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DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 蘇柏青 | |
dc.contributor.author | Ming-Fu Tang | en |
dc.contributor.author | 唐明甫 | zh_TW |
dc.date.accessioned | 2021-06-17T06:12:31Z | - |
dc.date.available | 2019-10-12 | |
dc.date.copyright | 2018-10-12 | |
dc.date.issued | 2018 | |
dc.date.submitted | 2018-10-09 | |
dc.identifier.citation | [1] T. L. Marzetta, “Noncooperative Cellular Wireless with Unlimited Numbers of Base Station Antennas,” IEEE Trans. Wireless Commun., vol. 9, no. 11, pp. 3590–3600, Nov. 2010.
[2] F. Boccardi, R.W. Heath, A. Lozano, T. L. Marzetta, and P. Popovski, “Five Disruptive Technology Directions for 5G,” IEEE Commun. Mag., vol. 52, no. 2, pp. 74–80, Feb. 2014. [3] E. G. Larsson, O. Edfors, F. Tufvesson, and T. L. Marzetta, “Massive MIMO for next generation wireless systems,” IEEE Commun. Mag., vol. 52, no. 2, pp. 186–195, Feb. 2014. [4] F. Rusek, D. Persson, B. K. Lau, E. G. Larsson, T. L. Marzetta, O. Edfors, and F. Tufvesson, “Scaling Up MIMO: Opportunities and Challenges with Very Large Arrays,” IEEE Signal Process. Mag., vol. 30, no. 1, pp. 40–60, Jan. 2013. [5] P. W. C. Chan, E. S. Lo, R. R. Wang, E. K. S. Au, V. K. N. Lau, R. S. Cheng, W. H. Mow, R. D. Murch, and K. B. Letaief, “The evolution path of 4G networks: FDD or TDD?” IEEE Commun. Mag., vol. 44, no. 12, pp. 42–50, Dec. 2006. [6] E. Björnson, E. G. Larsson, and T. L. Marzetta, “Massive MIMO: ten myths and one critical question,” IEEE Commun. Mag., vol. 54, no. 2, pp. 114–123, Feb. 2016. [7] A. Adhikary, J. Nam, J. Y. Ahn, and G. Caire, “Joint Spatial Division and Multiplexing: The Large-Scale Array Regime,” IEEE Trans. Inf. Theory, vol. 59, no. 10, pp. 6441–6463, Oct. 2013. [8] J. Nam, A. Adhikary, J. Y. Ahn, and G. Caire, “Joint Spatial Division and Multiplexing: Opportunistic Beamforming, User Grouping and Simplified Downlink Scheduling,” IEEE J. Sel. Areas Commun., vol. 8, no. 5, pp. 876–890, Oct. 2014. [9] Y. S. Jeon and M. Min, “Large System Analysis of Two-Stage Beamforming With Limited Feedback in FDD Massive MIMO Systems,” IEEE Trans. Veh. Technol., vol. 67, no. 6, pp. 4984–4997, June 2018. [10] J. Choi, D. J. Love, and P. Bidigare, “Downlink Training Techniques for FDD Massive MIMO Systems: Open-Loop and Closed-Loop Training With Memory,” IEEE J. Sel. Topics Signal Process., vol. 8, no. 5, pp. 802–814, Oct. 2014. [11] J. Fang, X. Li, H. Li, and F. Gao, “Low-Rank Covariance-Assisted Downlink Training and Channel Estimation for FDD Massive MIMO Systems,” IEEE Trans. Wireless Commun., vol. 16, no. 3, pp. 1935–1947, Mar. 2017. [12] X. Rao and V. K. N. Lau, “Distributed Compressive CSIT Estimation and Feedback for FDD Multi-User Massive MIMO Systems,” IEEE Trans. Signal Process., vol. 62, no. 12, pp. 3261–3271, Jun. 2014. [13] Z. Gao, L. Dai, Z. Wang, and S. Chen, “Spatially Common Sparsity Based Adaptive Channel Estimation and Feedback for FDD Massive MIMO,” IEEE Trans. Signal Process., vol. 63, no. 23, pp. 6169–6183, Dec. 2015. [14] Y. Han, J. Lee, and D. J. Love, “Compressed Sensing-Aided Downlink Channel Training for FDD Massive MIMO Systems,” IEEE Trans. Commun., vol. 65, no. 7, pp. 2852–2862, July 2017. [15] X. Zhang, J. Tadrous, E. Everett, F. Xue, and A. Sabharwal, “Angle-of-arrival based beamforming for FDD massive MIMO,” in 2015 49th Asilomar Conference on Signals, Systems and Computers, Nov 2015, pp. 704–708. [16] U. Ugurlu, R. Wichman, C. B. Ribeiro, and C. Wijting, “A Multipath Extraction-Based CSI Acquisition Method for FDD Cellular Networks With Massive Antenna Arrays,” IEEE Trans. Wireless Commun., vol. 15, no. 4, pp. 2940–2953, Apr. 2016. [17] H. Xie, F. Gao, S. Zhang, and S. Jin, “A Unified Transmission Strategy for TDD/FDD Massive MIMO SystemsWith Spatial Basis Expansion Model,” IEEE Trans. Veh. Technol., vol. 66, no. 4, pp. 3170–3184, Apr. 2017. [18] D. Fan, F. Gao, G. Wang, Z. Zhong, and A. Nallanathan, “Angle Domain Signal Processing-Aided Channel Estimation for Indoor 60-GHz TDD/FDD Massive MIMO Systems,” IEEE J. Sel. Areas Commun., vol. 35, no. 9, pp. 1948–1961, Sept. 2017. [19] X. Zhang, L. Zhong, and A. Sabharwal, “Directional Training for FDD Massive MIMO,” IEEE Trans. Wireless Commun., vol. 17, no. 8, pp. 5183–5197, Aug. 2018. [20] M.