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Author: 戴子堯
Tzu-Yao Tai
Thesis Title: 用於毫米波通訊系統之公平下行資源分配設計
Design of Fair Downlink Resource Allocation for the mmWave Communication System
Advisor: 馮輝文
Huei-Wen Ferng
Committee: 鄭瑞光
林嘉慶
張宏慶
Degree: 碩士
Master
Department: 電資學院 - 資訊工程系
Department of Computer Science and Information Engineering
Thesis Publication Year: 2020
Graduation Academic Year: 108
Language: 中文
Pages: 44
Keywords (in Chinese): 下行排程演算法公平性毫米波第五代行動通訊資源分配
Keywords (in other languages): Downlink Scheduling, Fairness, mmWave, 5G Mobile Communication, Resource Allocation
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  • 隨著行動通訊技術的發展,第五代行動通訊系統已正式上線,使用者裝置的數量也將隨之增長,各種數據的使用者需求將使基地台負擔加重。然而,如何公平、有效率地分配基地台的資源,以應對不同的使用者需求,仍是一個熱的議題。因此,本論文將設計一資源分配演算法,來維持系統效能與提升使用者裝置的公平性。為了能提升使用者裝置間的公平性,我們在所有效益較高的使用者裝置皆配置完成後,將剩餘資源區塊提供給需求較低的使用者裝置。除此之外,為了維護系統總體效能,我們在基地台資源區塊充足時,會優先選擇效益最高之使用者裝置優先進行服務,以維持系統效能。最後,透過數值分析進行比較,其顯示本論文所提出之演算法除了能維持高系統效能,且在公平性上可優於文獻上之相近演算法。


    With the rapid growth of the mobile communication technology, the fifth generation (5G) mobile communication system has been launched. The number of user equipments (UEs) will grow substantially and the requirements of UEs increases the burden of the base station (BS). However, how to allocate the resources of the BS so that different requirements of UEs can be satisfied is still a hot topic. Therefore, this thesis will propose a resource allocation algorithm to maintain system performance and to improve fairness among UEs. When all the profitable UEs have been allocated, the system will allocate the remaining resource blocks (RBs) to UEs with lower demand to improve fairness among UEs. Furthermore, the system will select preferentially the most UE profitable to serve to maintain the overall performance of the system when there are enough RBs at the BS. Finally, the proposed algorithm not only maintains system performance but achieves better fairness than the closely related algorithms in the literature as illustrated by the numerical results.

    論文指導教授推薦書. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . i 考試委員審定書. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii 中文摘要. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii 英文摘要. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv 誌謝. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v 目錄. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vi 表目錄. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . viii 圖目錄. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix 第一章、緒論. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.1 5G 發展技術簡介. . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 5G 網路架構. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.3 5G 資源分配架構. . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 1.3.1 子載波間隔及資源區塊. . . . . . . . . . . . . . . . . . . . . 5 1.3.2 訊框架構. . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 1.4 研究動機. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 1.5 論文章節安排. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 第二章、相關文獻探討. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 2.1 最大速率比與循環排程演算法. . . . . . . . . . . . . . . . . . . . . 10 2.2 基於貪婪演算法的資源分配方法. . . . . . . . . . . . . . . . . . . . 11 2.3 基於動態規劃法的資源分配方法. . . . . . . . . . . . . . . . . . . . 14 第三章、方法之設計與流程. . . . . . . . . . . . . . . . . . . . . . . . . . . 17 3.1 問題定義. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 3.2 方法設計. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 3.2.1 設計概念與發想. . . . . . . . . . . . . . . . . . . . . . . . . 17 3.2.2 效益函數定義. . . . . . . . . . . . . . . . . . . . . . . . . . 18 3.2.3 補償機制之設計. . . . . . . . . . . . . . . . . . . . . . . . . 19 3.2.4 提升優先權機制. . . . . . . . . . . . . . . . . . . . . . . . . 19 3.2.5 區塊錯誤率. . . . . . . . . . . . . . . . . . . . . . . . . . . 20 3.3 方法之複雜度分析. . . . . . . . . . . . . . . . . . . . . . . . . . . 22 3.3.1 時間複雜度. . . . . . . . . . . . . . . . . . . . . . . . . . . 22 3.3.2 空間複雜度. . . . . . . . . . . . . . . . . . . . . . . . . . . 23 第四章、數值結果分析. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 4.1 環境參數設定. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 4.2 所提出方法之數值結果分析與比較. . . . . . . . . . . . . . . . . . 25 4.2.1 吞吐量計算. . . . . . . . . . . . . . . . . . . . . . . . . . . 25 4.2.2 吞吐量之結果分析. . . . . . . . . . . . . . . . . . . . . . . 26 4.2.3 公平性指標之結果分析. . . . . . . . . . . . . . . . . . . . . 28 第五章、結論. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 參考文獻. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

    [1] J. G. Andrews, S. Buzzi, W. Choi, S. V. Hanly, A. Lozano, A. C. Soong, and J. C. Zhang, “What will 5G be?,” IEEE Journal on Selected Areas in Communications, vol. 32, no. 6, pp. 1065–1082, Jun. 2014.
