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系統識別號 U0026-0608202021581800
論文名稱(中文) 在小細胞網路具服務品質保證的最佳化聯合傳輸波束成型
論文名稱(英文) Optimal Joint Transmission Beamforming for Small-Cell Networks with QoS Guarantee
校院名稱 成功大學
系所名稱(中) 電腦與通信工程研究所
系所名稱(英) Institute of Computer & Communication
學年度 108
學期 2
出版年 109
研究生(中文) 林楨嵃
研究生(英文) Chen-Yen Lin
學號 Q36074324
學位類別 碩士
語文別 英文
論文頁數 62頁
口試委員 指導教授-劉光浩
口試委員-蔡尚澕
口試委員-古孟霖
口試委員-陳昭羽
口試委員-林家祥
中文關鍵字 聯合傳輸  小細胞網路  波束成型  服務品質  拉格朗日對偶技術  半正定鬆弛技術  伯恩施坦不等式 
英文關鍵字 joint transmission  small-cell networks  beamforming  quality-of-service  Lagrangian duality  semidefinite relaxation  Bernstein-type inequality 
學科別分類
中文摘要 在多細胞網路中,細胞間干擾是棘手並且必須被解決的問題,特別是對於細胞邊緣的用戶而言。透過基地台間合作與聯合傳輸,細胞間干擾可以有效地被降低。傳統上,聯合傳輸技術是被應用在巨細胞網路中,其基地台是位於細胞中央處。而隨著小細胞網路的概念興起,結合聯合傳輸與小細胞網路的研究也備受重視。因此在本篇論文中,我們將聯合傳輸應用於小細胞網路上。為確保用戶服務品質,最佳聯合傳輸波束成型的設計目標為:最小化傳輸能量,同時滿足個體用戶之訊號對干擾及雜訊比的要求。首先我們考慮非強健聯合傳輸波束成型,其基地台在設計波束成型器時,是假設收到的通道狀態資訊即為正確的通道狀態資訊;接下來我們考慮強健聯合傳輸波束成型,其基地台會將通道狀態資訊的誤差納入設計考量。由於對應的最佳化為非凸問題,我們將分別運用拉格朗日對偶技術於非強健聯合傳輸波束成型問題、半正定鬆弛技術與伯恩施坦不等式於強健聯合傳輸波束成型問題,來解決最佳化問題。最後透過模擬結果評估所提出方法的性能,並與現有方法作比較。
英文摘要 In the multicell networks, inter-cell interference (ICI) is a critical problem to solve, especially for the cell-edge User Equipments (UEs). Coordinated Multipoint-Joint Transmission (CoMP-JT) technique has been proposed where by neighboring the Base Stations (BSs) cooperate to reduce ICI. Conventionally, CoMP-JT is applied to the macro-cell networks where only single BS is deployed at each macro cell. As the notion of the small-cell networks becomes emerging, it is of importance to investigate CoMP-JT in the context of small-cell networks where more than one low-power BS are deployed at each macro cell. In this thesis, we consider a combination of small cell deployment and CoMP-JT technique. To guarantee the quality-of-service (QoS), the optimal JT beamforming aims to minimize transmitted power with individual signal-to-interference-plus-noise-ratio (SINR) constraints. We first consider the non-robust JT beamforming, where perfect channel-state-information (CSI) is assumed at the BS side. We then consider the robust JT beamforming, which takes the CSI errors into account. Since both the formulated problems are non-convex in nature, we obtain the optimal solutions by applying Lagrangian duality to the non-robust JT beamforming problem, and Semidefinite Relaxation (SDR) and Bernstein-type inequality to the robust JT beamforming problem, respectively, in order to reduce the high computational complexity. Numerical results are provided to evaluate the performance of the proposed methods in comparison with existing methods.