-F. Tang and B. Su, “Downlink precoding for multiple users in FDD massive MIMO without CSI feedback,” Journal of Signal Pro- cessing Systems, no. 2, pp. 151–163, 2015, [Online]. Available: http:/dx.doi.org/10.1007/s11265-015-1079-0. [21] M.-F. Tang, Y.-Y. Huang, and B. Su, “Beam-Time Block Coding with Joint User Grouping and Beamforming for FDD Massive MIMO Systems,” IEEE Access, pp. 1–1, 2018. [22] M.-F. Tang and B. Su, “Joint Window and Filter Optimization for New Waveforms in Multicarrier Systems,” EURASIP Journal on Advances in Signal Processing, vol. 2018, no. 1, p. 63, Oct. 2018. [23] J. Andrews, S. Buzzi, W. Choi, S. Hanly, A. Lozano, A. Soong, and J. Zhang, “WhatWill 5G Be?” IEEE J. Sel. Areas Commun., vol. 32, no. 6, pp. 1065–1082, June 2014. [24] L. Lu, G. Y. Li, A. L. Swindlehurst, A. Ashikhmin, and R. Zhang, “An Overview of Massive MIMO: Benefits and Challenges,” IEEE J. Sel. Topics Signal Process., vol. 8, no. 5, pp. 742–758, Oct. 2014. [25] J. Chen and V. Lau, “Two-Tier Precoding for FDD Multi-Cell Massive MIMO Time-Varying Interference Networks,” IEEE J. Sel. Areas Commun., vol. 32, no. 6, pp. 1230–1238, June 2014. [26] B. Hassibi and B. M. Hochwald, “How much training is needed in multiple-antenna wireless links?” IEEE Trans. Inf. Theory, vol. 49, no. 4, pp. 951–963, Apr. 2003. [27] K. Hugl, K. Kalliola, and J. Laurila, “Spatial reciprocity of uplink and downlink radio channels in FDD systems,” Proc. COST 273 Technical Document TD (02), vol. 66, p. 7, 2002. [28] S. Imtiaz, G. S. Dahman, F. Rusek, and F. Tufvesson, “On the directional reciprocity of uplink and downlink channels in Frequency Division Duplex systems,” in 2014 IEEE 25th Annual International Symposium on Personal, Indoor, and Mobile Radio Communication (PIMRC), Sept. 2014, pp. 172–176. [29] B. Carlson, “Covariance matrix estimation errors and diagonal loading in adaptive arrays,” IEEE Trans. Aerosp. Electron. Syst., vol. 24, no. 4, pp. 397–401, July 1988. [30] L. Karam and J. McClellan, “Complex Chebyshev approximation for FIR filter design,” IEEE Trans. Circuits Syst. II, vol. 42, no. 3, pp. 207–216, Mar. 1995. [31] D. Tse and P. Viswanath, Fundamentals of Wireless Communication. Cambridge University Press, 2005. [32] R. B. Ertel, P. Cardieri, K. W. Sowerby, T. S. Rappaport, and J. H. Reed, “Overview of spatial channel models for antenna array communication systems,” IEEE Personal Communications, vol. 5, no. 1, pp. 10–22, Feb. 1998. [33] L. Schumacher and B. Raghothaman, “Closed-form expressions for the correlation coefficient of directive antennas impinged by a multimodal truncated Laplacian PAS,” IEEE Trans. Wireless Commun., vol. 4, no. 4, pp. 1351–1359, July 2005. [34] H. Krim and M. Viberg, “Two decades of array signal processing research: the parametric approach,” IEEE Signal Process. Mag., vol. 13, no. 4, pp.67–94, July 1996. [35] B. D. V. Veen and K. M. Buckley, “Beamforming: a versatile approach to spatial filtering,” IEEE ASSP Magazine, vol. 5, no. 2, pp. 4–24, Apr. 1988. [36] F. Vincent and O. Besson, “Steering vector errors and diagonal loading,” IEE Proc. Radar Sonar Navzg, vol. 151, no. 6, pp. 337–343, Dec. 2004. [37] 3GPP, “Spatial channel model for Multiple Input Multiple Output (MIMO) simulations (Release 14),” TR25.996, V14.0.0, Apr. 2017. [38] ——, “Study on 3D channel model for LTE (Release 12),” TR36.873, V12.7.0, Dec. 2017. [39] J. Brady, N. Behdad, and A. M. Sayeed, “Beamspace MIMO for Millimeter-Wave Communications: System Architecture, Modeling, Analysis, and Measurements,” IEEE Trans. Antennas Propag., vol. 61, no. 7, pp. 3814–3827, Jul. 2013. [40] Q. Spencer, A. 