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无线能量传输支持的设备到设备多播能量协作传输机制

曾闵 罗颖 江虹

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无线能量传输支持的设备到设备多播能量协作传输机制

曾闵, 罗颖, 江虹

Wireless power transfer supported device-to-device multicast energy cooperative transmission scheme

Zeng Min, Luo Ying, Jiang Hong
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  • 能量采集支持的设备到设备多播通信(energy harvesting(EH)-supported D2D(device-to-device)multicast communications, EH-D2MD)传输过程中, 簇头将面临可用能量缺失和高能量消耗需求的矛盾问题. 无线能量协作技术是解决该矛盾问题的一种可行方案. 借助无线能量传输技术, D2D多播簇员传输部分可用能量给簇头, 共同承担内容卸载, 以提升多播簇的传输鲁棒性. 于是, 建立了EH-D2MD通信在复用蜂窝频谱资源前提下的能量协作传输机制; 该机制对频谱复用过程中的能量采集, 协作以及数据传输进行了合理规划, 并以多播簇传输速率最大化为优化目标, 联合优化多域资源(包括: 频谱资源分配、协作时间因子规划、功率控制). 为了探讨EH-D2MD通信场景的极限性能, 提出一种近似下界的凸联合求解方案. 经与暴力搜索算法对比, 提出方案可得到多播传输速率的近似最优下界解; 相比无能量协作机制而言, 建立的能量协作传输机制将多播簇传输速率提升45%以上, 增强了网络传输鲁棒性.
    The cluster heads (CHs) will face the contradiction between the lack of available energy and the demand of high energy consumption in energy harvesting-supported device-to-device multicast communications (EH-D2MD). Wireless power transfer (WPT) technology is a possible way to address the above contradiction. The members of a device-to-device (D2D) multicast cluster can transfer part of their available energy to the CH by WPT and jointly undertake contents unloading. As a result, the transmission robustness of the multicast cluster can be improved. Therefore, a transmission scheme with energy cooperation (EC) is designed on the premise of cellular spectrum reusing. The EC scheme designs elaborately the energy harvesting, energy cooperation and data transmission of the spectrum reusing process. To realize the EC scheme, this work is to maximize the transmission rate of a multicast cluster and give the joint optimal solution of multi-domain resources including spectrum resource allocation, cooperative time factor planning, and power control. The rate maximization problem is a typical non-convex mixed integer non-linear programming (non-convex MINLP) problem. To investigate the performance of EH-D2MD communication scenario, a convex approximate lower-bound algorithm is proposed, which can transfer the non-convex problem into convex MINLP and can give a joint solution. Simulation results show that the proposed algorithm obtains a lower-bound solution of the rate maximization problem in comparison with the exhausted searching method. Furthermore, compared with the scheme without energy cooperation, the established EC transmission scheme can increase the transmission rate of D2MD by more than 45% and enhance the robustness of EH-D2MD.
      通信作者: 罗颖, yluo@swust.edu.cn
    • 基金项目: 国家自然科学基金(批准号: 61771410)、四川省科技厅基础研发计划(批准号: 2021YJ0097)和西南科技大学博士基金项目(批准号: 18zx7144)资助的课题.
      Corresponding author: Luo Ying, yluo@swust.edu.cn
    • Funds: Project supported by the National Natural Science Foundation of China (Grant No. 61771410), the Sichuan Science and Technology Program (Grant No. 2021YJ0097), and the SouthWest University of Science and Technology Research Fund (Grant No. 18zx7144).
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    Kusaladharma S, Tellambura C 2017 IEEE Trans. Green Commun. Netw. 2 87Google Scholar

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    Lim D W, Kang J, Kim H M 2019 IEEE Wireless Commun. Lett. 8 1333Google Scholar

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    Ying L, Peilin H, Runzhou L 2018 IEEE Commun. Lett. 22 1704Google Scholar

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    Bhardwaj A, Agnihotri S 2018 IEEE Wireless Commun. Lett. 7 546Google Scholar

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    胡瑾瑜 2018 博士学位论文 (长沙: 湖南大学)

