高级搜索

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

异构网络中基于能效优化的D2D资源分配机制

张达敏 张绘娟 闫威 陈忠云 辛梓芸

张达敏, 张绘娟, 闫威, 陈忠云, 辛梓芸. 异构网络中基于能效优化的D2D资源分配机制[J]. 电子与信息学报, 2020, 42(2): 480-487. doi: 10.11999/JEIT190042
引用本文: 张达敏, 张绘娟, 闫威, 陈忠云, 辛梓芸. 异构网络中基于能效优化的D2D资源分配机制[J]. 电子与信息学报, 2020, 42(2): 480-487. doi: 10.11999/JEIT190042
Damin ZHANG, Huijuan ZHANG, Wei YAN, Zhongyun CHEN, Ziyun XIN. D2D Resource Allocation Mechanism Based on Energy EfficiencyOptimization in Heterogeneous Networks[J]. Journal of Electronics & Information Technology, 2020, 42(2): 480-487. doi: 10.11999/JEIT190042
Citation: Damin ZHANG, Huijuan ZHANG, Wei YAN, Zhongyun CHEN, Ziyun XIN. D2D Resource Allocation Mechanism Based on Energy EfficiencyOptimization in Heterogeneous Networks[J]. Journal of Electronics & Information Technology, 2020, 42(2): 480-487. doi: 10.11999/JEIT190042

异构网络中基于能效优化的D2D资源分配机制

doi: 10.11999/JEIT190042
基金项目: 贵州省自然科学基金(黔科合基础[2017]1047号)
详细信息
    作者简介:

    张达敏:男,1967年生,教授,研究方向为认知无线网络、异构网络融合、D2D通信技术、网络拥塞控制

    张绘娟:女,1994年生,硕士生,研究方向为认知无线网络、异构网络融合、D2D通信技术,优化计算

    闫威:男,1993年生,硕士生,研究方向为认知无线网络、异构网络融合、优化计算

    陈忠云:男,1989年生,硕士生,研究方向为认知无线网络、异构网络融合、优化计算

    辛梓芸:女,1994年生,硕士生,研究方向为认知无线网络、异构网络融合、优化计算

    通讯作者:

    张达敏 1203813362@qq.com

  • 中图分类号: TN929.5

D2D Resource Allocation Mechanism Based on Energy EfficiencyOptimization in Heterogeneous Networks

Funds: The Guizhou Province Natural Science Foundation of China ([2017]1047)
  • 摘要:

    针对异构网络中D2D通信复用蜂窝用户频谱时存在的频谱分配问题,该文提出一种基于改进离散鸽群优化(PIO)算法的D2D通信资源分配机制。通过设置信干噪比(SINR)门限值来保证用户的通信服务质量(QoS),采用功率控制算法为用户设置发射功率,使用基于运动权值的二进制离散鸽群优化(MWBPIO)算法为D2D用户进行资源分配,并将D2D通信技术与中继技术进行有效结合,为边缘用户建立D2D中继链路,保证边缘用户的通信质量,最大化系统性能目标。仿真结果表明,该方案有效抑制了异构通信系统中引入D2D用户后导致的干扰问题,提高了边缘用户的通信质量和系统的频谱利用率以及系统的能效。

  • 图  1  异构蜂窝网络通信系统模型

    图  2  yu随迭代次数的变化趋势

    图  3  r(t)随迭代次数的变化趋势

    图  4  算法流程图

    图  5  不同e值下系统总效益值的变化曲线

    图  6  系统总效益值随迭代次数的变化曲线

    图  7  中继链路下D2D边缘用户的SINR累计分布曲线

    图  8  不同D2D通信距离下的系统能效比较

    图  9  不同D2D数目下的系统能效比较

    图  10  不同算法下能效的收敛速度

    表  1  Rosenbrock函数对应不同a值的函数值

    a最优值平均值
    0.100.00820.1029
    0.150.08360.1347
    0.200.00490.1009
    0.250.07360.1342
    0.300.06230.1234
    0.350.06860.1604
    0.400.17540.3342
    0.450.62490.9983
    0.500.00400.0064
    0.550.00090.0002
    0.600.00410.0066
    0.650.04350.1167
    0.700.46450.7743
    0.750.66231.0885
    0.800.77451.2234
    0.850.88421.3354
    0.900.46780.7762
    0.950.54350.9943
    1.000.67350.9984
    下载: 导出CSV

    表  2  Rosenbrock函数对应不同e值的函数值

    e最优值平均值
    1.00.72491.1983
    1.50.02490.4983
    2.00.01990.1234
    2.50.02360.4342
    3.00.67541.1942
    3.50.55491.1009
    4.00.67401.1864
    4.50.56861.0604
    5.00.48361.0347
    下载: 导出CSV

