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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 林茂昭 | |
| dc.contributor.author | Yung-Tsao Hsu | en |
| dc.contributor.author | 許永超 | zh_TW |
| dc.date.accessioned | 2021-06-17T08:37:34Z | - |
| dc.date.available | 2022-08-18 | |
| dc.date.copyright | 2019-08-18 | |
| dc.date.issued | 2019 | |
| dc.date.submitted | 2019-08-08 | |
| dc.identifier.citation | [1] B.-H. Chang, “Multiple Access for Transmissions Over Independent Fading Channels,” Master’s thesis, National Taiwan University, 2018.
[2] S. Zhang, S. Liew, and P. Lam, “Hot Topic: Physical Layer Network Coding,” in Proc. International Conference on Mobile Computing and Networking (MobiCom), p. 358–365, 2006. [3] S. P. Lloyd, “Least Squares Quantization in PCM,” IEEE Trans. Inf. Theory, vol. IT-28, pp. 129–136, Mar. 1982. [4] Y. Linde, A. Buzo, and R. M. Gray, “An Algorithm for Vector Quantizer Design,” IEEE Trans. Commun., vol. COM-28, pp. 84–95, Jan. 1980. [5] D. Arthur and S. Vassilvitskii, “K-Means++: The Advantages of Careful Seeding,” in Proc. Symp. Discrete Algorithms, p. 1027–1035, 2007. [6] A. P. Dempster, N. M. Laird, and D. B. Rubin, “Maximum Likelihood from Incomplete Data via the EM Algorithm,” Journal of the Royal Statistical Society. Series B (Methodological), vol. 39, no. 1, pp. 84–95, 1977. [7] T. J. Richardson and R. L. Urbanke, “Multi-Edge Type LDPC Codes,” in Proc. 60th Birthday Workshop Honoring Prof. Bob McEliece, p. 1–36, 2002. [8] D. Wübben and Y. Lang, “Generalized Sum-Product Algorithm for Joint Channel Decoding and Physical-Layer Network Coding in Two-Way Relay Systems,” in IEEE Proc. Global Communications Conference (GLOBECOM), Feb. 2010. [9] F. R. Kschischang, B. J. Frey, and H.-A. Loeliger, “Factor Graphs and the Sum-Product Algorithm,” IEEE Trans. Inf. Theory, vol. 47, pp. 498–519, Feb. 2001. [10] D. Wübben, “Joint Channel Decoding and Physical-Layer Network Coding in Two-Way QPSK Relay Systems by a Generalized Sum-Product Algorithm,” in Proc. 7th International Symposium on Wireless Communication Systems (ISWCS), Sept. 2010. [11] E. Arikan, “Channel Polarization: A Method for Constructing Capacity-Achieving Codes for Symmetric Binary-Input Memoryless Channels,” IEEE Trans. Inf. Theory, vol. 55, pp. 3051–3073, July 2009. [12] I. Tal and A. Vardy, “List Decoding of Polar Codes,” IEEE Trans. Inf. Theory, vol. 61, pp. 2213–2226, May 2015. [13] D. J. C. MacKay, “Fountain Codes,” IEE Proc. Commun., vol. 152, pp. 1062–1068, Dec. 2005. [14] M. Luby, “LT Codes,” in Proc. 43rd Annu. IEEE Symp. Found. Comput. Sci., pp. 271–280, Nov. 2002. [15] A. Shokrollahi, “Raptor Codes,” IEEE Trans. Inf. Theory, vol. 52, pp. 2551–2567, June 2006. [16] S. Jayasooriya, M. Shirvanimoghaddam, L. Ong, and S. J. Johnson, “Analysis and Design of Raptor Codes Using a Multi-Edge Framework,” IEEE Trans. Commun., vol. 65, pp. 5123–5136, Dec. 2017. [17] H.-M. Wang, “A Design of Systematic Physical-Layer Raptor Codes for High Throughput and Low Complexity,” Master’s thesis, National Taiwan University, 2018. [18] S. M. Alamouti, “A Simple Transmit Diversity Technique for Wireless Communications,” IEEE Journal Select. Areas Commun., vol. 16, p. 1451–1458, Oct. 1998. [19] S.