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    Hu F, Liu X, Shao M, Dan S. Liheng W 2017 IEEE Netw. 31 90Google Scholar

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    Xu J, Zhang R 2015 IEEE Trans. Veh. Technol. 64 2476Google Scholar

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    谢振威, 朱琦 2017 通信学报 38 176Google Scholar

    Xie Z W, Zhu Q 2017 J. on Commun. 38 176Google Scholar

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    Ercan A Ö, Sunay O, Akyildiz I. F 2018 IEEE Trans. Mobile Comput. 17 1680Google Scholar

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    Ni W, Dong X 2015 IEEE Trans. Commun. 63 1457Google Scholar

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    Shin D K, Choi W, Kim D I 2015 IEEE Trans. Commun. 63 4551Google Scholar

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    Ammar A, Reynolds D 2018 IEEE Commun. Lett. 22 2128Google Scholar

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    Zhao D, Cui Y, Tian H, Zhang P 2019 IEEE Access 7 72316Google Scholar

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    Gyawali S, Xu S, Ye F, Hu, Rose Q , Qian Y 2018 Proceedings of IEEE 87th Vehicular Technology Conference Porto, Portugal, July 3–6, 2018 p1

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    Zeng M, Luo Y, Jiang H, Wang Y J 2022 Early Access by IEEE Trans. Wireless Commun.

    [19]

    Mukherjee M, Shu L, Prasad R V, Wang D, Hancke G P 2019 IEEE Commun. Mag. 57 108Google Scholar

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    Papandriopoulos J, Evans J S 2009 IEEE Trans. Inf. Theory 55 3711Google Scholar

    [21]

    Shahbazian A, Fereidunian A, Manshadi S D 2020 IEEE Trans. Smart Grid 11 5009Google Scholar

    [22]

    Girão-Silva R, Martins L, Gomes T, Tipper D, Alashaikh A 2019 Proceedings of IEEE 15th International Conference on the Design of Reliable Communication Networks Coimbra, Portugal, March 19–21, 2019 p29

    [23]

    Boyd S, Boyd S P, Vandenberghe L 2004 Convex Optimization (Cambridgeshire: Cambridge University Press)

    [24]

    Yuille A L, Rangarajan A 2003 Neural Comput. 15 915Google Scholar

    [25]

    Kronqvist J, Bernal D E, Lundell A, Grossmann I E 2019 Optim. Eng. 20 397Google Scholar

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    Fletcher R, Leyffer S 1994 Math. Program. 66 327Google Scholar

    [27]

    Shin D K, Choi W, Kim D I 2015 IEEE Trans. Commun. 63 4551

    [28]

    Chen W, Zhao S, Zhang R, Yang, L 2020 IEEE Internet Things J. 8 501

  • 图 1  单簇头的能量协作内容卸载场景

    Fig. 1.  Energy cooperative content offloading scheme for a single cluster head multicast scenario.

    图 2  CU和EH-D2MD一对一频谱复用下能量协作传输机制

    Fig. 2.  Energy cooperative transmission schemewhen one CU and one EH-D2MD share a spectrum.

    图 3  一个单蜂窝EH-D2MD通信场景示例

    Fig. 3.  A single EH-D2MD communication scenario example.

    图 4  3种算法在多播簇半径分别为50 m (a)和150 m (b)场景下的性能

    Fig. 4.  The performance of the above three algorithms in the scenario where the radius of multicast cluster are 50 m (a) and 150 m (b)

    图 5  EC和without EC算法在簇半径为50 m, 100 m, 150 m场景下的性能对比 (a)多播簇平均传输速率; (b)复用蜂窝链路下行平均传输速率

    Fig. 5.  Performance comparison of EC and Without EC algorithms in scenarios with cluster radius of 50 m, 100 m, and 150 m: (a) The average transmission rate of multicast cluster; (b) the average transmission rate of downlink of cellular user.

    图 6  EC算法在不同多播簇半径场景下参与能量协作的簇员比例分析

    Fig. 6.  The proportion of the cluster members participating in energy cooperation of EC algorithm under scenarios with different multicast cluster radius.