    [2] A. Anand, G. De Veciana, and S. Shakkottai, “Joint scheduling of URLLC and eMBB traffic in 5G wireless networks,” IEEE/ACM Transactions on Networking, vol. 28, no. 2, pp. 477–490, Feb. 2020.
    [3] A. Mukherjee, “Energy efficiency and delay in 5G ultra-reliable low-latency communications system architectures,” IEEE Network, vol. 32, no. 2, pp. 55–61, Apr. 2018.
    [4] C. Sun, C. She, C. Yang, T. Q. Quek, Y. Li, and B. Vucetic, “Optimizing resource allocation in the short blocklength regime for ultra-reliable and lowlatency communications,” IEEE Transactions on Wireless Communications, vol. 18, no. 1, pp. 402–415, Nov. 2018.
    [5] H. H. Yang, G. Geraci, Y. Zhong, and T. Q. Quek, “Packet throughput analysis of static and dynamic TDD in small cell networks,” IEEE Wireless Communications Letters, vol. 6, no. 6, pp. 742–745, Aug. 2017.
    [6] X. Ge, S. Tu, G. Mao, C.-X. Wang, and T. Han, “5G ultra-dense cellular networks,” IEEE Wireless Communications, vol. 23, no. 1, pp. 72–79, Feb. 2016.
    [7] M.-C. Chuang, M. C. Chen, and Y.-H. Lin, “SDN-based resource allocation scheme in ultra-dense OFDMA smallcell networks,” in Proc. International Conference on Advanced Materials for Science and Engineering (ICAMSE), pp. 524–527, Nov. 2016.
    [8] R. Khoder and R. Naja, “Software-defined networking-based resource management in 5G HetNet,” in Proc. IEEE Middle East and North Africa Communications Conference (MENACOMM), pp. 1–6, Apr. 2018.
    [9] G. Wang, G. Feng, W. Tan, S. Qin, R. Wen, and S. Sun, “Resource allocation for network slices in 5G with network resource pricing,” in Proc. IEEE Global Communications Conference, pp. 1–6, Dec. 2017.
    [10] M. Dighriri, A. S. D. Alfoudi, G. M. Lee, T. Baker, and R. Pereira, “Resource allocation scheme in 5G network slices,” in Proc. International Conference on Advanced Information Networking and Applications Workshops (WAINA), pp. 275–280, May. 2018.
    [11] S.-Y. Lien, S.-L. Shieh, Y. Huang, B. Su, Y.-L. Hsu, and H.-Y. Wei, “5G new radio: Waveform, frame structure, multiple access, and initial access,” IEEE Communications Magazine, vol. 55, no. 6, pp. 64–71, Jun. 2017.
    [12] 3GPP, Tech. Specif. Group Radio Access Network - NR; User Equipment (UE) radio transmission and reception (Release 15), 3GPP TS 38.101-1. Dec. 2019.
    [13] S. Agrawal and K. Sharma, “5G millimeter wave (mmWave) communications,” in Proc. International Conference on Computing for Sustainable Global Development (INDIACom), pp. 3630–3634, Mar. 2016.
    [14] T. Lin, J. Cong, Y. Zhu, J. Zhang, and K. B. Letaief, “Hybrid beamforming for millimeter wave systems using the MMSE criterion,” IEEE Transactions on Communications, vol. 67, no. 5, pp. 3693–3708, Jan. 2019.
