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面向一致覆盖的无蜂窝和传统蜂窝共存网络AP部署优化

姜静 陶莎 王伟 褚宏云 Worakrin Sutthiphan 李春国

姜静, 陶莎, 王伟, 褚宏云, Worakrin Sutthiphan, 李春国. 面向一致覆盖的无蜂窝和传统蜂窝共存网络AP部署优化[J]. 电子与信息学报, 2024, 46(6): 2352-2360. doi: 10.11999/JEIT230627
引用本文: 姜静, 陶莎, 王伟, 褚宏云, Worakrin Sutthiphan, 李春国. 面向一致覆盖的无蜂窝和传统蜂窝共存网络AP部署优化[J]. 电子与信息学报, 2024, 46(6): 2352-2360. doi: 10.11999/JEIT230627
JIANG Jing, TAO Sha, WANG Wei, CHU Hongyun, Worakrin Sutthiphan, LI Chunguo. Consistent-coverage Oriented AP Deployment Optimization in Cell Free and Legacy Coexistence Network[J]. Journal of Electronics & Information Technology, 2024, 46(6): 2352-2360. doi: 10.11999/JEIT230627
Citation: JIANG Jing, TAO Sha, WANG Wei, CHU Hongyun, Worakrin Sutthiphan, LI Chunguo. Consistent-coverage Oriented AP Deployment Optimization in Cell Free and Legacy Coexistence Network[J]. Journal of Electronics & Information Technology, 2024, 46(6): 2352-2360. doi: 10.11999/JEIT230627

面向一致覆盖的无蜂窝和传统蜂窝共存网络AP部署优化

doi: 10.11999/JEIT230627
基金项目: 国家自然科学基金(61871321, 61901370),陕西省国际科技合作项目重点计划(2023-GHZD-37),陕西省重点产业链(2023-ZDLGY-49)
详细信息
    作者简介:

    姜静:女,教授,研究方向为massive MIMO、人工智能及通感算一体化设计

    陶莎:女,硕士生,研究方向为massive MIMO

    王伟:男,高级工程师,研究方向为5G行业专网、能量与信息融合、空天地一体化网络

    褚宏云:女,讲师,研究方向为智能超表面技术

    Worakrin Sutthiphan:男,研究方向为无线网络规划、网络资源配置优化

    李春国:男,教授,研究方向为无线通信与网络安全

    通讯作者:

    陶莎 tsssss@stu.xupt.edu.cn

  • 中图分类号: TN929.5

Consistent-coverage Oriented AP Deployment Optimization in Cell Free and Legacy Coexistence Network

Funds: The National Natural Science Foundation of China (61871321, 61901370), Key Program for International S\&T Cooperation Projects of Shaanxi Province (2023-GHZD-37), Key Industrial Chain Projects of Shaanxi Province (2023-ZDLGY-49)
  • 摘要: 为了解决传统蜂窝网络中用户体验剧烈波动的问题,无蜂窝和传统蜂窝共存网络将大量接入点(Access Point, AP)部署到传统蜂窝网络中,显著改善边缘用户和盲区的覆盖信号质量。因此用户在覆盖区域的任何位置均获得良好、一致的用户体验,即一致覆盖是提升共存网络性能的首要目标。而AP部署方案是共存网络中用户传输速率和覆盖的决定性因素,该文提出了面向一致覆盖的AP部署优化方法。首先根据共存网络的联合传输模型推导得到用户的下行可达速率,然后以最大化平均吞吐量为目标,将AP部署建模为比率和规划问题,并基于分式规划和引入辅助变量将其转换为凸优化问题,进而通过迭代求解AP的最优位置。仿真结果表明,相比传统蜂窝网络,所提方案可显著提高边缘和盲区的平均吞吐量。
  • 图  1  传统蜂窝网络架构、无蜂窝和传统蜂窝共存网络架构、无蜂窝网络架构

    图  2  覆盖范围的栅格示意图

    图  3  不同部署方案下用户平均下行可达速率累积分布

    图  4  不同部署方案下的AP位置分布

    图  5  不同部署方案下的平均吞吐量

    图  6  系统平均吞吐量与AP数目关系

    图  7  系统能量效率与AP数目关系

    1  算法整体流程

     初始化:可行解${{\boldsymbol{X}}^0}$,迭代收敛精度$\delta \ge 0$,迭代次数$t = 0$,最
     大迭代次数${T_{\max }}$
     (1) while $ {R_t} - {R_{t - 1}} \ge \delta $或$t < {T_{\max }}$do
     (2) 对于给定的${{\boldsymbol{X}}_t}$,根据式(14)更新${\lambda _t}$
     (3) 根据式(21)和式(22)更新$ {{\boldsymbol{C}}_k} $和$ {{\boldsymbol{D}}_k} $
     (4) 根据式(23)更新$ {\boldsymbol{E}} $
     (5) 利用单纯形法求解P5,更新${{\boldsymbol{X}}_{t + 1}}$
     (6) 迭代次数$t = t + 1$
     (7) end while
     (8) 将${\boldsymbol{X}}$中最大的前$L$个值并将其置为1,其他置为0,输出${\boldsymbol{X}}$
    下载: 导出CSV