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. [41] H. Xie, F. Gao, and S. Jin, “An Overview of Low-Rank Channel Estimation for Massive MIMO Systems,” IEEE Access, vol. 4, pp. 7313–7321, 2016. [42] V. Tarokh, H. Jafarkhani, and A. R. Calderbank, “Space-time block codes from orthogonal designs,” IEEE Trans. Inf. Theory, vol. 45, no. 5, pp. 1456–1467, Jul. 1999. [43] Y. Xu, G. Yue, and S. Mao, “User Grouping for Massive MIMO in FDD Systems: New Design Methods and Analysis,” IEEE Access, vol. 2, pp. 947–959, 2014. [44] X. Sun, X. Gao, G. Y. Li, and W. Han, “Agglomerative user clustering and downlink group scheduling for FDD massive MIMO systems,” in 2017 IEEE International Conference on Communications (ICC), May 2017, pp. 1–6. [45] M.-F. Tang, C. C. Chen, and B. Su, “Downlink path-based precoding in FDD massive MIMO systems without CSI feedback,” in 2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM), July 2016, pp. 1–5. [46] W. Choi, N. Himayat, S. Talwar, and M. Ho, “The Effects of Co-channel Interference on Spatial Diversity Techniques,” in 2007 IEEE Wireless Communications and Networking Conference, Mar. 2007, pp. 1936–1941. [47] H. Lin, F. Gao, S. Jin, and G. Y. Li, “A New View of Multi-User Hybrid Massive MIMO: Non-Orthogonal Angle Division Multiple Access,” IEEE J. Sel. Areas Commun., vol. 35, no. 10, pp. 2268–2280, Oct. 2017. [48] Q. Spencer, B. Jeffs, and M. Jensen, “Modeling the statistical time and angle of arrival characteristics of an indoor multipath channel,” IEEE J. Sel. Areas Commun., vol. 18, no. 3, pp. 347–360, Mar. 2000. [49] O. E. Ayach, S. Rajagopal, S. Abu-Surra, Z. Pi, and R. W. Heath, “Spatially Sparse Precoding in Millimeter Wave MIMO Systems,” IEEE Trans. Wireless Commun., vol. 13, no. 3, pp. 1499–1513, Mar. 2014. [50] 3GPP, “Study on elevation beamforming/full-dimension (FD) MIMO for LTE (Release 13),” TR36.897, V13.0.0, June 2015. [51] “Propagation data and prediction methods for the planning of indoor radio communication systems and radio local area networks in the frequency range 900 MHz to 100 GHz,” Recommendation ITU-R P.1238–7, 2012. [52] S. Boyd and L. Vandenberghe, Convex optimization. Cambridge university press, 2004. [53] K. E. Atkinson, An introduction to numerical analysis. John Wiley & Sons, 2008. [54] J. Zhao, F. Gao, W. Jia, S. Zhang, S. Jin, and H. Lin, “Angle Domain Hybrid Precoding and Channel Tracking for MillimeterWave Massive MIMO Systems,” IEEE Trans. Wireless Commun., vol. 16, no. 10, pp. 6868–6880, Oct. 2017. [55] R. Schmidt, “Multiple emitter location and signal parameter estimation,” IEEE Trans. Antennas Propag., vol. 34, no. 3, Mar. 1986. [56] R. Roy and T. Kailath, “ESPRIT-estimation of signal parameters via rotational invariance techniques,” IEEE Trans. Acoust., Speech, Signal Process., vol. 37, no. 7, pp. 984–995, July 1989. [57] J. H. Ward, “Hierarchical grouping to optimize an objective function,” Journal of the American statistical association, vol. 58, no. 301, pp. 236–244, 1963. [58] A. Alkhairy, K. Christian, and J. Lim, “Design and characterization of optimal FIR filters with arbitrary phase,” IEEE Trans. Signal Process., vol. 41, no. 2, pp. 559–572, Feb. 1993. [59] M. Grant and S. Boyd, “CVX: Matlab Software for Disciplined Convex Programming, version 2.1,” http://cvxr.com/cvx, Mar. 2014. [60] M. Colombo and J. Gondzio, “Further development of multiple centrality correctors for interior point methods,” Computational Optimization and Applications, vol. 41, no. 3, pp. 277–305, 2008. [61] T. H. Cormen, Introduction to algorithms. MIT press, 2009. [62] A. Alkhateeb, O. E. Ayach, G. Leus, and R.W. Heath, “Channel Estimation and Hybrid Precoding for MillimeterWave Cellular Systems,” IEEE J. Sel. Topics Signal Process., vol. 8, no. 5, pp. 831–846, Oct. 2014. [63] C. B. Peel, B. M. Hochwald, and A. L. Swindlehurst, “A vector- perturbation technique for near-capacity multiantenna multiuser communication-part