基于支撑向量机算法的抗干扰混合波束成形系统

徐磊; 臧月进; 周新耀; 刘观发; 周藜莎

doi:10.11884/HPLPB202133.210235

基于支撑向量机算法的抗干扰混合波束成形系统

doi: 10.11884/HPLPB202133.210235

上海机电工程研究所, 上海210000

详细信息

作者简介:
徐　磊，742426820@qq.com

中图分类号: O451
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- 被引次数: 0
出版历程
- 收稿日期: 2021-06-11
- 修回日期: 2021-11-06
- 网络出版日期: 2021-11-16
- 刊出日期: 2021-12-15

An anti-jamming hybrid beamforming system designed based on support vector machine algorithm

Shanghai Institute of Mechanical and Electrical Engineering, Shanghai 210000, China

摘要

摘要: 针对复杂电磁环境下毫米波阵列的空间辐射干扰抑制问题，设计了一种低成本的自适应波束成形系统。首先建立了复杂电磁环境下通信系统模型，建立目标函数。然后利用机器学习中支持向量机算法将原非凸约束问题转化为二阶锥优化问题，获得理想编码矢量。最后利用梯度追踪算法对理想波束矢量进行稀疏重构，完成抗干扰波束的低复杂度实现。仿真结果表明，提出的波束成形系统能够对干扰作出有效抑制，能提升通信质量。
- 抗干扰 /
- 波束成形 /
- 支撑向量机 /
- 稀疏重构 /
- 梯度追踪
Abstract: A low-cost adaptive beamforming system is designed to solve the space radiation interference problem of millimeter wave communication in complex electromagnetic environment. Firstly, the communication system model in complex electromagnetic environment and the objective function are established. Then, the support vector machine algorithm in machine learning is used to simplify the objective function to obtain the ideal coding vector. Finally, the gradient pursuit algorithm is used to build sparse reconstruction of the ideal beam vector to achieve low-cost anti-jamming beam. Simulation results show that the proposed beamforming system can effectively suppress the interference and improve the communication quality.
- anti-jamming /
- beamforming /
- support vector machine /
- sparse reconstruct /
- gradient pursuit

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图 1 混合波束成形结构框图

Figure 1. Structure of hybrid beamforming system

下载: 全尺寸图片幻灯片

图 2 多链路通信网络

Figure 2. Communication network of muti-link

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图 3 干扰链路数为2时，SINR与发射功率关系

Figure 3. SINR vs total transmitted power, the number of interference is 2

下载: 全尺寸图片幻灯片

图 4 干扰链路数为6时，SINR与发射功率关系

Figure 4. SINR vs total transmitted power, the number of interference is 6

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图 5 运算时间与迭代次数关系

Figure 5. Running time vs number of iteration

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图 6 运算时间与阵列数目关系

Figure 6. Running time vs number of antennas

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表 1 基于GP的波束成形算法

Table 1. GP Algorithm

input $ {{\boldsymbol{w}}_i} $，$ {N_{{\text{RF}}}} $，${ { {{\boldsymbol{A}}} }_Q}$

① ${ { { {\boldsymbol{F} } } }_{ {\text{RF} }(i)} } = \left[ { \cdot } \right];$

② $ {{\boldsymbol{F}}_{{\text{res}}(i)}} = {{\boldsymbol{w}}_i}; $

③ for $ j \leqslant {N_{{\text{RF}}}} $ do

④ ${ { {\boldsymbol{ \varPsi } } } } = { {\boldsymbol{A} } } _Q^*{ {\boldsymbol{F} }_{ {\text{res} }(i)} }$

⑤ $k = \arg \max {(\boldsymbol{\varPsi} {\boldsymbol{\varPsi} ^*})_{l,l} },l = 1,\cdots ,{N_{ {A_Q} } }$

⑥ ${ {\boldsymbol{F} }_{ {\text{RF} }(i)} } = \left[ { { {\boldsymbol{F} }_{ {\text{RF} }(i)} }\left| { { {\boldsymbol{A} }_Q}(:,k)} \right.} \right];$

⑦ ${\boldsymbol{d} } = {{{\boldsymbol{F}}} _{ {\text{RF(} }i{\text{)} } }^{\text{H} }{ {\boldsymbol{F} }_{ {\text{res(} }i{\text{)} } } }ext{)} }$

⑧ $g = \dfrac{ { {\boldsymbol{F} }_{ {\text{res(} }i{\text{)} } }^{\text{H} }{ {\boldsymbol{F} }_{ {\text{RF} }(i)} }{\boldsymbol{d} } } }{ {\left\| { { {\boldsymbol{F} }_{ {\text{RF} }(i)} }{\boldsymbol{d} } } \right\|_{{F} }^2} }$

⑨ ${ {\boldsymbol{v} }_{ {\text{BB} }(i)} } = \left[ { { {\boldsymbol{v} }_{ {\text{BB} }(i)} }\left| 0 \right.} \right] + g*{\boldsymbol{d} }$

⑩ ${ {\boldsymbol{F} }_{ {\text{res} }(i)} } = { {\boldsymbol{F} }_{ {\text{res} }(i)} } - g{ {\boldsymbol{F} }_{ {\text{RF} }(i)} }{\boldsymbol{d} }$

⑪ end for

⑫ ${ {\boldsymbol{v} }_{ {\text{BB} }(i)} } = {P_i}\dfrac{ { { {\boldsymbol{v} }_{ {\text{BB} }(i)} } } }{ { { {\left\| { { {\boldsymbol{F} }_{ {\text{RF} }(i)} }{ {\boldsymbol{v} }_{ {\text{BB} }(i)} } } \right\|}_{{F} } } }}$

end

下载: 导出CSV

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