    表  1  部分仿真参数

    参数名称 符号 数值
    蜂窝数/BS数 $M$ 4
    用户数 $K$ 300
    基站天线数 ${N_{\mathrm{t}}}$ 64
    预定义AP位置数 $N$ 500
    栅格数 $S$ 900
    系统带宽(MHz) $B$ 20
    下载: 导出CSV
  • [1] FREDRIK J. Ericsson mobility report[R]. 2022.
    [2] NGUYEN V M and KOUNTOURIS M. Performance limits of network densification[J]. IEEE Journal on Selected Areas in Communications, 2017, 35(6): 1294–1308. doi: 10.1109/JSAC.2017.2687638.
    [3] 章嘉懿. 去蜂窝大规模MIMO系统研究进展与发展趋势[J]. 重庆邮电大学学报:自然科学版, 2019, 31(3): 285–292. doi: 10.3979/j.issn.1673-825X.2019.03.001.

    ZHANG Jiayi. Overview of cell-free massive MIMO system[J]. Journal of Chongqing University of Posts and Telecommunications:Natural Science Edition, 2019, 31(3): 285–292. doi: 10.3979/j.issn.1673-825X.2019.03.001.
    [4] LIU Pei, LUO Kai, CHEN Da, et al. Spectral efficiency analysis of cell-free massive MIMO systems with zero-forcing detector[J]. IEEE Transactions on Wireless Communications, 2020, 19(2): 795–807. doi: 10.1109/TWC.2019.2948841.
    [5] KIM T, KIM H, CHOI S, et al. How will cell-free systems be deployed?[J]. IEEE Communications Magazine, 2022, 60(4): 46–51. doi: 10.1109/MCOM.001.2100533.
    [6] WANG Kehao, LIU Pei, LIU Kezhong, et al. Joint beamforming and phase-shifting design for energy efficiency in RIS-assisted MISO communication with statistical CSI[J]. Physical Communication, 2023, 59: 102080. doi: 10.1016/j.phycom.2023.102080.
    [7] WANG Zhe, ZHANG Jiayi, AI Bo, et al. Uplink performance of cell-free massive MIMO with multi-antenna users over jointly-correlated Rayleigh fading channels[J]. IEEE Transactions on Wireless Communications, 2022, 21(9): 7391–7406. doi: 10.1109/TWC.2022.3158353.
    [8] NGUYEN L D, DUONG T Q, NGO H Q, et al. Energy efficiency in cell-free massive MIMO with zero-forcing precoding design[J]. IEEE Communications Letters, 2017, 21(8): 1871–1874. doi: 10.1109/LCOMM.2017.2694431.
    [9] LIU Heng, ZHANG Jiayi, JIN Shi, et al. Graph coloring based pilot assignment for cell-free massive MIMO systems[J]. IEEE Transactions on Vehicular Technology, 2020, 69(8): 9180–9184. doi: 10.1109/TVT.2020.3000496.
    [10] NAYEBI E and RAO B D. Access point location design in cell-free massive MIMO systems[C]. Proceedings of 2018 52nd Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, USA, 2018: 985–989. doi: 10.1109/ACSSC.2018.8645382.
    [11] ZHU Yihang, CALLEBAUT G, ÇALIK H, et al. Energy efficient access point placement for distributed massive MIMO[J]. Network, 2022, 2(2): 288–310. doi: 10.3390/network2020019.
    [12] GOPAL G R, NAYEBI E, VILLARDI G P, et al. Modified vector quantization for small-cell access point placement with inter-cell interference[J]. IEEE Transactions on Wireless Communications, 2022, 21(8): 6387–6401. doi: 10.1109/TWC.2022.3148996.
    [13] 戴琼海, 付长军, 季向阳. 压缩感知研究[J]. 计算机学报, 2011, 34(3): 425–434. doi: 10.3724/SP.J.1016.2011.00425.

    DAI Qionghai, FU Changjun, and JI Xiangyang. Research on compressed sensing[J]. Chinese Journal of Computers, 2011, 34(3): 425–434. doi: 10.3724/SP.J.1016.2011.00425.
    [14] SHEN Kaiming and YU Wei. Fractional programming for communication systems—Part I: Power control and beamforming[J]. IEEE Transactions on Signal Processing, 2018, 66(10): 2616–2630. doi: 10.1109/TSP.2018.2812733.
    [15] ZHANG Weizhong, ZHANG Lijun, JIN Zhongming, et al. Sparse learning with stochastic composite optimization[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017, 39(6): 1223–1236. doi: 10.1109/TPAMI.2016.2578323.
    [16] NGO H Q, ASHIKHMIN A, YANG Hong, et al. Cell-free massive MIMO versus small cells[J]. IEEE Transactions on Wireless Communications, 2017, 16(3): 1834–1850. doi: 10.1109/TWC.2017.2655515.
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出版历程
  • 收稿日期:  2023-06-25
  • 修回日期:  2023-12-12
  • 网络出版日期:  2023-12-20
  • 刊出日期:  2024-06-30

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