簡易檢索 / 詳目顯示

研究生: 林佑儒
Lin, You-Ru
論文名稱: 基於可暫存的 D2D 多播網路之資源分配方法
Resource Allocation for Cache-Enabled D2D Multicast Networks
指導教授: 高榮駿
Kao, Jung-Chun
口試委員: 趙禧綠
Chao, Hsi-Lu
楊舜仁
Yang, Shun-Ren
學位類別: 碩士
Master
系所名稱: 電機資訊學院 - 通訊工程研究所
Communications Engineering
論文出版年: 2022
畢業學年度: 110
語文別: 英文
論文頁數: 55
中文關鍵詞: D2D 多播通訊無線資源分配可暫存 D2D
外文關鍵詞: D2D multicastc ommunications, radio resource allocation, ache- enabled D2D
相關次數: 點閱:1下載:0
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報
  • 因為現今日益增長的用戶需求,D2D 多播通訊 (Device-to-Device multicast
    communications) 作為加強傳統 D2D 通訊技術以提升頻譜效率的技術可以滿足
    更大量的使用者需求而備受期待,我們考慮存在多個 Cache-Enabled D2D 裝置
    的環境,每個 D2D 設備都配有有限容量的電池而且可以作為需求者 (demander)
    要求下載檔案同時也能作為幫助者 (helper) 傳送存放在暫存中的檔案給需求
    者。 為了提高在此 Cache-Enabled D2D 網路的頻譜效益,我們提出了一個方法
    並分成三個步驟,第一個步驟的目的是使用最少數量的幫助者來滿足盡可能多
    的需求者的需求,一個幫助者允許同時為多個需求者服務,我們將這個問題轉
    化成最小集合覆蓋問題的變種並使用啟發式演算法來找出最小數量的幫助者集
    合。 在取得幫助者集合後,由於每個幫助者都會服務多個需求者,所以第二個
    步驟是要去決定每幫助者的功率分配,以便在最短時間內完成檔案傳輸,同時
    也要滿足所有需求者的速率要求以及幫助者的功率限制。 第三個步驟目的是通
    過讓多個幫助者共享一個頻譜資源來盡量減少使用的頻譜資源數量,實驗結果
    表明,我們提出的方法可以顯著增加被良好服務的需求者數量 (由幫助者提供服
    務),並提高頻譜效益和幫助者的效益。


    We consider a mobile network in which there exist multiple device-to-device
    (D2D) multicast networks. Each D2D node is powered by finite-capacity battery
    and can serve as a demander (which requests of downloading files) and/or a helper
    (which sends files stored in its cache to demanders). This cache-enabled scenario
    offloads data delivery (which is originally targeted for base stations) to helpers.
    In order to improve spectral efficiency in this cache-enabled scenarios, we de-
    velop a method, which could be divided into helper association, sum multicast
    rate maximization, and channel-sharing scheduling.
    The helper association process aims to satisfy the rate requirements of as many
    demanders as possible by utilizing fewest helpers; a helper is allowed to serve
    multiple demanders. We transfer this helper association problem into a variant
    of the minimum set cover problem and use a heuristic algorithm to find out a
    minimal set of helpers.
    After obtaining a set of helpers, each of which serves multiple demanders, the
    sum multicast rate maximization process decides power allocation for each helper
    in order to finish file transmissions in the shortest time duration while satisfying
    rate requirements of all these demanders and power constraints of the helpers
    themselves.
    The channel sharing scheduling process aims to minimize the number of chan-
    nels in use by letting multiple helpers share the same channel if it can fit. The
    experimental results show that our proposed method can significantly increase
    the number of well-served demanders (that are served by helpers) and improve
    per-channel efficiency and per-helper efficiency.
    Keywords: D2D multicast communications, radio resource allocation, cache-
    enabled D2D

