請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/77992完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 吳安宇(An-Yeu Wu) | |
| dc.contributor.author | Yu-Hsin Liu | en |
| dc.contributor.author | 劉佑新 | zh_TW |
| dc.date.accessioned | 2021-07-11T14:39:08Z | - |
| dc.date.available | 2022-08-29 | |
| dc.date.copyright | 2017-08-29 | |
| dc.date.issued | 2017 | |
| dc.date.submitted | 2017-06-27 | |
| dc.identifier.citation | [1] Q. Li, H. Niu, A. Papathanassiou, and G. Wu, '5G Network Capacity: Key Elements and Technologies,' IEEE Vehicular Technology Magazine, vol.9, no.1, pp.71-78, Mar. 2014.
[2] D.J. Love, R.W. Heath, Jr., 'Limited feedback unitary precoding for spatial multiplexing systems,' IEEE Trans. Inf. Theory, vol.51, no.8, pp.2967-2976, Aug. 2005. [3] T.S. Rappaport, S. Sun. R. Mayzus, H. Zhao, Y. Azar, K. Wang, G. Wong, J. Schulz, M. Samimi, F. Gutierrez, 'Millimeter wave mobile communications for 5G cellular: It will work!,' IEEE Access, vol.1, pp.335-349, May 2013. [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] ETRI, “Paving the way for 5G”, Nov, 2016, https://5g-ppp.eu/wp-content/uploads/2016/11/06_10-Nov_Session-3_Lee-JunHwan.pdf [6] NTT DOCOMO, “DOCOMO to Conduct 5G Experimental Trials with world-leading Mobile Technology Vendors”, May 2016, https://www.nttdocomo.co.jp/english/info/media_center/pr/2014/0508_00.html. [7] T. Kim, J. Park, J.-Y. Seol, S. Jeong, J. Cho, and W. Roh, 'Tens of Gbps support with mmWave beamforming systems for next generation communications,' in Proc. IEEE Global Telecommun. Conf., Dec. 2013, pp. 3685-369. [8] W. Roh, J.-Y. Seol, J. Park, B. Lee, J. Lee, Y. Kim, J. Cho, K. Cheun, and F. Aryanfar, “Millimeter-wave beamforming as an enabling technology for 5G cellular communications: Theoretical feasibility and prototype results,” IEEE Commun. Mag., vol. 52, no. 2, pp. 106–113, Feb. 2014. [9] O. El Ayach, R. W. Heath, Jr., S. Abu-Surra, S. Rajagopal, and Z. Pi, “The capacity optimality of beam steering in large millimeter wave MIMO systems,” in Proc. IEEE International Workshop Signal Process. Advances Wireless Commun., Jun. 2012, pp. 100–104. [10] O. El Ayach, R. W. Heath, Jr., S. Abu-Surra, S. Rajagopal, and Z. Pi, “Low complexity precoding for large millimeter wave MIMO systems,” in Proc. IEEE International Conf. Commun., Jun. 2012, pp. 3724–3729. [11] O. El Ayach, S. Rajagopal, S. Abu-Surra, Z. Pi, R. W. Heath, Jr., 'Spatially sparse precoding in millimeter wave MIMO systems,' IEEE Trans. Wireless Commun., vol.13, no.3, pp.1499-1513, Mar. 2014. [12] Y.-Y. Lee, C.-H. Wang, and Y.