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H-CRAN網(wǎng)絡下聯(lián)合擁塞控制和資源分配的網(wǎng)絡切片動態(tài)資源調度策略

唐倫 魏延南 譚頎 唐睿 陳前斌

唐倫, 魏延南, 譚頎, 唐睿, 陳前斌. H-CRAN網(wǎng)絡下聯(lián)合擁塞控制和資源分配的網(wǎng)絡切片動態(tài)資源調度策略[J]. 電子與信息學報, 2020, 42(5): 1244-1252. doi: 10.11999/JEIT190439
引用本文: 唐倫, 魏延南, 譚頎, 唐睿, 陳前斌. H-CRAN網(wǎng)絡下聯(lián)合擁塞控制和資源分配的網(wǎng)絡切片動態(tài)資源調度策略[J]. 電子與信息學報, 2020, 42(5): 1244-1252. doi: 10.11999/JEIT190439
Lun TANG, Yannan WEI, Qi TAN, Rui TANG, Qianbin CHEN. Joint Congestion Control and Resource Allocation Dynamic Scheduling Strategy for Network Slices in Heterogeneous Cloud Raido Access Network[J]. Journal of Electronics & Information Technology, 2020, 42(5): 1244-1252. doi: 10.11999/JEIT190439
Citation: Lun TANG, Yannan WEI, Qi TAN, Rui TANG, Qianbin CHEN. Joint Congestion Control and Resource Allocation Dynamic Scheduling Strategy for Network Slices in Heterogeneous Cloud Raido Access Network[J]. Journal of Electronics & Information Technology, 2020, 42(5): 1244-1252. doi: 10.11999/JEIT190439

H-CRAN網(wǎng)絡下聯(lián)合擁塞控制和資源分配的網(wǎng)絡切片動態(tài)資源調度策略

doi: 10.11999/JEIT190439
基金項目: 國家自然科學基金(61571073),重慶市教委科學技術研究項目(KJZD-M201800601)
詳細信息
    作者簡介:

    唐倫:男,1973年生,教授,研究方向為下一代無線通信網(wǎng)絡、異構蜂窩網(wǎng)絡、軟件定義無線網(wǎng)絡等

    魏延南:男,1995年生,碩士生,研究方向為5G網(wǎng)絡切片、虛擬資源分配、隨機優(yōu)化理論

    譚頎:女,1995年生,碩士生,研究方向為5G網(wǎng)絡切片、資源分配、隨機優(yōu)化理論

    陳前斌:男,1967年生,教授,博士生導師,研究方向為個人通信、多媒體信息處理與傳輸、異構蜂窩網(wǎng)絡等

    通訊作者:

    魏延南 weiyannan_cqupt@163.com

  • 中圖分類號: TN929.5

Joint Congestion Control and Resource Allocation Dynamic Scheduling Strategy for Network Slices in Heterogeneous Cloud Raido Access Network

Funds: The National Natural Science Foundation of China (61571073), The Science and Technology Research Program of Chongqing Municipal Education Commission (KJZD-M201800601)
  • 摘要:

    針對異構云無線接入網(wǎng)絡(H-CRAN)網(wǎng)絡下基于網(wǎng)絡切片的在線無線資源動態(tài)優(yōu)化問題,該文通過綜合考慮業(yè)務接入控制、擁塞控制、資源分配和復用,建立一個以最大化網(wǎng)絡平均和吞吐量為目標,受限于基站(BS)發(fā)射功率、系統(tǒng)穩(wěn)定性、不同切片的服務質量(QoS)需求和資源分配等約束的隨機優(yōu)化模型,并進而提出了一種聯(lián)合擁塞控制和資源分配的網(wǎng)絡切片動態(tài)資源調度算法。該算法會在每個資源調度時隙內動態(tài)地為性能需求各異的網(wǎng)絡切片中的用戶分配資源。仿真結果表明,該文算法能在滿足各切片用戶QoS需求和維持網(wǎng)絡穩(wěn)定的基礎上,提升網(wǎng)絡整體吞吐量,并且還可通過調整控制參量的取值實現(xiàn)時延和吞吐量間的動態(tài)平衡。