-H. Chang, “A Design of 16 ADQAM BICM,” Master’s thesis, National Taiwan University, 2013. [20] L. R. Bahl, J. Cocke, F. Jelinek, and J. Raviv, “Optimal Decoding of Linear Codes for Minimizing Symbol Error Rate,” IEEE Trans. Inf. Theory, vol. IT-20, pp. 284–287, Mar. 1974. [21] P. Hoeher and J. Lodge, ““Turbo DPSK”: Iterative Differential PSK Demodulation and Channel Decoding,” IEEE Trans. Commun., vol. 47, pp. 837–843, June 1999. [22] R.-Y. Wei, “Noncoherent Block-Coded MPSK,” IEEE Trans. Commun., vol. 53, pp. 978–986, June 2005. [23] Y. R. Zheng and C. Xiao, “Improved Models for the Generation of Multiple Uncorrelated Rayleigh Fading Waveforms,” IEEE Commun. Lett., vol. 6, pp. 256–258, June 2002. [24] S. Jayasooriya, M. Shirvanimoghaddam, L. Ong, G. Lechner, and S. J. Johnson, “A New Density Evolution Approximation for LDPC and Multi-Edge Type LDPC Codes,” IEEE Trans. Commun., vol. 64, pp. 4044–4056, Oct. 2016. [25] R. Storn and K. Price, “Differential Evolution—A simple and efficient heuristic for global optimization over continuous spaces,” J. Global Optim., vol. 11, no. 4, pp. 341–359, 1997. [26] H. Chen and Z. Cao, “A Modified PEG Algorithm for Construction of LDPC Codes with Strictly Concentrated Check-Node Degree Distributions,” in Proc. IEEE Wireless Communications and Networking Conference (WCNC 2007), Mar. 2007. [27] H. Xiao and A. H. Banihashemi, “Improved Progressive-Edge-Growth (PEG) Construction of Irregular LDPC Codes,” IEEE Commun. Lett., vol. 8, pp. 715–717, Dec. 2004. [28] M. Franceschini, G. Ferrari, R. Raheli, and A. Curtoni, “Serial Concatenation of LDPC Codes and Differential Modulations,” IEEE J. Sel. Areas Commun., vol. 23, pp. 1758–1768, Sep. 2005. [29] W. Ryan and S. Lin, Channel Codes: Classical and Modern. New York, NY, USA: Cambridge Univ. Press, 2009. [30] S. Kay, Fundamentals of Statistical Signal Processing, Volume I: Estimation Theory. Prentice Hall, 1993. [31] T. J. Richardson and R. Urbanke, Modern Coding Theory. Cambridge, U.K.: Cambridge Univ. Press, 2008. [32] B. Vucetic and J. Yuan, Space-Time Coding. Chichester, U.K.: Wiley, 2003. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/74469 | - |
| dc.description.abstract | 多重接取技術為現今通信系統中不可或缺的一部分。在大多數的系統中，能同時進行資料傳輸的使用者數量往往會因為傳輸資源的特性而有所限制。本篇論文介紹了如何使用分增益多重接取技術，在使用者透過不同且獨立的衰弱通道進行資料傳輸的場景中，利用不同的通道係數來區分不同使用者所傳輸的信號。這樣的多重接取技術允許多個使用者共享相同的傳輸資源，使資源的分配可以更有彈性。
這篇論文也針對多重接取的系統架構，基於分群演算法提出了一種通道盲測的技術。所提出的通道估計方法不需要使用額外的引信信號，因此能得到較高的頻譜使用效率。為了要解決在盲測技術中不可避免的相位不定性且同時保有一定的傳輸可靠度，我們在有使用差分編碼的系統中，針對低密度奇偶檢查碼進行最佳化，藉此降低差分編碼對於傳輸效能的影響。 | zh_TW |
| dc.description.abstract | Multiple access techniques are essential to telecommunication systems nowadays. In this thesis, we investigate a multiple access scheme called gain-division multiple access (GDMA), which allows multiple users to share the same user-specific resource by exploiting distinct channel coefficients when the transmissions are over independent fading channels.