-H. Huang, “A hybrid RF/baseband precoding processor based on parallel-index-selection matrix-inversion-bypass simultaneous orthogonal matching pursuit for millimeter wave MIMO systems,' IEEE Trans. Signal Process., vol.63, no.2, pp.305-317, Jan, 2015. [13] K.-N. Hsu, C.-H. Wang, Y.-Y. Lee, and Y.-H. Huang, “Low-complexity hybrid beamforming and precoding for 2D planar antenna array mmWave systems,” in Proc. IEEE Workshop on Signal Process. Syst. (SiPS), Sep. 2015. pp. 1-6. [14] C. Rusu, R. M´endez-Rial, N. Gonz´alez-Prelcic, and R. W. Heath Jr., “Low Complexity Hybrid Sparse Precoding and Combining in Millimeter Wave MIMO Systems,” in Proc. IEEE Int. Conf. on Commun. (ICC), Jun, 2015. [15] X. Zhang, A. Molisch and S.-Y. Kung 'Variable-phase-shift-based RF-baseband codesign for MIMO antenna selection', IEEE Trans. Signal Process., vol. 53, no. 11, pp.4091 -4103, Oct. 2005 . [16] W.-L. Hung, C.-H. Chen, C.-C. Liao, C.-R. Tsai, and A.-Y.Wu, 'Low- complexity hybrid precoding algorithm based on orthogonal beamforming codebook,' in Proc. IEEE Workshop on Signal Process. Syst. (SiPS), Sep. 2015. pp. 1-5. [17] A. Alkhateeb et al., “Channel Estimation and Hybrid Precoding for Millimeter Wave Cellular Systems,” IEEE J. Sel. Topics Signal Process., vol. 8, no. 5, Oct. 2014, pp. 831–46. [18] A. Alkhateeb, G. Leus, and R. W. Heath, Jr., “Compressed sensing based multi-user millimeter wave systems: How many measurements are needed?,' in Proc. IEEE International Conf. on Acoustics, Speech and Signal Processing (ICExploiting spatial ASSP), Apr. 2015, pp.2909-2913. [19] R. Méndez-Rial, C. Rusu, A. Alkhateeb, N. González-Prelcic, and R. W. Heath Jr., “Channel estimation and hybrid combining for mmwave: Phase shifters or switches?,” in Proc. Inf. Theory Appl. Workshop (ITA), Feb. 2015, pp. 90–97. [20] R. W. Heath Jr, N. Gonzalez-Prelcic, S. Rangan, W. Roh, and A. M. Sayeed, “An overview of signal processing techniques for millimeter wave MIMO systems,” IEEE J. Sel. Top. Signal Process., vol. 10, no. 3, pp. 436–453, 2016. [21] Z. Xiao, T. He, P. Xia, and X. G. Xia, “Hierarchical codebook design for beamforming training in millimeter-wave communication,” IEEE Trans. Wireless Commun., vol. 15, no. 5, pp. 3380–3392, May 2016. [22] J. A. Tropp, A. C. Gilbert, and M. J. Strauss, “Algorithms for simultaneous sparse approximation. Part I: Greedy pursuit,” Signal Process., vol. 86, pp. 572–588, Apr. 2006. [23] Z. Xiao, P. Xia, and X.-G. Xia, “Low complexity hybrid precoding and channel estimation based on hierarchical multi-beam search for millimeter-wave MIMO systems,” arXiv Preprint arXiv:1603.01634, Submitted to IEEE Transactions on Vehicular Technology. [24] L. Dai, X. Gao, J. Quan, S. Han, and C.