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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
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dc.contributor.advisor | 蘇炫榮 | zh_TW |
dc.contributor.advisor | Hsuan-Jung Su | en |
dc.contributor.author | 邱瀚鋐 | zh_TW |
dc.contributor.author | Han-Hung Chiu | en |
dc.date.accessioned | 2024-09-25T16:22:11Z | - |
dc.date.available | 2024-09-26 | - |
dc.date.copyright | 2024-09-25 | - |
dc.date.issued | 2024 | - |
dc.date.submitted | 2024-08-12 | - |
dc.identifier.citation | [1] E. Basar, M. Di Renzo, J. De Rosny, M. Debbah, M.-S. Alouini, and R. Zhang, “Wireless Communications Through Reconfigurable Intelli- gent Surfaces,” IEEE Access, vol. 7, pp. 116 753–116 773, 2019.
[2] M. D. Renzo, M. Debbah, D. T. P. Huy, A. Zappone, M. Alouini, C. Yuen, V. Sciancalepore, G. C. Alexandropoulos, J. Hoydis, H. Gacanin, J. de Rosny, A. Bounceur, G. Lerosey, and M. Fink, “Smart Radio Environments Empowered by AI Reconfigurable Meta- Surfaces: An Idea Whose Time Has Come,” CoRR, vol. abs/1903.08925, 2019. [Online]. Available: http://arxiv.org/abs/1903.08925 [3] J. Liu, X. Qian, and M. Di Renzo, “Interference Analysis in Recon- figurable Intelligent Surface-Assisted Multiple-Input Multiple-Output Systems,” in ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021, pp. 8067–8071. [4] Q. Zhu, H. Li, R. Liu, M. Li, and Q. Liu, “Hybrid Beamforming and Passive Reflection Design for RIS-Assisted mmWave MIMO Systems,” in 2021 IEEE International Conference on Communications Workshops (ICC Workshops), 2021, pp. 1–6. 51 [5] C. Pradhan, A. Li, L. Song, B. Vucetic, and Y. Li, “Hybrid Precoding Design for Reconfigurable Intelligent Surface Aided mmWave Communi- cation Systems,” IEEE Wireless Communications Letters, vol. 9, no. 7, pp. 1041–1045, 2020. [6] H. Chen, G. Yang, and Y.-C. Liang, “Joint Active and Passive Beam- forming for Reconfigurable Intelligent Surface Enhanced Symbiotic Ra- dio System,” IEEE Wireless Communications Letters, vol. 10, no. 5, pp. 1056–1060, 2021. [7] C. Hu, L. Dai, S. Han, and X. Wang, “Two-Timescale Channel Esti- mation for Reconfigurable Intelligent Surface Aided Wireless Commu- nications,” IEEE Transactions on Communications, vol. 69, no. 11, pp. 7736–7747, 2021. [8] J. He, M. Leinonen, H. Wymeersch, and M. Juntti, “Channel Estimation for RIS-Aided mmWave MIMO Systems,” in GLOBECOM 2020 - 2020 IEEE Global Communications Conference, 2020, pp. 1–6. [9] J. He, H. Wymeersch, and M. Juntti, “Channel Estimation for RIS- Aided mmWave MIMO Systems via Atomic Norm Minimization,” IEEE Transactions on Wireless Communications, vol. 20, no. 9, pp. 5786– 5797, 2021. [10] J. Chen, Y.-C. Liang, H. V. Cheng, and W. Yu, “Channel estimation for reconfigurable intelligent surface aided multi-user MIMO systems,” arXiv preprint arXiv:1912.03619, 2019. 52 [11] G. Zhou, C. Pan, H. Ren, P. Popovski, and A. L. Swindlehurst, “Channel Estimation for RIS-Aided Multiuser Millimeter-Wave Systems,” IEEE Transactions on Signal Processing, vol. 70, pp. 1478–1492, 2022. [12] M. Elad, “Optimized Projections for Compressed Sensing,” IEEE Trans- actions on Signal Processing, vol. 55, no. 12, pp. 5695–5702, 2007. [13] J. M. Duarte-Carvajalino and G. Sapiro, “Learning to Sense Sparse Signals: Simultaneous Sensing Matrix and Sparsifying Dictionary Opti- mization,” IEEE Transactions on Image Processing, vol. 18, no. 7, pp. 1395–1408, 2009. [14] T. E. Bogale, L. B. Le, A. Haghighat, and L. Vandendorpe, “On the Number of RF Chains and Phase Shifters, and Scheduling Design With Hybrid Analog–Digital Beamforming,” IEEE Transactions on Wireless Communications, vol. 15, no. 5, pp. 3311–3326, 2016. [15] P. Zheng, X. Ma, and T. Y. Al-Naffouri, “On the Impact of Mutual Coupling on RIS-Assisted Channel Estimation,” IEEE Wireless Com- munications Letters, vol. 13, no. 5, pp. 1275–1279, 2024. | - |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/95964 | - |