  • 圖  1  基于網(wǎng)絡切片的H-CRAN下行傳輸場景

    圖  2  平均和吞吐量與控制參量V

    圖  3  平均隊列時延與控制參量V

    圖  4  平均和速率與平均業(yè)務到達率$\lambda $

    圖  5  平均隊列時延與平均業(yè)務到達率$\lambda $

    表  1  H-CRAN網(wǎng)絡下聯(lián)合擁塞控制和資源分配的網(wǎng)絡切片動態(tài)資源調度算法

     (1) 初始化控制參量$V > 0$、各用戶的初始隊列長度${Q_u}(0),\forall u \in {\cal{U}}$和最大時隙數(shù)${T^{\max }}$初始化最大迭代次數(shù)$T_0^{\max }$和允許誤差$\delta $
     (2) for $t = 0,1, ··· ,{T^{\max } } - 1$
     (3) 根據(jù)式(24)分別計算各用戶當前時隙最優(yōu)的流量接入控制策略
     (4) Repeat:
     (5) 令迭代索引$n = 1$,初始化拉格朗日乘子${{\lambda}} $, ${{\eta }}$和${{\mu}} $
     (6) for $s \in {\cal{S}}$
     (7)  計算子載波$s$當前時隙(近似)最優(yōu)的子載波復用、分配和功率分配策略${\alpha _s}^*$, ${{\beta}} _s^*$和${{{P}}_s}^*$,進而更新各用戶剩余的排隊隊列長度
     (8)  若某用戶$u \in {\cal{U}}$已經獲得了足夠的子載波(即其隊列長度為0),則將其從接下來的子載波分配過程中排除。
     (9)  若所有用戶均分配到足夠的子載波,則break
     (10) end for
     (11) 根據(jù)得到的(近似)最優(yōu)子載波復用、分配和功率分配策略${\alpha ^*}$, ${\beta ^*}$和${P^*}$計算拉格朗日函數(shù)${\cal{L}}{\left( {\alpha ,\beta ,P,\lambda ,\eta ,\mu } \right)^{(n)}}$
     (12) Until$\left| { {\cal{L} }{ {\left( {\alpha ,\beta ,P,\lambda ,\eta ,\mu } \right)}^{(n)} } - {\cal{L} }{ {\left( {\alpha ,\beta ,P,\lambda ,\eta ,\mu } \right)}^{(n - 1)} } } \right| \le \delta $ or $n > T_0^{\max }$, then stop Otherwise, 利用次梯度法更新拉格朗日乘子$\lambda $,
    $\eta $和$\mu $,令$n = n + 1$并返回第6步
     (13) 根據(jù)式(17)更新各用戶在下一時隙的業(yè)務隊列長度
     (14) end for
     (15) 輸出:(近似)最優(yōu)流量接入控制、子載波復用和分配以及功率分配策略$r$, $\alpha $, $\beta $和$P$,${Q_u}(t),\forall u \in {\cal{U}},t$。
    下載: 導出CSV
  • Cisco System. Cisco visual networking index: Global mobile data traffic forecast update, 2017–2022 White Paper[R/OL]. https://www.cisco.com/c/en/us/solutions/collateral/service-provider/visual-networking-index-vni/white-paper-c11-738429.html, 2019.
    LI Xin, SAMAKA M, CHAN H A, et al. Network slicing for 5G: challenges and opportunities[J]. IEEE Internet Computing, 2017, 21(5): 20–27. doi: 10.1109/MIC.2017.3481355
    ITU-R. IMT vision-framework and overall objectives of the future development of IMT for 2020 and beyond[EB/OL]. http://www.itu.int/pub/R-REC/en. 2020.
    LI Jian, PENG Mugen, YU Yuling, et al. Energy-efficient joint congestion control and resource optimization in heterogeneous cloud radio access networks[J]. IEEE Transactions on Vehicular Technology, 2016, 65(12): 9873–9887. doi: 10.1109/TVT.2016.2531184
    ZHANG Haijun, WANG Baobao, JIANG Chunxiao, et al. Energy efficient dynamic resource optimization in NOMA system[J]. IEEE Transactions on Wireless Communications, 2018, 17(9): 5671–5683. doi: 10.1109/TWC.2018.2844359
    DANG Tian and PENG Mugen. Delay-aware radio resource allocation optimization for network slicing in fog radio access networks[C]. 2018 IEEE International Conference on Communications Workshops, Kansas City, USA, 2018: 1–6. doi: 10.1109/ICCW.2018.8403717.
    AMANI N, PEDRAM H, TAHERI H, et al. Energy-efficient resource allocation in heterogeneous cloud radio access networks via BBU offloading[J]. IEEE Transactions on Vehicular Technology, 2019, 68(2): 1365–1377. doi: 10.1109/TVT.2018.2882466
    KIM T and CHANG J M. Profitable and energy-efficient resource optimization for heterogeneous cloud-based radio access networks[J]. IEEE Access, 2019, 7: 34719–34737. doi: 10.1109/ACCESS.2019.2904766
    ZHANG Biling, MAO Xingwang, YU J L, et al. Resource allocation for 5G heterogeneous cloud radio access networks with D2D communication: a matching and coalition approach[J]. IEEE Transactions on Vehicular Technology, 2018, 67(7): 5883–5894. doi: 10.1109/TVT.2018.2802900
    唐倫, 魏延南, 馬潤琳, 等. 虛擬化云無線接入網(wǎng)絡下基于在線學習的網(wǎng)絡切片虛擬資源分配算法[J]. 電子與信息學報, 2019, 41(7): 1533–1539. doi: 10.11999/JEIT180771