-L. I, “Near-optimal hybrid analog and digital precoding for downlink mmWave massive MIMO systems,” in Proc. IEEE Int. Conf. Commun. (ICC), Jun. 2015, pp. 1334–1339. [25] X. Yu, J. C. Shen, J. Zhang, and K. Letaief, “Alternating minimization algorithms for hybrid precoding in millimeter wave MIMO systems,” IEEE J. Sel. Topics Signal Process., vol. 10, no. 3, pp. 1–16, Apr. 2016. [26] C. R. Tsai, C. H. Chen, Y. H. Liu, and A. Y. Wu, ' Joint spatially sparse channel estimation for millimeter-wave cellular systems,' in Proc. IEEE GlobalSIP, pp. 3411-3415, Dec. 2016. [27] A. Foucart, H. Rauhut, A Mathematical Introduction to Compressive Sensing. Applied and Numerical Harmonic Analysis. Birkhäuser, 2013. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/77992 | - |
| dc.description.abstract | 下世代通訊系統之技術標準有三大應用方向：增強型移動寬頻（eMBB, Enhance Mobile Broadband）， 超高可靠性與超低延遲通訊（uRLLC, Ultra Reliable & Low Latency Communication）以及巨量物聯網通訊（mMTC, Massive Machine Type Communication）。對於增強型移動寬頻此方向，毫米波頻帶被認為是高速率通訊所需之關鍵技術，而透過大量數量的天線陣列以及預編碼進行波束成型，能克服毫米波通訊環境下的高路徑損耗。然而，常見之預編碼需要通道資訊來進行奇異值分解，而通道資訊之維度正比於天線數量，因此在大量數量的天線陣列架構下，通道資訊變得難以取得，因此分層搜索（Hierarchical Search)為目前廣泛被討論之低複雜度估測通道技術，但分層搜索需要基地台（BS, base station）與使用者端設備(UE, user equipment）之間的訊息回授，以反覆縮小搜索範圍，在高維度的天線陣列下，此訊息回授的次數將會大幅增加，成為通道估測的嚴重成本。因此，本論文將著重於如何降低分層搜索中的訊息回授次數，同時維持估測的通道品質。
本論文中，我們首先採用廣度優先分層搜尋（BFHS, breadth first hierarchical search），相較於傳統的分層搜索，此方法能降低K倍回授次數，同時達到更好的估測通道品質。接著，透過壓縮感知（Compressive Sensing）技術的輔助，我們能基於廣度優先搜尋方法，更進一步減少回授次數，同時維持一定的估測通道品質。基於上述方法得到的通道資訊，我們接著提出低複雜度之混合預編碼器設計方法，相較於目前現有文獻中的方法，此方法可降低 98.44%的複雜度，同時達到99.27%的預編碼器效能。最後，我們將此低複雜度混合預編碼器演算法延伸到子陣列天線架構，相較於目前現有文獻，此方法能夠同時提高預編碼器效能，並降低大量的運算複雜度。 | zh_TW |
| dc.description.abstract | The next generation communication systems (5G) have three directions: enhanced mobile broadband (eMBB), massive machine type communications (mMTC), and ultra-reliable and low latency communications (URLLC). For eMBB, transmitting signals at millimeter-wave (mmWave) frequency bands is an essential technology, and precoding with large-scale antenna array can overcome the huge path-loss in mmWave frequency bands. However, precoding needs singular value decomposition (SVD) on the high-dimensional channel matrix, which is hard to acquire under large antenna array. Therefore, hierarchical search is proposed to estimate the mmWave channel with low-complexity. However, hierarchical search needs the feedback between BS and UE to refine the search range. Under large antenna array, the number of feedbacks will become unbearable. Therefore, in this thesis, we focus on how to reduce the number of feedbacks of hierarchical search, while estimating the mmWave channel with satisfying quality.
