在本篇論文中，我們提出了一個在上行鏈路多細胞環境多用戶多輸入多輸出系統中，考慮干擾疊加(Interference-Superimposing)的分散式(Distributed)用戶選擇(User Selection)演算法。首先每個配備多根天線的使用者都利用波束成型向量(Transmit Beamforming Vector)初步的降低對鄰近細胞的干擾，接下來使用者會將其收集到的干擾疊加的量及其產生的波束成型向量傳送給基地台(Base Station, BS)。接著基地台利用他所收集到的資訊，以和速率最大化或比例公平的目標來決定自己的使用者集合，故我們所提出的方法除了考慮細胞的效能之外，同時也降低細胞間的干擾(Inter-Cell Interference, ICI)，進而提升整個系統的效能。
我們所提出的方法除了有考慮到整個系統的效能之外，同時也是一個低複雜度(Low Complexity)分散式的方法。由於基地台之間不需要傳輸任何資訊給對方，可以防止大量傳輸反饋開銷(Feedback Overhead)的情形發生。除此之外，我們也對干擾疊加的量做了數學分析，可以證明出我們所使用的干擾疊加估測器(Estimator)為一個不偏的估測器，所以當細胞內的使用者越多，考慮干擾疊加後所選擇的使用者所造成的和速率提高，故我們的演算法在細胞中的使用者越多的時候效能會更好。由模擬結果可以知道，我們所提出的方法在多細胞的環境中，效能有很顯著的改善。

In this thesis, we propose an interference-superimposing user selection scheme for uplink multiuser multiple-input multiple-output (MU-MIMO) systems in a multicell environment. The proposed scheme works in a distributed manner. Each user determines its transmit beamforming vector based on the locally available channel state information (CSI),and informs the associated base station (BS) of the amount of potentially superimposing interference caused to adjacent cells along with the resulting beamforming vector. Then, the BS selects a set of users to be served simultaneously with consideration of intercell interference. The user selection scheme is devised either to maximize the sum rate or to achieve proportional fairness among users. Our approach not only takes account of the performance of the whole system, but it is also a decentralized approach with low complexity. The base station doesn’t need to transmit any information to other BSs, so we can prevent a lot of feedback overhead transmission. In addition, we also proposed a mathematical analysis of the amount of superimposed interference. Then we can prove that the interference-superimposing estimator which we use is an unbiased estimator. Therefore, the more users are within the cell, the better performance of our algorithm is. Simulation results confirm that the proposed scheme offers significant throughput enhancement due to reduction of the intercell interference in a multicell environment.

論文審定書 i
致謝 ii
中文摘要 iii
Abstract iv
目錄 v
圖目錄 vii
第一章 導論 1
1.1 研究背景 1
1.2研究動機 1
1.3研究目的 2
1.4論文架構 2
第二章 系統模型 4
2.1 單細胞單使用者多重輸入多重輸出系統 4
2.1.1單細胞單使用者多重輸入多重輸出系統模型 4
2.1.2單細胞單使用者多重輸入多重輸出系統的容量 6
2.2 單細胞多使用者多重輸入多重輸出系統 7
2.2.1單細胞多使用者多重輸入多重輸出系統的上傳 7
2.2.2單細胞多使用者多重輸入多重輸出系統的容量 8
2.3 多細胞多使用者多重輸入多重輸出系統 9
2.4分散式的傳送波束成型矩陣 12
2.4.1 MAX-SNR波束形成向量 13
2.4.2 MAX-SGINR波束形成向量 13
第三章 文獻回顧 15
3.1使用者選擇 15
3.1.1 和速率最大化 15
3.1.2 比例公平 17
第四章 干擾疊加之使用者選擇法 20
4.1干擾疊加期望值分析 20
4.1.1 計算對鄰近細胞的疊加的干擾 20
4.1.2對鄰近細胞的干擾疊加期望值分析 21
4.2分散式系統的實現 22
4.3干擾疊加之使用者選擇法 23
4.3.1 和速率最大化 24
4.3.2 比例公平 25
第五章 模擬結果 27
第六章結論 35
參考文獻 36
中英對照表 41
縮寫 44

[1] L. Zheng and D. Tse, “Diversity and multiplexing: a fundamental tradeoff in multiple-antenna channels,” IEEE Trans. Inf. Theory, vol. 49, no. 5,pp. 1073–1096, May 2003.