    TANG Lun, WEI Yannan, MA Runlin, et al. Online learning-based virtual resource allocation for network slicing in virtualized cloud radio access network[J]. Journal of Electronics &Information Technology, 2019, 41(7): 1533–1539. doi: 10.11999/JEIT180771
    MEI Jie, ZHENG Kan, ZHAO Long, et al. A latency and reliability guaranteed resource allocation scheme for LTE V2V communication systems[J]. IEEE Transactions on Wireless Communications, 2018, 17(6): 3850–3860. doi: 10.1109/TWC.2018.2816942
    NEELY M J. Stochastic network optimization with application to communication and queueing systems[J]. Synthesis Lectures on Communication Networks, 2010, 3(1): 15–62. doi: 10.2200/S00271ED1V01Y201006CNT007
    MOKDAD A, AZMI P, MOKARI N, et al. Cross-layer energy efficient resource allocation in PD-NOMA based H-CRANs: implementation via GPU[J]. IEEE Transactions on Mobile Computing, 2019, 18(6): 1246–1259. doi: 10.1109/TMC.2018.2860985
    TANG Liya, ZHANG Xian, XIANG Hongyu, et al. Joint resource allocation and caching placement for network slicing in fog radio access networks[C]. The 18th International Workshop on Signal Processing Advances in Wireless Communications, Sapporo, Japan, 2017: 1–6. doi: 10.1109/SPAWC.2017.8227791.
    LEE Y L, LOO J, CHUAH T C, et al. Dynamic network slicing for multitenant heterogeneous cloud radio access networks[J]. IEEE Transactions on Wireless Communications, 2018, 17(4): 2146–2161. doi: 10.1109/TWC.2017.2789294
    TANG Lun, YANG Xixi, WU Xiaolin, et al. Queue stability-based virtual resource allocation for virtualized wireless networks with self-backhauls[J]. IEEE Access, 2018, 6: 13604–13616. doi: 10.1109/ACCESS.2018.2797088
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出版歷程
  • 收稿日期:  2019-06-17
  • 修回日期:  2020-01-03
  • 網(wǎng)絡出版日期:  2020-01-11
  • 刊出日期:  2020-06-04

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