I: channel inversion and regularization,” IEEE Trans. Commun., vol. 53, no. 1, pp. 195–202, Jan. 2005. [64] M. Z. Win and R. A. Scholtz, “Energy capture vs. correlator resources in ultra-wide bandwidth indoor wireless communications channels,” in MILCOM 97 MILCOM 97 Proceedings, vol. 3, Nov. 1997, pp. 1277–1281, vol.3. [65] P. Hoeher, “A statistical discrete-time model for the WSSUS multipath channel,” IEEE Trans. Veh. Technol., vol. 41, no. 4, pp. 461–468, Nov. 1992. [66] D. Samardzija and N. Mandayam, “Unquantized and uncoded channel state information feedback in multiple-antenna multiuser systems,” IEEE Trans. Commun., vol. 54, no. 7, pp. 1335–1345, July 2006. [67] G. Caire, N. Jindal, M. Kobayashi, and N. Ravindran, “Multiuser MIMO Achievable Rates With Downlink Training and Channel State Feedback,” IEEE Trans. Inf. Theory, vol. 56, no. 6, pp. 2845–2866, June 2010. [68] G.Wunder, P. Jung, M. Kasparick, T.Wild, F. Schaich, Y. Chen, S. T. Brink, I. Gaspar, N. Michailow, A. Festag, L. Mendes, N. Cassiau, D. Ktenas, M. Dryjanski, S. Pietrzyk, B. Eged, P. Vago, and F. Wiedmann, “5GNOW: non-orthogonal, asynchronous waveforms for future mobile applications,” IEEE Commun. Mag., vol. 52, no. 2, pp. 97–105, Feb. 2014. [69] X. Zhang, L. Chen, J. Qiu, and J. Abdoli, “On theWaveform for 5G,” IEEE Commun. Mag., vol. 54, no. 11, pp. 74–80, Nov. 2016. [70] A. A. Zaidi, R. Baldemair, H. Tullberg, H. Bjorkegren, L. Sundstrom, J. Medbo, C. Kilinc, and I. D. Silva, “Waveform and Numerology to Support 5G Services and Requirements,” IEEE Commun. Mag., vol. 54, no. 11, pp. 90–98, Nov. 2016. [71] L. Zhang, A. Ijaz, P. Xiao, A. Quddus, and R. Tafazolli, “Subband Filtered Multi-Carrier Systems for Multi-Service Wireless Communications,” IEEE Trans. Wireless Commun., vol. 16, no. 3, pp. 1893–1907, Mar. 2017. [72] L. Zhang and A. Ijaz and P. Xiao and R. Tafazolli, “Multi-service system: An enabler of flexible 5g air interface,” IEEE Commun. Mag., vol. 55, no. 10, pp. 152–159, Oct. 2017. [73] P. Guan, D. Wu, T. Tian, J. Zhou, X. Zhang, L. Gu, A. Benjebbour, M. Iwabuchi, and Y. Kishiyama, “5G Field Trials: OFDM-Based Waveforms and Mixed Numerologies,” IEEE J. Sel. Areas Commun., vol. 35, no. 6, pp. 1234–1243, June 2017. [74] B. Farhang-Boroujeny, “OFDM Versus Filter Bank Multicarrier,” IEEE Signal Process. Mag., vol. 28, no. 3, pp. 92–112, May 2011. [75] X. Mestre, M. Majoral, and S. Pfletschinger, “An Asymptotic Approach to Parallel Equalization of Filter Bank Based Multicarrier Signals,” IEEE Trans. Signal Process., vol. 61, no. 14, pp. 3592–3606, July 2013. [76] M. Pauli and P. Kuchenbecker, “On the reduction of the out-of-band radiation of OFDM-signals,” in Proc. IEEE Int. Conf. Commun., vol. 3, June 1998, pp. 1304–1308. [77] Y. Medjahdi, R. Zayani, H. Shaïek, and D. Roviras, “WOLA processing: A useful tool for windowed waveforms in 5G with relaxed synchronicity,” in 2017 IEEE International Conference on Communications Workshops (ICC Workshops), May 2017, pp. 393–398. [78] Y.-P. Lin and S. M. Phoong, “Window designs for DFT-based multicarrier systems,” IEEE Trans. Signal Process., vol. 53, no. 3, pp. 1015–1024, Mar. 2005. [79] D. Roque and C. Siclet, “Performances of Weighted Cyclic Prefix OFDM with Low-Complexity Equalization,” IEEE Commun. Lett., vol. 17, no. 3, pp. 439–442, Mar. 2013. [80] N. Michailow, M. Matthé, I. S. Gaspar, A. N. Caldevilla, L. L. Mendes, A. Festag, and G. Fettweis, “Generalized Frequency Division Multiplexing for 5th Generation Cellular Networks,” IEEE Trans. Commun., vol. 62, no. 9, pp. 3045–3061, Sept. 2014. [81] H. M. Chen, W. C. Chen, and C. D. Chung, “Spectrally Precoded OFDM and OFDMA with Cyclic Prefix and Unconstrained Guard Ratios,” IEEE Trans. Wireless Commun., vol. 10, no. 5, pp. 1416–1427, May 2011. [82] M. Ma, X. Huang, B. Jiao, and Y. J. Guo, “Optimal Orthogonal Precoding for Power Leakage Suppression in DFT-Based Systems,” IEEE Trans. Commun., vol. 59, no. 3, pp. 