[2] K.-N. Lau, “Analytical framework for multiuser uplink MIMO space-time scheduling design with convex utility functions,” IEEE Trans. Wireless Commun., vol. 3, no. 5, pp. 1832–1843, Sep. 2004.
[3] Y. Hara, L. Brunel, and K. Oshima, “Uplink spatial scheduling with adaptive transmit beamforming in multiuser MIMO systems,” in Proc. IEEE Inter. Symp. Personal, Indoor, and Mobile Radio Commun., Helsinki, Finland, Sep. 2006.
[4] S. Serbetli and A. Yener, “Beamforming and scheduling strategies for time slotted multiuser MIMO systems,” in Proc. the 38th Asilomar Conf. Signals, Systems, and Computers, PacificGrove, CA, USA, Nov. 2004, vol. 1, pp. 1227–1231.
[5] S. Catreux, P. F. Driessen, and L. J. Greenstein, “Simulation results for an interference-limited multiple-input multiple-output cellular system,” IEEE Commun. Lett., vol. 4, no. 11, pp. 334–336, Nov. 2000.
[6] A. Paulraj, R. Nabar, and D. Gore, Introduction to space time wireless communications. Cambridge University Press, 2003.
[7] D. Tse and P. Viswanath, Fundamentals of wireless communication. Cambridge University Press, 2005.
[8] G. J. Foschini and M. J. Gans, “On limits of wireless communications in a fading environment when using multiple antennas,” Kluwer Academic Publishers-Wireless Per. Commun., pp. 311–335, 1998.
[9] S. Sanayei and A. Nosratinia, “Antenna selection in MIMO systems,” IEEE Commun. Mag., vol. 42, no. 10, pp. 68–73, Oct. 2004.
[10] B. O. Lee, H. W. Je, I. S. Sohn, O.-S. Shin, and K. B. Lee, “Interference-awared centralized precoding for multicell MIMO TDD systems,” in Proc. IEEE Global Commun. Conf. 2008, New Orleans, USA, Nov.2008.
[11] B. O. Lee, O.-S. Shin, and K. B. Lee, “Uplink user selection scheme for multiuser MIMO systems in a multi-cell environment,” in Proc. IEEE Int. Conf. Commun., Cape Town, South Africa, May 2010, pp.1–6.
[12] C. K. Au-Yeung and D. J. Love, “On the performance of random vector quantization limited feedback beamforming in a MISO system,” IEEE Trans. Wireless Commun., vol. 6, no. 2, pp. 458–462, Feb. 2007.
[13] Samsung Electronics, “Inter-cell interference mitigation through limited coordination,” R1-082886, 3GPP TSG RAN WG1 Meeting #54, 2008.
[14] Alcatel Lucent, “Collaborative MIMO based on multiple base station coordination,” IEEE C802.16m-07/162, IEEE 802.16 Broadband Wireless Access Working Group, 2007.
[15] J. Zhang, R. Chen, J. G. Andrews, A. Ghosh, and R. W. Heath, “Networked MIMO with clustered linear precoding,” IEEE Trans. Wireless Commun., vol. 8, no. 4, pp. 1910–1921, Apr. 2009.
[16] M. Maddah-Ali, A. Motahari, and A. Khandani, “Communication over MIMO X channels: interference alignment, decomposition and performance analysis,” IEEE Trans. Inf. Theory, vol. 54, no. 8, pp. 3457–3470, Aug. 2008.
[17] G. Foschini, K. Karakayali, and R. A. Valenzuela, “Coordinating multiple antenna cellular networks to achieve enormous spectral efficiency,” IEE Proc. Commun., vol. 153, no. 4, pp. 548–555, Aug. 2006.
[18] D. Gesbert, A. Hjorungnes, and H. Skjevling, “Cooperative spatial multiplexing with hybrid channel knowledge,” in Proc. IEEE Int. Zurich Seminar Commun., 2006, pp. 38–41.
[19] R. Zakhour, Z. K. M. Ho, and D. Gesbert, “Distributed beamforming coordination in multicell MIMO channels,” in Proc. IEEE Veh. Tech. Conf. (VTC), Barcelona, Spain, April 2009.