    Abstract i 中文摘要 iii Contents iv List of Figures vi 1 Introduction 1 2 Related Work 5 3 System Model 8 3.1 Cluster model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 3.2 Multi-file model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 4 Problem Formulation 13 5 Our Method 17 5.1 Helper association process . . . . . . . . . . . . . . . . . . . . . . . 17 5.1.1 Awareness of residual battery capacity . . . . . . . . . . . . 18 5.1.2 Transformation to the set cover problem . . . . . . . . . . . 21 iv 5.1.3 Finding the solutions by Modified Algorithm X . . . . . . . 22 5.1.4 Post-processing . . . . . . . . . . . . . . . . . . . . . . . . . 26 5.2 Sum multicast rate maximization process . . . . . . . . . . . . . . . 27 5.3 Channel sharing scheduling process . . . . . . . . . . . . . . . . . . 30 5.3.1 Enhancing phase . . . . . . . . . . . . . . . . . . . . . . . . 31 6 Simulation 33 6.1 Compared algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . 33 6.1.1 The decentralized matching algorithm . . . . . . . . . . . . 34 6.1.2 The matching and coalitional game algorithm . . . . . . . . 34 6.2 Simulation settings . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 6.3 Simulation results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 6.3.1 Total traffic volume received by demanders . . . . . . . . . . 39 6.3.2 Traffic volume per active channel . . . . . . . . . . . . . . . 40 6.3.3 Traffic volume per active helpers . . . . . . . . . . . . . . . 42 6.3.4 Energy consumption per file reception . . . . . . . . . . . . 43 6.3.5 The total number of active helpers . . . . . . . . . . . . . . 44 6.3.6 Computational time . . . . . . . . . . . . . . . . . . . . . . 45 7 Conclusion 47 A Proof of monotonically increasing 48 B Minimum set cover problem 50 Reference 52

