Trans. Veh. Technol., vol. 53, no. 1, pp. 18–28, Jan 2004. [5] A. Khachan, A. Tenenbaum, and R. S. Adve, “Linear processing for the downlink in multiuser MIMO systems with multiple data streams,” in IEEE International Conf. on Communications, vol. 9, Jun 2006, pp. 4113–4118. [6] Y. H. Yang, S. C. Lin, and H. J. Su, “Multiuser MIMO downlink beamforming design based on group maximum sinr filtering,” IEEE Trans. Signal Processing, vol. 59, no. 4, pp. 1746–1758, Apr 2011. [7] H. J. Su and E. Geraniotis, “Maximum signal-to-noise array processing for space-time coded systems,” IEEE Trans. Commun., vol. 50, no. 8, pp. 1419–1422, Sep 2002. [8] H. Boche and M. Schubert, “Optimal multi-user interference balancing using transmit beamforming,” in Wireless Personal Comm. (WPC), vol. 26, no. 4, Sep 2003. [9] M. Schubert and H. Boche, “A unifying theory for uplink and downlink multi-user beamforming,” in Proc. IEEE Intern. Zurich Seminar, Jul 2002. [10] D. Tse and P. Viswanath, “Downlink-uplink duality and effective bandwidths,”in Proc. IEEE Int. Symp. Inf. Theory (ISIT), Jul 2002. [11] H. Boche and M. Schubert, “A general duality theory for uplink and downlink beamforming,” in Proc. Of IEEE Vehicular Technology Conference (VTC-02 Fall), vol. 1, Dec. 2002, pp. 87–91. [12] V. R. Cadambe and S. A. Jafar, “Interference alignment and degrees of freedom of the K-user interference channel,” IEEE Trans. Inform. Theory, vol. 54, no. 8, pp. 3425–3441, Aug 2008. [13] K. Gomadam, V. Cadambe, and S. Jafar, “Approaching the capacity of wireless networks through distributed interference alignment,” in Proc. of IEEE GLOBECOM, Dec 2008, pp. 1–6. [14] M. Razaviyayn, M. S. Boroujeni, and Z.-Q. Luo, “Linear transceiver design for interference alignment: Complexity and computation,” in IEEE Eleventh International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Jun 2010, pp. 1–5. [15] C. Suh and D. Tse, “Interference alignment for cellular networks,” in Communication, Control, and Computing, 2008 46th Annual Allerton Conference on, Sep. 2008, pp. 1037–1044. [16] C. Suh, M. Ho, and D. Tse, “Downlink interference alignment,” in Proc. of IEEE GLOBECOM, Dec 2010, pp. 1–5. [17] Q. Shi, M. Razaviyayn, Z. Luo, and C. He, “An iteratively weighted MMSE approach to distributed sum-utility maximization for a MIMO interfering broadcast channel,” IEEE Trans. Signal Processing, pp. 1–10, Apr 2011. [18] D. Tse and P. Viswanath, Fundamentals of Wireless Communication. Cambridge University Press, 2005. [19] J. Wang and D. P. Palomar, “Worst-case robust MIMO transmission with imperfect channel knowledge,” IEEE Trans. Signal Processing, pp.3086–3100, Aug. 2009. [20] J. Proakis, Digital communications, 4th ed. McGraw-hill, 2000. [21] S. Haykin, Communication Systems, 4th ed. John Wiley & Sons, Inc., 2001. [22] S. Boyd and L. Vandenberghe, Convex Optimization. Cambridge University Press, 2003. [23] N. Jindal, W. Rhee, S. Vishwanath, S. A. Jafar, and A. Goldsmith, “Sum power iterative water-filling for multi-antenna Gaussian broadcast channels,” IEEE Trans. Inform. Theory, vol. 51, no. 4, pp. 1570 – 1580, Apr. 2005. [24] G.Caire, N. Jindal, M. Kobayashi, and N. Ravindran, “Multiuser MIMO achievable rates with downlink training and channel state feedback,”IEEE Trans. Inform. Theory, vol. 56, no. 6, pp. 2845 – 2886, Jun. 2010. [25] M. Biguesh and A. Gershman, “Training-based MIMO channel estimation: a study of estimator tradeoffs and optimal training signals,” IEEE Trans. Signal Processing, vol. 54, no. 3, pp. 884–893, Aug. 2006. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/66640 | - |
dc.description.abstract | 在多細胞多輸入多輸出通道下,基地台有多根天線傳送訊號給其細胞中服務的使用者們,且每位使用者有多根天線以接收其多個資料流;在此系統中,干擾的傳送端以及傳給同細胞中其他使用者的資料留都會產生干擾而降低系統效能。藉由修正適用於單一細胞的二重性定理使其可應用於多細胞系統,我們提出一個有效的迭代方法去共同設計傳送端、接收端的波束成形濾波器庫以及設計分配功率給每位服務的使用者。
我們採用了群體最大訊號干擾雜訊比濾波做為波束成形濾波器庫,並且利用平 均訊號干擾雜訊比當作服務質量的依據。此外,利用此多波束濾波器庫,我們可以 找到一個平衡的訊號干擾雜訊比結構因而可以找到一個最佳的功率分配矩陣以保證 每位使用者的公平性。我們同時也做出簡單的修正,提出一個功率分配的方法使得 總傳輸速率最大化。我們提出的演算法有效協調處理不同細胞、同一細胞的不同使 用間、同一使用者的不同資料流而可以達到更好的表現。模擬結果同時證明了這些 提出的演算法可以有效的處理干擾並且優於其他現存的方法。 | zh_TW |
dc.description.abstract | In multi-cell multi-input multi-output (MIMO) channel where multiple base stations with multiple antennas transmit signals to a group of users with multiple antennas in their own cell, both interfering transmitters and data streams to different users in the same cell will cause interference to one user and thus decrease system’s throughput. By judiciously modifying the duality principle which is developed for single cell scenario to our multi-cell case, we propose an efficient approach to the joint transmit-receive beamforming and power allocation for each cell based on iterative method.