We also propose a blind channel estimation scheme based on the clustering algorithm for GDMA system. The proposed method achieves high spectral efficiency by avoiding the use of pilot signal in channel estimation. To remove the inherent phase ambiguity in estimates derived from blind estimation and also attain an acceptable reliability in transmission, we optimize the outer low-density parity-check (LDPC) codes specifically when an inner differential encoding is cascaded in multi-edge framework and thus relieve the performance degradation introduced by differential encoding. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-17T08:37:34Z (GMT). No. of bitstreams: 1 ntu-108-R06942102-1.pdf: 5837551 bytes, checksum: 6a13b95b520476092dcb7218be2e7a96 (MD5) Previous issue date: 2019 | en |
| dc.description.tableofcontents | 口試委員會審定書 i
致謝 ii 中文摘要 iii ABSTRACT iv CONTENTS v LIST OF FIGURES viii LIST OF TABLES xii Chapter 1 Introduction 1 Chapter 2 Gain-Division Multiple Access 5 2.1 Detection Principle 5 2.2 Bound of Error Rate 11 2.3 Multi-Level Receiver with Error-Correcting Codes 15 2.3.1 Joint Channel Decoding 15 2.3.2 Throughput Performance of Rateless Coding 22 2.4 System Examples 26 2.4.1 Multi-Carrier DS-CDMA 26 2.4.2 Alamouti Space-Time Scheme 30 Chapter 3 Cluster-Based Channel Estimation 34 3.1 K-Means Algorithm 35 3.1.1 The LBG Algorithm 39 3.1.2 K-Means++ Algorithm 42 3.1.3 Gaussian Mixture Model 44 3.2 Derivation of Channel Coefficients 49 3.3 Resolving Phase Ambiguity 56 3.3.1 Differential Encoding 56 3.3.2 Turbo Principle 59 3.3.3 Joint Decoding 60 3.3.4 Noncoherent Block-Coded Modulation 62 3.4 System Impairments 68 3.4.1 Unknown Timing Drifts 68 3.4.2 Doppler Effect 70 Chapter 4 Concatenation of LDPC Codes and Differential Encoding in Multi-Edge Framework 72 4.1 Multi-Edge Type LDPC Codes 73 4.2 Ensemble Behavior 77 4.3 Serial Concatenation of LDPC Codes and Differential Encoding 81 4.3.1 Multi-Edge Representation 82 4.3.2 Decoding Schemes 84 4.3.3 Optimization in Multi-Edge Framework 85 4.3.4 Numerical Results 86 Chapter 5 Conclusion and Future Works 93 BIBLIOGRAPHY 95 | |
| dc.language.iso | en | |
| dc.subject | 多重接取 | zh_TW |
| dc.subject | 衰弱通道 | zh_TW |
| dc.subject | 通道估計 | zh_TW |
| dc.subject | 盲蔽估測 | zh_TW |
| dc.subject | 分群演算法 | zh_TW |
| dc.subject | 低密度奇偶檢查碼 | zh_TW |
| dc.subject | 多邊式低密度奇偶檢查碼 | zh_TW |
| dc.subject | 差分編碼 | zh_TW |
| dc.subject | 密度演化 | zh_TW |
| dc.subject | density evolution | en |
| dc.subject | Multiple access | en |
| dc.subject | differential encoding | en |
| dc.subject | MET-LDPC codes | en |
| dc.subject | LDPC codes | en |
| dc.subject | clustering algorithm | en |
| dc.subject | fading channel | en |
| dc.subject | blind estimation | en |
| dc.subject | channel estimation | en |
| dc.title | 分增益多重接取系統之分析與設計 | zh_TW |
| dc.title | Analysis and Design of Gain-Division Multiple Access | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 107-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 蘇育德,趙啟超,蘇賜麟,呂忠津 | |
| dc.subject.keyword | 多重接取,衰弱通道,通道估計,盲蔽估測,分群演算法,低密度奇偶檢查碼,多邊式低密度奇偶檢查碼,差分編碼,密度演化, | zh_TW |
| dc.subject.keyword | Multiple access,fading channel,channel estimation,blind estimation,clustering algorithm,LDPC codes,MET-LDPC codes,differential encoding,density evolution, | en |
| dc.relation.page | 99 | |
| dc.identifier.doi | 10.6342/NTU201902807 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2019-08-10 | |
| 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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| ntu-108-1.pdf 未授權公開取用 | 5.7 MB | Adobe PDF |
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