    GBD算法执行步骤:
      初始化. 定义GBD每一次迭代的计数器为t, 并初始化为1; k为主问题不可行后λ的计数次数, 初始化为0; λk = {0}, 设置使算法停止的上下界阈值$\zeta = 0.001$.  步骤1: 在取值区间内给定一组二值变量$\left\{ {\bar {\boldsymbol{X}}, \bar {\boldsymbol{Y}}, \bar {\boldsymbol{Z}}} \right\}$, 根据问题(33)和(34)分别求得此时的连续变量和拉格朗日乘子最优解$\{ {{{\boldsymbol{\alpha}} ^ * }, {{\boldsymbol{\beta}} ^ * }, {{\boldsymbol{\tau}} ^ * }, \hat {\boldsymbol{P}}^* }\}$, μ*; 将此时的目标方程$F( {\bar {\boldsymbol{X}}, \bar {\boldsymbol{Y}}, \bar {\boldsymbol{Z}}, {\boldsymbol{\alpha}} ^ * }, {{\boldsymbol{\beta}} ^ * }, {{\boldsymbol{\tau}} ^ * }, \hat {\boldsymbol{P}}^* )$设为下界U;   步骤2: 若此时给定二值变量的问题(33)可行, 则将μt = μ*, 并求解松弛的master问题(36); 将问题(36)求得的二值变量定义为新的$ \left\{ {\bar {\boldsymbol{X}}, \bar{\boldsymbol{ Y}}, \bar {\boldsymbol{Z}}} \right\} $, 以及目标方程$F( {\bar {\boldsymbol{X}}, \bar {\boldsymbol{Y}}, \bar {\boldsymbol{Z}}, {\boldsymbol{\alpha}} ^ * }, {{\boldsymbol{\beta}} ^ * }, {{\boldsymbol{\tau}} ^ * }, \hat {\boldsymbol{P}}^* )$的上界f0;   步骤3: 根据步骤2求得的二值变量, 求解问题(33), 并得到此时的目标方程$F( {\bar {\boldsymbol{X}}}, \bar {\boldsymbol{Y}}, \bar {\boldsymbol{Z}}, {\boldsymbol{\alpha}} ^ * , {{\boldsymbol{\beta}} ^ * }, {{\boldsymbol{\tau}} ^ * }, \hat {\boldsymbol{P}}^* )$设为新的下界U;   步骤3(a): 若步骤3可行, 判断|f0U| ≤ $\zeta $, 则算法结束; 反之, 根据求解问题(34)得到μ*; 令t = t + 1; μt = μ*; 返回步骤2;   步骤3(b): 若步骤3不可行, 求解松弛问题(35); 令k = k + 1; λk = {$ {\lambda _s} $}; 返回步骤2.
    下载: 导出CSV

    表 1  EH-D2MD通信场景仿真参数设置表[27]

    Table 1.  Simulation parameters setting for EH-D2MD scenario[27].

    变量物理含义参数设置
    I蜂窝用户个数[26]
    JD2MD簇个数[2—6]
    Njj个D2MD簇中簇员个数[2—10]
    T传输时隙1 s
    γ路径衰落指数蜂窝链路: [3—5], D2 D链路: [1.6—1.8]
    BW信道带宽150 kHz
    ρ噪声功率密度–174 dBm/Hz
    h瑞利信道衰落因子正太高斯分布
    η能量转换效率[0.6—0.9]
    $p_B^{{\text{th}}}$基站传输功率阈值43 dBm
    $p_I^{{\text{th}}}$蜂窝用户传输功率阈值24 dBm
    $p_D^{{\text{th}}}$D2D用户传输功率阈值17 dBm
    $R_B^{{\text{th}}}$蜂窝下行传输速率阈值1 bps/Hz
    $R_I^{{\text{th}}}$蜂窝上行传输速率阈值2 bps/Hz
    $R_J^{{\text{th}}}$D2MD多播传输速率阈值4 bps/Hz
    下载: 导出CSV
  • [1]

    Perera T D P, Jayakody D N K, Sharma S K, Symeon C, Jun L 2018 IEEE Commun. Surv. Tutor. 20 264Google Scholar