    [1] N. Golrezaei, P. Mansourifard, A. F. Molisch, and A. G. Dimakis, “Basestation assisted device-to-device communications for high-throughput wireless video networks,” IEEE Transactions on Wireless Communications, vol. 13,
    no. 7, pp. 3665–3676, 2014. doi: 10.1109/TWC.2014.2316817.
    [2] M. Ji, G. Caire, and A. F. Molisch, “Wireless device-to-device caching networks: Basic principles and system performance,” IEEE Journal on Selected
    Areas in Communications, vol. 34, no. 1, pp. 176–189, 2016. doi: 10.1109/
    JSAC.2015.2452672.
    [3] J. Liu, B. Bai, J. Zhang, K. B. Letaief, and Y. Li, “Joint device caching
    and channel allocation for D2D-assisted wireless content delivery,” in 2018
    IEEE International Conference on Communications (ICC), 2018, pp. 1–6.
    doi: 10.1109/ICC.2018.8422591.
    [4] P. Duan, Y. Jia, L. Liang, J. Rodriguez, K. M. S. Huq, and G. Li, “Spacereserved cooperative caching in 5G heterogeneous networks for industrial
    IoT,” IEEE Transactions on Industrial Informatics, vol. 14, no. 6, pp. 2715–
    2724, 2018. doi: 10.1109/TII.2018.2794615.
    [5] K. Wan, D. Tuninetti, M. Ji, and G. Caire, “A novel cache-aided Fog-RAN
    architecture,” in 2019 IEEE International Symposium on Information Theory (ISIT), 2019, pp. 2977–2981. doi: 10.1109/ISIT.2019.8849605.
    [6] S. A. Taheri and M. Rasti, “Caching placement and offloading in D2Dassisted wireless networks with in-band full duplex,” in 2020 28th Iranian
    Conference on Electrical Engineering (ICEE), 2020, pp. 1–5. doi: 10.1109/
    ICEE50131.2020.9260935.
    [7] Z. Chen, Z. Chen, Y. Jia, and L. Liang, “Residual energy-aware caching
    in mobile D2D cellular network,” in ICC 2019 - 2019 IEEE International
    Conference on Communications (ICC), 2019, pp. 1–6. doi: 10.1109/ICC.
    2019.8762068.
    [8] X. Zhang and J. Wang, “Heterogeneous statistical QoS-driven resource allocation for D2D cluster-caching based 5G multimedia mobile wireless networks,” in 2018 IEEE International Conference on Communications (ICC),
    2018, pp. 1–6. doi: 10.1109/ICC.2018.8422701.
    [9] J. Chuan, L. Wang, and J. Wu, “Belief propagation based distributed content
    delivery scheme in caching-enabled D2D networks,” in ICC 2019 - 2019
    IEEE International Conference on Communications (ICC), 2019, pp. 1–5.
    doi: 10.1109/ICC.2019.8761590.
    [10] B. Chen, C. Yang, and G. Wang, “High-throughput opportunistic cooperative device-to-device communications with caching,” IEEE Transactions on
    Vehicular Technology, vol. 66, no. 8, pp. 7527–7539, 2017. doi: 10.1109/
    TVT.2017.2659701.
    [11] Y. Wang, G. Feng, J. Lin, et al., “Optimal content caching policy considering
    mode selection and user preference under overlay D2D communications,” in
    2018 14th International Conference on Mobile Ad-Hoc and Sensor Networks
    (MSN), 2018, pp. 212–217. doi: 10.1109/MSN.2018.00035.
    [12] Y. Wu, D. Wu, L. Yang, and S. Xu, “Incentive-based cluster formation for
    D2D multicast content sharing,” in 2018 24th Asia-Pacific Conference on
    Communications (APCC), 2018, pp. 125–130. doi: 10.1109/APCC.2018.
    8633512.
    [13] S. Kim, “A new multicasting device-to-device communication control scheme
    for virtualized cellular networks,” Wireless Communications and Mobile Computing, vol. 2019, pp. 1–9, Feb. 2019. doi: 10.1155/2019/3540674.
    [14] X. Zhang and J. Wang, “Heterogeneous statistical QoS-driven power allocation for collaborative D2D caching over edge-computing networks,” in
    2019 IEEE 39th International Conference on Distributed Computing Systems (ICDCS), 2019, pp. 944–953. doi: 10.1109/ICDCS.2019.00098.
    [15] S. Yu, R. Langar, and X. Wang, “A D2D-multicast based computation offloading framework for interactive applications,” in 2016 IEEE Global Communications Conference (GLOBECOM), 2016, pp. 1–6. doi: 10 . 1109 /
    GLOCOM.2016.7841490.
    [16] L. Feng, P. Zhao, F. Zhou, et al., “Resource allocation for 5G D2D multicast
    content sharing in social-aware cellular networks,” IEEE Communications
    Magazine, vol. 56, no. 3, pp. 112–118, 2018. doi: 10 . 1109 / MCOM . 2018 .
    1700667.
    [17] G. Zhang, K. Yang, and H.-H. Chen, “Socially aware cluster formation and
    radio resource allocation in D2D networks,” IEEE Wireless Communications, vol. 23, no. 4, pp. 68–73, 2016. doi: 10.1109/MWC.2016.7553028.
    [18] D. E. Knuth, “Dancing links,” 2000. doi: 10.48550/ARXIV.CS/0011047.
    [Online]. Available: https://arxiv.org/abs/cs/0011047.
    [19] 3GPP, “Evolved Universal Terrestrial Radio Access (E-UTRA); Radio Frequency (RF) requirements for LTE Pico Node B,” 3rd Generation Partnership Project (3GPP), Technical Report (TR) 36.931, Dec. 2009, Version
    9.0.0.
    [20] G. Piro, A. Orsino, C. Campolo, G. Araniti, G. Boggia, and A. Molinaro,
    “D2d in lte vehicular networking: System model and upper bound performance,” in International Congress on Ultra Modern Telecommunications and
    Control Systems and Workshops, Brno, Czech Republic, Oct. 2015, pp. 281–
    286.

    QR CODE