844–853, Mar. 2011. [83] A. Farhang, N. Marchetti, and L. E. Doyle, “Low-Complexity Modem Design for GFDM,” IEEE Trans. Signal Process., vol. 64, no. 6, pp. 1507–1518, Mar. 2016. [84] V. Vakilian, T. Wild, F. Schaich, S. ten Brink, and J. F. Frigon, “Universal-filtered multi-carrier technique for wireless systems beyond LTE,” in 2013 IEEE Globecom Workshops (GC Wkshps), Dec. 2013, pp. 223–228. [85] T. Wild, F. Schaich, and Y. Chen, “5G air interface design based on Universal Filtered (UF-)OFDM,” in 2014 19th International Conference on Digital Signal Processing, Aug. 2014, pp. 699–704. [86] M.-F. Tang and B. Su, “Filter optimization of low out-of-subband emission for universal-filtered multicarrier systems,” in 2016 IEEE International Conference on Communications Workshops (ICC), May 2016, pp. 468–473. [87] L. Zhang, P. Xiao, and A. Quddus, “Cyclic Prefix-Based Universal Filtered Multicarrier System and Performance Analysis,” IEEE Signal Process. Lett., vol. 23, no. 9, pp. 1197–1201, Sept. 2016. [88] J. Abdoli, M. Jia, and J. Ma, “Filtered OFDM: A new waveform for future wireless systems,” in 2015 IEEE 16th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), June 2015, pp. 66–70. [89] F.-O. E. for Flexible Waveform in the 5th Generation Cellular Networks, “Filtered-OFDM - Enabler for Flexible Waveform in the 5th Generation Cellular Networks,” in 2015 IEEE Global Communications Conference (GLOBECOM), Dec. 2015, pp. 1–6. [90] P. Weitkemper, J. Bazzi, K. Kusume, A. Benjebbour, and Y. Kishiyama, “Adaptive filtered OFDM with regular resource grid,” in 2016 IEEE International Conference on Communications Workshops (ICC), May 2016, pp. 462–467. [91] D. J. Han, J. Moon, D. Kim, S. Y. Chung, and Y. H. Lee, “Combined Subband-Subcarrier Spectral Shaping in Multi-Carrier Modulation Under the Excess Frame Length Constraint,” IEEE J. Sel. Areas Commun., vol. 35, no. 6, pp. 1339–1352, June 2017. [92] Y.-P. Lin, S.-M. Phoong, and P. Vaidyanathan, Filter bank transceivers for OFDM and DMT systems. Cambridge University Press, 2010. [93] J. A. Zhang, X. Huang, A. Cantoni, and Y. J. Guo, “Sidelobe Suppression with Orthogonal Projection for Multicarrier Systems,” IEEE Trans. Commun., vol. 60, no. 2, pp. 589–599, Feb. 2012. [94] P. P. Vaidyanathan, Multirate systems and filter banks. Prentice-Hall, 1993. [95] K. Ichige, M. Iwaki, and R. Ishii, “Accurate estimation of minimum filter length for optimum FIR digital filters,” IEEE Trans. Circuits Syst. II, vol. 47, no. 10, pp. 1008–1016, Oct. 2000. [96] A. Papoulis, Signal analysis. McGraw-Hill, 1977, vol. 191. [97] S.-P. Wu, S. Boyd, and L. Vandenberghe, “FIR filter design via semidefinite programming and spectral factorization,” in Proceedings of 35th IEEE Conference on Decision and Control, vol. 1, Dec. 1996, pp. 271–276. [98] R. G. Lorenz and S. P. Boyd, “Robust minimum variance beamforming,” IEEE Trans. Signal Process., vol. 53, no. 5, pp. 1684–1696, May 2005. [99] Z. L. Yu, W. Ser, M. H. Er, Z. Gu, and Y. Li, “Robust Adaptive Beamformers Based on Worst-Case Optimization and Constraints on Magnitude Response,” IEEE Trans. Signal Process., vol. 57, no. 7, pp. 2615–2628, July 2009. [100] S. W. Peters and R. W. Heath, “Interference alignment via alternating minimization,” in 2009 IEEE International Conference on Acoustics, Speech and Signal Processing, Apr. 2009, pp. 2445–2448. [101] L. Kong, S. Han, and C. Yang, “Hybrid PrecodingWith Rate and Coverage Constraints for Wideband Massive MIMO Systems,” IEEE Trans. Wireless Commun., vol. 17, no. 7, pp. 4634–4647, July 2018. [102] T. Wild and F. Schaich, “A Reduced Complexity Transmitter for UF-OFDM,” in 2015 IEEE 81st Vehicular Technology Conference (VTC Spring), May 2015, pp. 1–6. [103] G. Cuypers, K. Vanbleu, G. Ysebaert, M. Moonen, and P. Vandaele, “Combining raised cosine windowing and per tone equalization for RFI mitigation in DMT receivers,” in Communications, 2003. ICC ’03. IEEE International