    表  3  系统仿真参数

    参数数值
    小区半径${R_{\rm cell} }$500 m
    宏蜂窝用户数50个
    微蜂窝用户数5个
    D2D用户对数25对
    中继节点数25个
    蜂窝用户最大发射功率24 dBm
    D2D用户最大发射功率15 dBm
    热噪声功率–174 dBm/Hz
    下载: 导出CSV
  • HOANG T D, LE Longbao, and LE-NGOC T. Energy-efficient Resource allocation for D2D communications in cellular networks[J]. IEEE Transactions on Vehicular Technology, 2016, 65(9): 6972–6986. doi: 10.1109/TVT.2015.2482388
    LIANG Le, LI G Y, and XU Wei. Resource allocation for D2D-enabled vehicular communications[J]. IEEE Transactions on Communications, 2017, 65(7): 3186–3197. doi: 10.1109/TCOMM.2017.2699194
    HUANG Jun, XING Congcong, QIAN Yi, et al. Resource allocation for multicell device-to-device communications underlaying 5G networks: A game-theoretic mechanism with incomplete information[J]. IEEE Transactions on Vehicular Technology, 2018, 67(3): 2557–2570. doi: 10.1109/TVT.2017.2765208
    CHEN Yali, AI Bo, NIU Yong, et al. Resource allocation for device-to-device communications underlaying heterogeneous cellular networks using coalitional games[J]. IEEE Transactions on Wireless Communications, 2018, 17(6): 4163–4176. doi: 10.1109/TWC.2018.2821151
    SUN Shijie, KIM K Y, SHIN O S, et al. Device-to-device resource allocation in LTE-advanced networks by hybrid particle swarm optimization and genetic algorithm[J]. Peer-to-Peer Networking and Applications, 2016, 9(5): 945–954. doi: 10.1007/s12083-015-0424-1
    张祖凡, 王立沙, 陈美铃. 基于D2D对分组的TDD系统资源分配算法[J]. 计算机研究与发展, 2017, 54(5): 961–968. doi: 10.7544/issn1000-1239.2017.20151128

    ZHANG Zufan, WANG Lisha, and CHEN Meiling. Resource allocation algorithm based on D2D pairs grouping in TDD system[J]. Journal of Computer Research and Development, 2017, 54(5): 961–968. doi: 10.7544/issn1000-1239.2017.20151128
    KIM T and DONG Miaomiao. An iterative hungarian method to joint relay selection and resource allocation for D2D communications[J]. IEEE Wireless Communications Letters, 2014, 3(6): 625–628. doi: 10.1109/LWC.2014.2338318
    GAO Chuhan, LI Yong, ZHAO Yulei, et al. A two-level game theory approach for joint relay selection and resource allocation in network coding assisted D2D communications[J]. IEEE Transactions on Mobile Computing, 2017, 16(10): 2697–2711. doi: 10.1109/TMC.2016.2642190
    曲桦, 朱正仓, 赵季红, 等. 移动中继协助下终端直通中面向能效的联合中继选择和资源分配方案[J]. 电子与信息学报, 2017, 39(10): 2464–2471. doi: 10.11999/JEIT161359

    QU Hua, ZHU Zhengcang, ZHAO Jihong, et al. Energy-efficient joint relay selection and resource allocation scheme for mobile relay aided device-to-device communication[J]. Journal of Electronics &Information Technology, 2017, 39(10): 2464–2471. doi: 10.11999/JEIT161359
    EBERHART R C and SHI Yuhui. Particle swarm optimization: Developments, applications and resources[C]. 2001 Congress on Evolutionary Computation, Seoul, South Korea, 2001: 81–86. doi: 10.1109/CEC.2001.934374.
    JIANG Yanxiang, LIU Qiang, ZHENG Fuchun, et al. Energy-efficient joint resource allocation and power control for D2D communications[J]. IEEE Transactions on Vehicular Technology, 2016, 65(8): 6119–6127. doi: 10.1109/TVT.2015.2472995
    DUAN Haibin and QIAO Peixin. Pigeon-inspired optimization: A new swarm intelligence optimizer for air robot path planning[J]. International Journal of Intelligent Computing and Cybernetics, 2014, 7(1): 24–37. doi: 10.1108/IJICC-02-2014-0005
    陶国娇, 李智. 带认知因子的交叉鸽群算法[J]. 四川大学学报: 自然科学版, 2018, 55(2): 295–300. doi: 10.3969/j.issn.0490-6756.2018.02.014

    TAO Guojiao and LI Zhi. A crossed pigeon-inspired optimization algorithm with congnitive factor[J]. Journal of Sichuan University:Natural Science Edition, 2018, 55(2): 295–300. doi: 10.3969/j.issn.0490-6756.2018.02.014
    CHEN S M and HSIN W C. Weighted fuzzy interpolative reasoning based on the slopes of fuzzy sets and particle swarm optimization techniques[J]. IEEE Transactions on Cybernetics, 2015, 45(7): 1250–1261. doi: 10.1109/TCYB.2014.2347956
    KENNEDY J and EBERHART R C. A discrete binary version of the particle swarm algorithm[C]. 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation, Orlando, USA, 1997: 4104–4108. doi: 10.1109/ICSMC.1997.637339.
    李志华. D2D通信系统功率控制算法研究[D]. [硕士论文], . 西南交通大学, 2013: 20–22. doi: 10.7666/d.Y2320245.

    LI Zhihua. Research on power control algorithm for device-to-device communication system[D]. [Master dissertation], Southwest Jiaotong University, 2013: 20–22. doi: 10.7666/d.Y2320245.
  • 加载中
图(10) / 表(3)
计量
  • 文章访问数:  3167
  • HTML全文浏览量:  990
  • PDF下载量:  113
  • 被引次数: 0
出版历程
  • 收稿日期:  2019-01-15
  • 修回日期:  2019-08-20
  • 网络出版日期:  2019-09-20
  • 刊出日期:  2020-02-19

目录

    /

    返回文章
    返回