We adopt group maximum signal-to-interference-plus-noise-ratio (SINR) filter banks (GSINR-FB) as our beamformers and the average SINR is served as a metric to measure the quality of service (QoS). Moreover, we find a balancing SINR structure for optimal power allocation form to guarantee fairness of each user. We also propose a heuristic power allocation for sum rate maximization. The proposed algorithm can coordinate signal across cells, users in one cell and even data streams in one user to achieve better performance. Simulation results verify these proposed algorithms can align interference effectively and outperform other existing methods. | en |
dc.description.provenance | Made available in DSpace on 2021-06-17T00:48:08Z (GMT). No. of bitstreams: 1 ntu-100-R98942075-1.pdf: 4979794 bytes, checksum: b80fe3ddf56548d00aefd56de9833125 (MD5) Previous issue date: 2011 | en |
dc.description.tableofcontents | 1 Introduction 1
1.1 Background . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Previous Work . . . . . . . . . . . . . . . . . . . . 4 1.3 Notations . . . . . . . . . . . . . . . . . . . . . . 6 2 System Model and Problem Formulation 7 2.1 System Model . . . . . . . . . . . . . . . . . . . . . 7 2.2 Problem Formulation . . . . . . . . . . . . . . . . . 10 2.2.1 QoS-Oriented Problem . . . . . . . . . . . . . . . 11 2.2.2 Sum-Rate-Oriented Problem . . . . . . . . . . . . . 12 2.3 Multi-cell Uplink-downlink Duality . . . . . . .. . . 13 2.3.1 Iterative methods based on uplink-downlink duality . . 15 3 Joint Beamforming for the Average SINR Constraint Based on Interference Alignment 18 3.1 Group Maximum SINR Filter Bank . . .. . . . . . . . . 19 3.2 Average SINR criterion . . . . . . . . . . . . . . . 21 3.3 Downlink Interference Alignment . . . . . . . . . . . 22 4 Power Allocation 25 4.1 SINR balancing structure for power allocation based on GSINRFB beamforming . . . . . . . . . . . . . . . . . . . . . . 26 4.2 Power Allocation with QoS constraints . . . . . . . . 27 4.2.1 Group Power Allocation . . . . . . . . . . . . . . 28 4.2.2 Per Stream Power Allocation . . . . . . . . . . . . 32 4.3 Power Allocation for Sum-Rate maximization .. . . . . 35 4.3.1 Group Power Allocation . . . . . . . . . . . . . . 35 4.3.2 Per-Stream Power Allocation . . . . . . . . . . . . 36 5 Simulation Results and Comparison 44 5.1 QoS-Oriented Problems . . . . . . . . . . . . . . . . 45 5.2 Sum-Rate Oriented Problems . . . . . . . . . . . . . 50 6 Convergence Behavior, Feedback Overhead and Computational Complexity 53 6.1 Convergence Behavior . . . . . . . . . . . . . . . . 53 6.2 Feedback Overhead . . . . . . . . . . . . . . . . . . 58 6.3 Complexity . . . . . . . . . . . . . . .. . . . . . . 61 7 Conclusions 63 Bibliography 65 | |
dc.language.iso | en | |
dc.title | 基於群體最大訊號干擾雜訊比濾波之多細胞協定多輸入多輸出波束形成設計 | zh_TW |
dc.title | Coordinated Multi-Cell MIMO Beamforming Design Based on Group Maximum SINR Filtering | en |
dc.type | Thesis | |
dc.date.schoolyear | 100-1 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 蘇育德,洪樂文,葉丙成,林士駿 | |
dc.subject.keyword | 多細胞,多點協調,多用戶多輸入多輸出,干擾通道,細胞內干擾,細胞間干擾,波束成形技術, | zh_TW |
dc.subject.keyword | Multi-cell,Coordinated multi-point,Multi-user multi-input multi-output,Interference channel,Intra-cell interference,Inter-cell interference,Beamforming, | en |
dc.relation.page | 68 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2011-12-19 | |
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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