Conference on, vol. 4, May 2003, pp. 2852–2856 vol.4. [104] J. Proakis, Digital Communications, 4th ed. McGraw-Hill, 2001. [105] H. T. Hsieh and W. R. Wu, “Blind Maximum-Likelihood Carrier-Frequency-Offset Estimation for Interleaved OFDMA Uplink Systems,” IEEE Trans. Veh. Technol., vol. 60, no. 1, pp. 160–173, Jan. 2011. [106] X. N. Zeng and A. Ghrayeb, “Joint CFO and channel estimation for OFDMA uplink: an application of the variable projection method,” IEEE Trans. Wireless Commun., vol. 8, no. 5, pp. 2306–2311, May 2009. [107] S. Sesia, M. Baker, and I. Toufik, LTE - the UMTS long term evolution: from theory to practice. New Jersey: John Wiley & Sons, 2011. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/71862 | - |
dc.description.abstract | 本論文中探討在分頻雙工巨量天線系統中針對多位使用者在下行傳輸之波束成型設計之議題。由於巨量天線系統具備大幅提高頻寬效益及傳輸能量效率之能力,已被視為實現下一代無線通訊需求之重要技術。在此系統下,如何使基地台獲取與使用者間下行通道資訊為此系統效能提升之關鍵。分時雙工模式基於通道互惠之特性,能夠使基地台有效獲取下行通道資訊,因此被目前與巨量天線系統相關之研究廣泛採用。雖然分頻雙工模式並不具有通道互惠性,它卻更適合用於需要低時間延遲之通訊服務,因此分頻雙工模式在目前的行動通訊系統中被大量採用。下行資料傳輸效能可藉由下行波束成型設計以達到最佳化。而波束成型之設計通常需要下行通道之資訊。在上一代通訊系統為分頻雙工系統獲取通道資訊的機制中,下行訓練及上行回饋為必要之手段。然而,在分頻雙工巨量天線系統中,使用以往獲取通道資訊的機制會產生大量的頻寬損耗。因此,此論文中提出了不需下行訓練及上行回饋之波束成型設計方法。這些方法更適合用在需要極度低延遲的通訊應用中。除此之外,本論文也提出了能夠大幅降低為了下行訓練及上行回饋產生的頻寬損耗之通道估計方法。此方法能顯著提升分頻雙工多天線系統中下行傳輸的頻寬效益。
關鍵字:巨量多天線系統、波束成型、分頻雙工 | zh_TW |
dc.description.abstract | This dissertation addresses the fundamental issues of beamforming designs in massive multi-input-multi-output (MIMO) systems, especially for these systems operated under the frequency-division duplexing (FDD) mode. Massive MIMO is regarded as a crucial technology in enabling the next generation mobile communications due to its capability of enhancing system capacity and improving energy efficiency. Acquiring accurate downlink (DL) channel state information (CSI) at the transmitter for performing DL beamforming is regarded as a key of realizing the advantages of massive MIMO. The majority of studies concerning massive MIMO adopted the time-division duplexing (TDD) mode because it enables the base station (BS) to acquire DL CSI efficiently due to channel reciprocity. FDD massive MIMO is also considered because FDD is more suitable for providing low-latency services, and that is why it is widely deployed in nowadays cellular networks. Nevertheless, channel reciprocity no longer holds in FDD systems. Therefore, DL training and uplink (UL) feedback prior to DL data transmission are usually required for CSI acquisition at the BS. Compressing the overhead of DL training and UL feedback is considered utterly critical to the validation of FDD massive MIMO. In the literature, many channel estimation and beamforming schemes aimed at improving the efficiency of DL training and UL feedback have been proposed. However, these schemes all result in more round-trips between the BS and UEs than what TDD massive MIMO possesses. This implies longer latency of DL transmission. In this dissertation, beamforming schemes that need neither DL training nor UL feedback are proposed. Therefore, the proposed schemes are more suitable for extremely low-latency applications, which play an important role in the next generation wireless communication systems. The proposed schemes take advantage of the angular reciprocal property of FDD systems, which was suggested by a number of channel measurement studies. This property is called angle reciprocity in the literature. The simulation results provided in this dissertation indicate that the proposed schemes possess comparable performance to previous schemes that need DL training and UL feedback. Furthermore, a two-stage beamforming scheme with significantly reduced overhead of training and feedback is proposed by utilizing angle reciprocity. It is demonstrated that the proposed two-stage beamforming scheme outperforms some other schemes in achievable spectral efficiency. An optimization method for multicarrier new transmission waveform design is also proposed in this dissertation.