dc.description.abstract | 隨著第六代行動通訊技術及其以上的無線通信服務的發展,可重構智能表面是一種能夠增強系統覆蓋範圍和容量的新技術。可重構智能表面由一個能反射傳輸波的超穎介面組成,並且像相移器一樣調整相位以增加通道容量。與中繼技術不同,可重構智能表面是一種幾乎被動的元件,只能調整相位而不能調整振幅,這是其物理限制。本論文考慮通過結合兩個可重構智能表面元素來設計的新方法,從而放寬毫米波多用戶多輸入單輸出系統中通道估計的限制。
其他文獻討論了具有可重構智能表面物理限制的通道估計優化問題。相比之下,我們將兩個可重構智能表面元素作為一組進行設計。因此,我們獲得了一個等效的半維可重構智能表面矩陣,可以調整相位和振幅。在結合兩個可重構智能表面元素時,我們需要將兩個相鄰的可重構智能表面元素盡可能靠近。我們假設這兩個相鄰的可重構智能表面元素具有相同的通道,模擬結果表明,通道估計誤差的性能優於以往的工作。 | zh_TW |
dc.description.abstract | With the 6G and 6G above wireless communications services, reconfig- urable intelligent surface (RIS) is a novel technique that can enhance the coverage and capacity of the systems. RIS consists of a metasurface that can reflect the transmitted waves and, like a phase shifter, adjust the phase to in- crease channel capacity. Unlike relaying, RIS is a nearly passive element that can only adjust the phase but the amplitude, which is its physical constraint. This thesis considers applying a new way to design RIS by combining two elements of RIS, which relaxes the constraint in channel estimation of the mmWave multi-user MISO system.
Other literature discusses channel estimation optimization problem with RIS physical constraint. In comparison, we take two RIS elements as a group to design it. Due to that, we have an equivalent half-dimension RIS matrix that can adjust the phase and amplitude. When combining two RIS elements, we need to place the two nearby RIS elements as close as possible. We assume the two nearby RIS elements have the same channel, and the simulation results show that the performance of channel estimation error is better than the previous work. | en |
dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2024-09-25T16:22:11Z No. of bitstreams: 0 | en |
dc.description.provenance | Made available in DSpace on 2024-09-25T16:22:11Z (GMT). No. of bitstreams: 0 | en |
dc.description.tableofcontents | Master’s Thesis Acceptance Certificate i
Acknowledgement ii Abstract (Traditional Chinese) iii Abstract (English) iv 1 Introduction 1 1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.3 Overview of the Thesis . . . . . . . . . . . . . . . . . . . . . . 4 1.4 Notations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2 System Model 6 2.1 Cascaded Channel Model . . . . . . . . . . . . . . . . . . . . . 6 2.2 Signal Model . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 3 Problem Formulation and Proposed Algorithm 11 3.1 SMJCE Method . . . . . . . . . . . . . . . . . . . . . . . . . 11 3.2 Grouping RIS elements . . . . . . . . . . . . . . . . . . . . . . 14 4 Simulation Results 30 4.1 Comparison of placement and compensation angle methods . 32 4.2 Simulation with different sub-frames B . . . . . . . . . . . . . 35 4.3 Simulation with different SNR . . . . . . . . . . . . . . . . . 37 4.4 Simulation with different number of Nf path . . . . . . . . . . 39 4.5 Simulation with different coefficients . . . . . . . . . . . . . . 41 4.6 Simulation with the small number of RIS elements . . . . . . . 43 4.7 The impact of the distance between two RIS elements on NMSE 45 4.8 Simulation of sum-rate . . . . . . . . . . . . . . . . . . . . . . 46 5 Conclusions 49 Bibliography 51 | - |
dc.language.iso | en | - |
dc.title | 在可重構智能表面輔助的多用戶多輸入單輸出系統中藉由元件群組放寬設計限制的通道估測法 | zh_TW |
dc.title | Channel Estimation for Reconfigurable-Intelligent-Surface-Assisted Multi-User MISO Systems Using Element Grouping That Relaxes Design Constraints | en |
dc.type | Thesis | - |
dc.date.schoolyear | 112-2 | - |
dc.description.degree | 碩士 | - |
dc.contributor.oralexamcommittee | 林士駿;李佳翰 | zh_TW |
dc.contributor.oralexamcommittee | Shih-Chun Lin;Chia-Han Lee | en |
dc.subject.keyword | 可重構智能表面,毫米波,多用戶聯合通道估計,多輸入單輸出,超穎介面, | zh_TW |
dc.subject.keyword | Reconfigurable intelligent surfaces,Millimeter Wave,multi-user joint channel estimation,MISO,metasurface, | en |
dc.relation.page | 53 | - |
dc.identifier.doi | 10.6342/NTU202403710 | - |
dc.rights.note | 同意授權(限校園內公開) | - |
dc.date.accepted | 2024-08-13 | - |
dc.contributor.author-college | 電機資訊學院 | - |
dc.contributor.author-dept | 電信工程學研究所 | - |
顯示於系所單位: | 電信工程學研究所 |
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