論文目次 Chinese Abstract i
Abstract ii
Acknowledgement iv
Table of Contents v
List of Figures vii
List of Tables viii
List of Symbols x
List of Acronyms xi
1 Introduction 1
1.1 Thesis Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Thesis Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.3 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.3.1 Coordinated Multipoint-Joint Transmission (CoMP-JT) . . . . 3
1.3.2 Small Cell Networks . . . . . . . . . . . . . . . . . . . . . . . . 4
1.3.3 Quality of Service . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.3.4 Uplink-Downlink Duality . . . . . . . . . . . . . . . . . . . . . 5
1.3.5 Semidefinite Relaxation . . . . . . . . . . . . . . . . . . . . . . 5
1.3.6 Bernstein-Type Inequality . . . . . . . . . . . . . . . . . . . . . 6
2 Related Work 8
3 System Model 10
3.1 Multicell Scenario . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
3.2 Channel Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
3.3 Signal Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
3.3.1 Joint Transmission . . . . . . . . . . . . . . . . . . . . . . . . . 12
3.3.2 Non-Joint Transmission . . . . . . . . . . . . . . . . . . . . . . 13
3.3.3 Association method of JT UE . . . . . . . . . . . . . . . . . . . 14
3.3.4 Association method of non-JT UE . . . . . . . . . . . . . . . . 14
4 Proposed Methods 15
4.1 Beamforming with Perfect CSI . . . . . . . . . . . . . . . . . . . . . . 15
4.1.1 JT Beamforming . . . . . . . . . . . . . . . . . . . . . . . . . . 15
4.1.2 Non-JT Beamforming . . . . . . . . . . . . . . . . . . . . . . . 21
4.1.3 Necessity of Robust Beamforming Design . . . . . . . . . . . . 22
4.2 Beamforming with Imperfect CSI . . . . . . . . . . . . . . . . . . . . . 24
4.2.1 Problem Formulation . . . . . . . . . . . . . . . . . . . . . . . . 25
4.2.2 Problem Reformulation with SDR . . . . . . . . . . . . . . . . . 25
4.2.3 Problem Reformulation with Bernstein-Type Inequality . . . . . 28
5 Results and Discussions 34
5.1 Simulation Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
5.2 Performance Comparison . . . . . . . . . . . . . . . . . . . . . . . . . . 34
5.2.1 Impact of Outage Probability ρ . . . . . . . . . . . . . . . . . . 35
5.2.2 Impact of CSI Error Radius ϵ . . . . . . . . . . . . . . . . . . . 38
5.2.3 Impact of Number of Transmit Antennas Nt . . . . . . . . . . . 42
5.2.4 Impact of SINR target γ . . . . . . . . . . . . . . . . . . . . . . 45
6 Conclusion and Future Work 50
6.1 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
6.2 Future Works . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
References 52
Appendix 54
A.1 Proof of Theorem 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
A.2 Proof of Theorem 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
A.3 Proof of Lemma 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
A.4 ZF Beamforming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
參考文獻 [1] D. Lee, H. Seo, B. Clerckx, E. Hardouin, D. Mazzarese, S. Nagata, and K. Sayana,“Coordinated multipoint transmission and reception in lte-advanced: deployment scenarios and operational challenges,” IEEE Communications Magazine, vol. 50, no. 2, pp. 148–155, 2012.
[2] V. Jungnickel, K. Manolakis, W. Zirwas, B. Panzner, V. Braun, M. Lossow, M. Sternad, R. Apelfröjd, and T. Svensson, “The role of small cells, coordinated multipoint, and massive MIMO in 5G,” IEEE Communications Magazine, vol. 52, no. 5, pp. 44–51, 2014.
[3] C. Yang, S. Han, X. Hou, and A. F. Molisch, “How do we design CoMP to achieve its promised potential?” IEEE Wireless Communications, vol. 20, no. 1, pp. 67–74, 2013.
[4] T. A. Le, S. Nasseri, A. Zarrebini-Esfahani, M. R. Nakhai, and A. Mills, “Powerefficient downlink transmission in multicell networks with limited wireless backhaul,” IEEE Wireless Communications, vol. 18, no. 5, pp. 82–88, 2011.
[5] H. Dahrouj and W. Yu, “Coordinated beamforming for the multicell multi-antenna wireless system,” IEEE Transactions on Wireless Communications, vol. 9, no. 5, pp. 1748–1759, 2010.
[6] Z. Luo, W. Ma, A. M. So, Y. Ye, and S. Zhang, “Semidefinite relaxation of quadratic optimization problems,” IEEE Signal Processing Magazine, vol. 27, no. 3, pp. 20–34, 2010.