In this thesis, we first introduce BFHS to reduce the number of feedback by K times, while estimating channel with better quality. Next, assisted by compressive sensing (CS), we can further reduce the number of feedbacks. Based on the estimated channel state information (CSI), we further propose a low-complexity hybrid precoding algorithm. It can reduce 98.44% complexity, while achieving 99.27% performance of state-of-the-art hybrid precoding algorithms. Finally, we extend the proposed low-complexity hybrid precoding algorithm to sub-array structure, which can outperform other related works with much less computing time. | en |
| dc.description.provenance | Made available in DSpace on 2021-07-11T14:39:08Z (GMT). No. of bitstreams: 1 ntu-106-R04943049-1.pdf: 4042697 bytes, checksum: adb3ff4ea4033b3fa09cfd8ef92e69df (MD5) Previous issue date: 2017 | en |
| dc.description.tableofcontents | 致謝 v
摘要 vii Abstract ix List of Tables xv Chapter1 Introduction 1 1.1 Millimeter-Wave Communication 2 1.2 Beamforming Transceiver Structures 5 1.3 Channel State Information 8 1.4 Motivations and Contributions 9 1.5 Thesis Organization 11 Chapter2 Review of Channel Estimation Algorithm and Hybrid Precoder Design 12 2.1 Millimeter-Wave System and Channel Model 12 2.1.1 System Model 12 2.1.2 Channel Model 14 2.2 Hierarchical Channel Estimation 16 2.3 SVD-based Hybrid Precoding 20 2.3.1 Full-digital Structure 20 2.3.2 Hybrid Structure 21 2.4 Sparse Optimization Problem 22 2.4.1 Problem Formulation 22 2.4.2 Sparse Optimization Algorithm 23 2.5 Summary 25 Chapter3 Compressing Sensing Assisted Hierarchical Search 26 3.1 Problem of Traditional Hierarchical Search 26 3.2 Breadth First Hierarchical Search 26 3.3 CS-assisted Breadth First Hierarchical Search 27 3.4 Search Depth and Sparse Recovery 32 3.5 Simulation Results 33 3.5.1 Spectral Efficiency 33 3.5.2 Sweeping Overhead 36 3.5.3 The Impact of K 37 3.5.4 CS-BFHS with Training Beams at Earlier Layer 38 3.5.5 CS-BFHS-TBE and Pure CS 42 Chapter4 Low-Complexity Hybrid Precoding Based on Quantized Dictionaries 44 4.1 Low-Correlation Property of Quantized Candidate Beamforming Matrix 44 4.2 Low-Complexity Hybrid Precoding 46 4.3 Simulation Results 49 4.3.1 Spectral Efficiency 50 4.3.2 Analysis of Complexity 51 Chapter5 Hybrid Precoding with Sub-array structure 54 5.1 Fully-connected and Sub-array Structure 54 5.2 Algorithms on Hybrid Precoding with Sub-array Structure 56 5.2.1 Successive Interference Cancellation 56 5.2.2 Semidefinite Relaxation Alternating Minimization (SDR-AltMin) 57 5.3 Low-complexity Hybrid Precoding with Sub-array Structure 59 5.4 Simulation Results 64 5.4.1 Spectral Efficiency 65 5.4.2 Analysis of Complexity 65 Chapter6 Conclusions 66 6.1 Contributions 66 6.2 Future Works 68 Reference 69 | |
| dc.language.iso | zh-TW | |
| dc.subject | 通道估測 | zh_TW |
| dc.subject | 混合預編碼器 | zh_TW |
| dc.subject | 壓縮感知 | zh_TW |
| dc.subject | 毫米波 | zh_TW |
| dc.subject | Hybrid precoding | en |
| dc.subject | Millimeter-wave | en |
| dc.subject | Channel estimation | en |
| dc.subject | Compressive sensing | en |
| dc.title | 適用於毫米波多輸入多輸出通訊系統下以壓縮感知輔助之分層波束搜索與低複雜度預編碼器演算法設計 | zh_TW |
| dc.title | Compressive Sensing (CS)-Assisted Hierarchical Beam Search and Low-Complexity Hybrid Precoding for Millimeter-Wave MIMO Communication Systems | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 105-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 吳仁銘(Jen-Ming Wu),陳儒雅(Ju-Ya Chen),伍紹勳(Shao-Hsun Wu),曹恆偉(Hen-Wei Tsao) | |
| dc.subject.keyword | 毫米波,通道估測,壓縮感知,混合預編碼器, | zh_TW |
| dc.subject.keyword | Millimeter-wave,Channel estimation,Compressive sensing,Hybrid precoding, | en |
| dc.relation.page | 72 | |
| dc.identifier.doi | 10.6342/NTU201701069 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2017-06-27 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 電子工程學研究所 | zh_TW |
| 顯示於系所單位： | 電子工程學研究所 | |
文件中的檔案：
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-106-R04943049-1.pdf 未授權公開取用 | 3.95 MB | Adobe PDF |
系統中的文件，除了特別指名其著作權條款之外，均受到著作權保護，並且保留所有的權利。