Keywords: Massive MIMO, robust beamforming, beam-time block coding, no CSI feedback, two-stage beamforming, new waveform. | en |
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dc.description.tableofcontents | 口試委員簽名頁
致謝 i 中文摘要 ii Abstract iii Contents iv List of Figures ix List of Tables xi 1 Introduction 1 1.1 Downlink Beamforming for Multiuser Transmissions in FDD Mas- sive MIMO Without CSI Feedback . . . . . . . . . . . . . . . . . 3 1.2 Beam-Time Block Coding with Joint User Grouping and Beam- forming for FDD Massive MIMO Systems . . . . . . . . . . . . . 3 1.3 Spectrally-Efficient Channel Estimation for Two-Stage Beamforming in FDD Massive MIMO . . . . . . . . . . . . . . . . . . . . . 4 1.4 New Multicarrier Transmission Waveform Design . . . . . . . . . 5 2 Downlink Beamforming for Multiuser Transmissions in FDD Massive MIMO Without CSI Feedback . . . . . . . . . . . . . . . . . . . . . . . 6 2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.2 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 2.2.1 Channel Model . . . . . . . . . . . . . . . . . . . . . . . 11 2.2.2 UL Signaling . . . . . . . . . . . . . . . . . . . . . . . . 12 2.2.3 DL Transmission . . . . . . . . . . . . . . . . . . . . . . 13 2.3 Problem Statement . . . . . . . . . . . . . . . . . . . . . . . . . 14 2.4 Proposed Beamforming Methods . . . . . . . . . . . . . . . . . . 16 2.4.1 Beamforming Using Diagonal Loading . . . . . . . . . . 16 2.4.2 Robust Beamforming Using Generalized PM Algorithm . 18 2.4.3 Summary of the Two Proposed Beamforming Methods . . 19 2.5 Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . . 20 2.5.1 Beam Pattern . . . . . . . . . . . . . . . . . . . . . . . . 22 2.5.2 Achievable Sum Rate . . . . . . . . . . . . . . . . . . . . 23 2.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 3 Beam-Time Block Coding with Joint User Grouping and Beamforming for FDD Massive MIMO Systems 26 3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 3.1.1 Related Works . . . . . . . . . . . . . . . . . . . . . . . 28 3.1.2 Summary of the BTBC Scheme . . . . . . . . . . . . . . 30 3.1.3 Organization and Notations . . . . . . . . . . . . . . . . 31 3.2 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 3.2.1 Channel Model . . . . . . . . . . . . . . . . . . . . . . . 33 3.2.2 Angle Reciprocity in FDD Systems . . . . . . . . . . . . 34 3.2.3 Angular-Domain Channel Characterization . . . . . . . . 35 3.2.3.1 UL Channel Spatial Signature Optimization . . 36 3.2.3.2 UL Dominant Path Direction Estimation . . . . 37 3.2.3.3 DL Angular-Domain Channel Characterization . 40 3.3 Beam-Time Block Coding . . . . . . . . . . . . . . . . . . . . . 41 3.4 Joint UE Grouping and Beamforming . . . . . . . . . . . . . . . 44 3.4.1 UE Grouping . . . . . . . . . . . . . . . . . . . . . . . . 44 3.4.2 Beamforming Optimization . . . . . . . . . . . . . . . . 48 3.4.3 Joint UE Grouping and Beamforming Optimization . . . . 50 3.4.4 Complexity Analysis . . . . . . . . . . . . . . . . . . . . 51 3.5 Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . . 53 3.5.1 CDF of Group Number . . . . . . . . . . . . . . . . . . . 56 3.5.2 BER Performance Comparison . . . . . . . . . . . . . . . 56 3.5.3 Average Worst-UE BER Performance Comparison . . . . 61 3.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 4 Spectrally-Efficient Channel Estimation for Two-Stage Beamforming in FDD Massive MIMO 66 4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 4.2 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70 4.2.1 Channel Model . . . . . . . . . . . . . . . . . . . . . . . 70 4.3 Two-Stage Beamforming for DL Transmission . . . . . . . . . . 