[7] I. Bechar, “A bernstein-type inequality for stochastic processes of quadratic forms of gaussian variables,” 2009. [Online]. Available: https://arxiv.org/abs/0909.3595
[8] M. Bengtsson and B. Ottersten, “Optimal downlink beamforming using semidefinite optimization,” in Proc. 37th Annual Allerton Conference on Communication, Control, and Computing, 1999, pp. 987–996.
[9] C. Shen, K.-Y. Wang, T.-H. Chang, Z. Qiu, and C.-Y. Chi, “Worst-case SINR constrained robust coordinated beamforming for multicell wireless systems,” in Proc. IEEE International Conference on Communications (ICC), 2011, pp. 1–5.
[10] K. Wang, T. Chang, W. Ma, A. M. So, and C. Chi, “Probabilistic SINR constrained robust transmit beamforming: A bernstein-type inequality based conservative approach,” in Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2011, pp. 3080–3083.
[11] W. Yu and T. Lan, “Transmitter optimization for the multi-antenna downlink with per-antenna power constraints,” IEEE Transactions on signal processing, vol. 55, no. 6, pp. 2646–2660, 2007.
[12] J. Yang and D. K. Kim, “Multi-cell uplink-downlink beamforming throughput duality based on lagrangian duality with per-base station power constraints,” IEEE Communications Letters, vol. 12, no. 4, pp. 277–279, 2008.
[13] X. Gong, M. Jordan, G. Dartmann, and G. Ascheid, “Max-min beamforming for multicell downlink systems using long-term channel statistics,” in Proc. 2009 IEEE 20th International Symposium on Personal, Indoor and Mobile Radio Communications, 2009, pp. 803–807.
[14] C. Shen, T. Chang, K. Wang, Z. Qiu, and C. Chi, “Distributed robust multicell coordinated beamforming with imperfect CSI: An ADMM approach,” IEEE Transactions on Signal Processing, vol. 60, no. 6, pp. 2988–3003, 2012.
[15] ——, “Chance-constrained robust beamforming for multi-cell coordinated downlink,” in Proc. IEEE Global Communications Conference (GLOBECOM), 2012, pp. 4957–4962.
[16] S. Bassoy, M. Jaber, M. A. Imran, and P. Xiao, “Load aware self-organising usercentric dynamic comp clustering for 5G networks,” IEEE Access, vol. 4, pp. 2895–2906, 2016.
[17] 3GPP, “Evolved Universal Terrestrial Radio Access (E-UTRA); Mobility enhancements in heterogeneous networks,” 3rd Generation Partnership Project (3GPP), 3GPP TR 36.839, Jan. 2013, version 11.1.0. [Online]. Available: https://portal.3gpp.org/desktopmodules/Specifications/SpecificationDetails.aspx?specificationId=2540
[18] M. Grant and S. Boyd, “CVX: Matlab software for disciplined convex programming, version 2.1,” http://cvxr.com/cvx, Mar. 2014.
[19] 3GPP, “Time Division Duplex (TDD) for Downlink-Uplink (DL-UL) interference management and traffic adaptation,” 3rd Generation Partnership Project (3GPP), 3GPP TR 36.828, Jun. 2012, version 11.0.0. [Online]. Available: https://portal.3gpp.org/desktopmodules/Specifications/SpecificationDetails.aspx?specificationId=2507
[20] K.-C. Toh, M. J. Todd, and R. H. Tütüncü, “Sdpt3—a matlab software package for semidefinite programming, version 1.3,” Optimization methods and software, vol. 11, no. 1-4, pp. 545–581, 1999.
[21] A. Wiesel, Y. C. Eldar, and S. Shamai, “Linear precoding via conic optimization for fixed MIMO receivers,” IEEE Transactions on Signal Processing, vol. 54, no. 1, pp. 161–176, 2006.
[22] G. Xu, C. Lin, W. Ma, S. Chen, and C. Chi, “Outage constrained robust hybrid coordinated beamforming for massive MIMO enabled heterogeneous cellular networks,” IEEE Access, vol. 5, pp. 13 601–13 616, 2017.
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