[20] D. Gesbert, S. Hanly, H. Huang, S. S. Shitz, O. Simeone, and W. Yu, “Multi-cell MIMO cooperative networks: a new look at interference,” IEEE J. Sel. Areas Commun., vol. 28, no. 9, pp.1380–1408, Dec. 2010.
[21] J. Zhang and J. G. Andrews, “Adaptive spatial intercell interference cancellation in multicell wireless networks,” IEEE J. Sel. Areas Commun., vol. 28, no. 9, pp. 1455–1468, Dec. 2010.
[22] J.-C. Chen, S.-H. Wang, M.-K. Lee, and C.-P. Li, “Cross-entropy method for the optimization of optical alignment signals with diffractive effects,” IEEE/OSA Journal of Lightwave Technology, vol. 28, issue 18, pp. 2706-2714, Sep. 15, 2011.
[23] Q. H. Spencer, A. L. Swindlehurst, and M. Haardt, “Zero-forcing methods for downlink spatial multiplexing in multiuser MIMO channels,” IEEE Trans. Signal Process., vol. 52, no. 2, pp. 461–471, Feb. 2004.
[24] Z. Pan, K.-K. Wong, and T.-S. Ng, “Generalized multiuser orthogonal space-division multiplexing,” IEEE Trans. Wireless Commun., vol. 3, no. 6, pp. 1969–1973, Nov. 2004.
[25] T. Yoo and A. Goldsmith, “On the optimality of multi-antenna broadcast scheduling using zero-forcing beamforming,” IEEE J. Sel. Areas Commun., vol. 24, no. 3, pp. 528–541, Mar. 2006.
[26] N. Jindal, “MIMO broadcast channels with finite-rate feedback,” IEEE Trans. Inf. Theory., vol. 52, no. 11, pp. 5045–5060, Nov. 2006.
[27] C. J. Au-Yeung and D. J. Love, “On the performance random vector quantization limited feedback beamforming in a MISO system,” IEEE Trans. Wireless Commun., vol. 6, no. 2, pp. 458–462, Feb. 2007.
[28] S. Catreux and P. F. Driessen, “Data throughputs using multiple-input multiple-output MIMO techniques in a noise-limited cellular environment,” IEEE Trans. Wireless Commun., vol. 1, no. 2, pp. 226–235, Apr. 2002.
[29] S. Ye and R. S. Blum, “Optimized signaling for MIMO interference systems with feedback,” IEEE Trans. Signal Process., vol. 51, no. 11, pp.2839–2848, Nov. 2003.
[30] Z. Shen, R. Chen, J. G. Andrews, R. W. Heath, and B. L. Evans, “Low complexity user selection algorithms for multiuser MIMO systems with block diagonalization,” IEEE Trans. Signal Process., vol. 54, no. 9, pp. 3658–3663, Sep. 2006.
[31] J. Choi and F. Adachi, “User selection criteria for multiuser systems with optimal and suboptimal LR based detectors,” IEEE Trans. Signal Process., vol. 58, no. 10, pp. 5463–5468, Oct. 2010.
[32] V. K. N. Lau, “Proportional fair space–time scheduling for wireless communications,” IEEE Trans. Commun., vol. 53, no. 8, pp. 1353–1360, Aug. 2005.
[33] Jung-Chieh Chen, Min-Han Chiu, Yi-Syun Yang, Kuan-Yuen Liao, and Chih-Peng Li, “Efficient Capacity-Based Joint Quantized Precoding and Transmit Antenna Selection Using Cross-Entropy Method for Multiuser MIMO Systems,” International Journal of Antennas and Propagation, vol. 2012.
[34] .C.-P. Li, S.-H. Wang, and K.-C. Chan, “Low complexity transmitter architectures for SFBC MIMO-OFDM systems,” IEEE Trans. on Commun., vol. 60, issue 6, pp. 1712-1718, June 2012.
[35] Y.-L. Chen, C.-P. Li, J.-W. Wang, and J.-H. Wen, “Performance analysis of multi-step power control algorithm for cellular systems,” European Transactions on Telecommunications(ETT), vol. 19, no. 2, pp. 193-206, Mar. 2008.
[36] C.-P. Li and Z. J. Haas, “Macrodiversity technique for improvement in BER in wireless systems,” IEE Electronics Letters, vol. 33, no. 7, pp. 556-557, Mar. 1997.