    [15] 3GPP, Tech. Specif. Group Radio Access Network - NR; NR and NG-RAN Overall Description (Release 15), 3GPP TS 38.300. Jul. 2020.
    [16] A. Karimi, K. I. Pedersen, N. H. Mahmood, J. Steiner, and P. Mogensen, “5G centralized multi-cell scheduling for URLLC: Algorithms and system-level performance,” IEEE Access, vol. 6, pp. 72253–72262, Nov. 2018.
    [17] 3GPP, Tech. Specif. Group Radio Access Network - NR; Physical channels and modulation (Release 15), 3GPP TS 38.211. Sep. 2019.
    [18] “5G 新無線電技術:實體層簡介,” tech. rep., National Instruments, 2018.
    [19] C. Balint and G. Budura, “OFDM-based multi-carrier waveforms performances in 5G,” in Proc. International Symposium on Electronics and Telecommunications (ISETC), pp. 1–4, Nov. 2018.
    [20] F. Zabini, A. Bazzi, B. M. Masini, and R. Verdone, “Optimal performance versus fairness tradeoff for resource allocation in wireless systems,” IEEE Transactions on Wireless Communications, vol. 16, no. 4, pp. 2587–2600, Mar. 2017.
    [21] M. Salah and I. Kostanic, “Performance evaluation of 5G downlink under different beamforming and scheduling methods,” in Proc. IEEE 9th Annual Computing and Communication Workshop and Conference (CCWC), pp. 0778–0782, Jan. 2019.
    [22] G. Femenias, F. Riera-Palou, X. Mestre, and J. J. Olmos, “Downlink scheduling and resource allocation for 5G MIMO-multicarrier: OFDM vs FBMC/OQAM,” IEEE Access, vol. 5, pp. 13770–13786, Jul. 2017.
    [23] R. Knopp and P. A. Humblet, “Information capacity and power control in single-cell multiuser communications,” in Proc. IEEE International Conference on Communications ICC’95, vol. 1, pp. 331–335, Sep. 1995.
    [24] S. Shakkottai and A. L. Stolyar, “Scheduling for multiple flows sharing a timevarying channel: The exponential rule,” Translations of the American Mathematical Society-Series 2, vol. 207, pp. 185–202, Dec. 2000.
    [25] M. Andrews, S. C. Borst, F. Dominique, P. R. Jelenkovic, K. Kumaran, K. Ramakrishnan, and P. A. Whiting, “Dynamic bandwidth allocation algorithms for high-speed data wireless networks,” Bell Labs Technical Journal, vol. 3, no. 3, pp. 30–49, Jul. 1998.
    [26] A. Vora and K.-D. Kang, “Downlink scheduling and resource allocation for 5G MIMO multicarrier systems,” in Proc. IEEE 5G World Forum (5GWF), pp. 174–179, Jul. 2018.
    [27] A. Vora and K.-D. Kang, “Effective 5G wireless downlink scheduling and resource allocation in cyber-physical systems,” Technologies, vol. 6, no. 4, p. 105, Nov. 2018.
    [28] K. D. Rao and T. A. Babu, “Performance analysis of QC-LDPC and Polar Codes for eMBB in 5G systems,” in Proc. International Conference on Electrical, Electronics and Computer Engineering (UPCON), pp. 1–6, Nov. 2019.
    [29] I. Pastushok and N. Boikov, “Investigation of methods for multiplexing eMBB and URLLC streams in a downlink,” in Proc. Wave Electronics and its Application in Information and Telecommunication Systems (WECONF), pp. 1–4, Jun. 2019.
    [30] W. Li and J. Zhang, “Cluster-based resource allocation scheme with QoS guarantee in ultra-dense networks,” IET Communications, vol. 12, no. 7, pp. 861–867, Apr. 2018.
    [31] 3GPP, Tech. Specif. Group Radio Access Network - NR; User Equipment (UE) radio access capabilities (Release 16), 3GPP TS 38.306. Jul. 2020.
    [32] R. Jain, D.-M. Chiu, and W. R. Hawe, A quantitative measure of fairness and discrimination for resource allocation in shared computer system, vol. 38. Sep. 1984.

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