71 4.3.1 Two-Stage Beamforming Design . . . . . . . . . . . . . . 72 4.3.2 Problem Description . . . . . . . . . . . . . . . . . . . . 74 4.4 Proposed Channel Estimation Scheme . . . . . . . . . . . . . . . 78 4.4.1 Auxiliary Path Selection . . . . . . . . . . . . . . . . . . 78 4.4.2 DL Training with Path Grouping and FBF . . . . . . . . . 80 4.4.3 Proposed Path Grouping Method . . . . . . . . . . . . . . 82 4.4.4 Angular-Domain Channel Reconstruction . . . . . . . . . 85 4.5 Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . . 87 4.5.1 CDF of DL Training Overhead . . . . . . . . . . . . . . . 89 4.5.2 Average Achievable Sum Rate and Spectral Efficiency . . 90 4.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91 5 Joint Window and Filter Optimization for New Waveforms in Multicarrier Systems 94 5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 5.1.1 Related Waveforms . . . . . . . . . . . . . . . . . . . . . 97 5.1.2 Contributions . . . . . . . . . . . . . . . . . . . . . . . . 98 5.1.3 Organization and Notations . . . . . . . . . . . . . . . . 99 5.2 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 5.2.1 Transmitter Structure . . . . . . . . . . . . . . . . . . . . 100 5.2.2 Effective Channel . . . . . . . . . . . . . . . . . . . . . . 103 5.2.3 Receiver Structure . . . . . . . . . . . . . . . . . . . . . 103 5.2.4 Noise Analysis . . . . . . . . . . . . . . . . . . . . . . . 106 5.3 Problem Statement . . . . . . . . . . . . . . . . . . . . . . . . . 108 5.4 Proposed Method . . . . . . . . . . . . . . . . . . . . . . . . . . 111 5.4.1 Optimization of Filter Function . . . . . . . . . . . . . . 112 5.4.2 Optimization of Window Coefficients . . . . . . . . . . . 114 5.4.3 Proposed Iterative Method for Joint Optimization . . . . . 117 5.4.4 Convergence Analysis of the Proposed Algorithm . . . . . 118 5.4.5 Complexity Analysis of the Proposed Algorithm . . . . . 119 5.4.6 Complexity Analysis of the Transceiver . . . . . . . . . . 120 5.5 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . 120 5.5.1 Parameter Settings . . . . . . . . . . . . . . . . . . . . . 120 5.5.2 Convergence of the Proposed Algorithm . . . . . . . . . . 121 5.5.3 Approximation of SNR Loss . . . . . . . . . . . . . . . . 122 5.5.4 Related Waveforms for Comparison . . . . . . . . . . . . 123 5.5.5 Normalized PSD . . . . . . . . . . . . . . . . . . . . . . 124 5.5.6 Bandwidth Efficiency . . . . . . . . . . . . . . . . . . . . 126 5.5.7 Single-User BER Simulations . . . . . . . . . . . . . . . 127 5.5.8 Asynchronous Multiuser BER Simulations . . . . . . . . 131 5.5.9 BER Simulations With ETU Channel Model . . . . . . . 134 5.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135 A Appendix 138 A.1 Derivation of Constraint (5.27c) . . . . . . . . . . . . . . . . . . 138 A.2 Proof of Theorem 1 . . . . . . . . . . . . . . . . . . . . . . . . . 139 Bibliography 141 | |
dc.language.iso | en | |
dc.title | 分頻雙工巨量多天線系統中多使用者之下行波束成型 | zh_TW |
dc.title | Multiuser Downlink Beamforming in Frequency-Division Duplexing Massive MIMO Systems | en |
dc.type | Thesis | |
dc.date.schoolyear | 107-1 | |
dc.description.degree | 博士 | |
dc.contributor.oralexamcommittee | 闕志達,蘇炫榮,馮世邁,魏宏宇,林源倍 | |
dc.subject.keyword | 巨量多天線系統,波束成型,分頻雙工, | zh_TW |
dc.subject.keyword | Massive MIMO,robust beamforming,beam-time block coding,no CSI feedback,two-stage beamforming,new waveform, | en |
dc.relation.page | 153 | |
dc.identifier.doi | 10.6342/NTU201804190 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2018-10-11 | |
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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