    [2]

    Kusaladharma S, Tellambura C 2017 IEEE Trans. Green Commun. Netw. 2 87Google Scholar

    [3]

    Lim D W, Kang J, Kim H M 2019 IEEE Wireless Commun. Lett. 8 1333Google Scholar

    [4]

    Ying L, Peilin H, Runzhou L 2018 IEEE Commun. Lett. 22 1704Google Scholar

    [5]

    Bhardwaj A, Agnihotri S 2018 IEEE Wireless Commun. Lett. 7 546Google Scholar

    [6]

    Zhang G, Yang K, Chen H H 2016 IEEE Wireless Commun. Lett. 23 68Google Scholar

    [7]

    Gurakan B, Ozel O, Yang J, Sennur U 2013 IEEE Trans. Commun. 61 4884Google Scholar

    [8]

    胡瑾瑜 2018 博士学位论文 (长沙: 湖南大学)

    Hu J Y 2018 Ph. D. Dissertation (Changsha: Hunan University) (in Chinese)

    [9]

    Hu F, Liu X, Shao M, Dan S. Liheng W 2017 IEEE Netw. 31 90Google Scholar

    [10]

    Xu J, Zhang R 2015 IEEE Trans. Veh. Technol. 64 2476Google Scholar

    [11]

    谢振威, 朱琦 2017 通信学报 38 176Google Scholar

    Xie Z W, Zhu Q 2017 J. on Commun. 38 176Google Scholar

    [12]

    Ercan A Ö, Sunay O, Akyildiz I. F 2018 IEEE Trans. Mobile Comput. 17 1680Google Scholar

    [13]

    Ni W, Dong X 2015 IEEE Trans. Commun. 63 1457Google Scholar

    [14]

    Shin D K, Choi W, Kim D I 2015 IEEE Trans. Commun. 63 4551Google Scholar

    [15]

    Ammar A, Reynolds D 2018 IEEE Commun. Lett. 22 2128Google Scholar

    [16]

    Zhao D, Cui Y, Tian H, Zhang P 2019 IEEE Access 7 72316Google Scholar

    [17]

    Gyawali S, Xu S, Ye F, Hu, Rose Q , Qian Y 2018 Proceedings of IEEE 87th Vehicular Technology Conference Porto, Portugal, July 3–6, 2018 p1

    [18]

    Zeng M, Luo Y, Jiang H, Wang Y J 2022 Early Access by IEEE Trans. Wireless Commun.

    [19]

    Mukherjee M, Shu L, Prasad R V, Wang D, Hancke G P 2019 IEEE Commun. Mag. 57 108Google Scholar

    [20]

    Papandriopoulos J, Evans J S 2009 IEEE Trans. Inf. Theory 55 3711Google Scholar

    [21]

    Shahbazian A, Fereidunian A, Manshadi S D 2020 IEEE Trans. Smart Grid 11 5009Google Scholar

    [22]

    Girão-Silva R, Martins L, Gomes T, Tipper D, Alashaikh A 2019 Proceedings of IEEE 15th International Conference on the Design of Reliable Communication Networks Coimbra, Portugal, March 19–21, 2019 p29

    [23]

    Boyd S, Boyd S P, Vandenberghe L 2004 Convex Optimization (Cambridgeshire: Cambridge University Press)

    [24]

    Yuille A L, Rangarajan A 2003 Neural Comput. 15 915Google Scholar

    [25]

    Kronqvist J, Bernal D E, Lundell A, Grossmann I E 2019 Optim. Eng. 20 397Google Scholar

    [26]

    Fletcher R, Leyffer S 1994 Math. Program. 66 327Google Scholar

    [27]

    Shin D K, Choi W, Kim D I 2015 IEEE Trans. Commun. 63 4551

    [28]

    Chen W, Zhao S, Zhang R, Yang, L 2020 IEEE Internet Things J. 8 501

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出版历程
  • 收稿日期:  2022-02-28
  • 修回日期:  2022-05-07
  • 上网日期:  2022-08-11
  • 刊出日期:  2022-08-20

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