基于Hilbert空间向量赋权的网络选择算法

毛忠阳; 王婷婷; 陆发平; 张治霖; 康家方

doi:10.11999/JEIT230641

基于Hilbert空间向量赋权的网络选择算法

doi: 10.11999/JEIT230641

毛忠阳^{1, 2},
王婷婷^{1, 2, 3, ,},
陆发平^{1, 2},
张治霖^{1, 2},
康家方^{1, 2}

1.
海军航空大学航空通信教研室烟台 264001
2.
海军航空大学信号与信息处理山东省重点实验室烟台 264001
3.
中国人民解放军93786部队张家口 075000

基金项目: 国家基础加强计划重点基础研究项目(61701518)，山东省“泰山学者”建设工程专项经费(TS20081330)，山东省自然科学基金(ZR2023MD045)

详细信息

作者简介:
毛忠阳：男，教授，研究方向为抗干扰通信技术、无线光通信、智能组网

王婷婷：女，硕士生，研究方向为智能组网

陆发平：男，讲师，主要研究方向为现代通信系统、非正弦波通信、信号波形设计、高效调制

张治霖：男，博士生，研究方向为智能组网

康家方：男，副教授，研究方向为抗干扰通信技术、智能组网

通讯作者:
王婷婷　709718966@qq.com

中图分类号: TN92
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出版历程
- 收稿日期: 2023-06-29
- 修回日期: 2023-12-01
- 网络出版日期: 2024-01-28
- 刊出日期: 2024-06-30

Network Selection Algorithm Based on Hilbert Space Vector Weighting

MAO Zhongyang^{1, 2},
WANG Tingting^{1, 2, 3
, ,},
LU Faping^{1, 2},
ZHANG Zhilin^{1, 2},
KANG Jiafang^{1, 2}

1.
Aviation Communication Teaching and Research Section, Naval Aeronautic University, Yantai 264001, China
2.
State Key Laboratory of Signal and Information Processing of Shandong, Naval Aeronautic University, Yantai 264001, China
3.
Unit 93786, PLA, Zhangjiakou 075000, China

Funds: The National Basic Research Program of China (61701518), The Special Fund for Construction Project of “Taishan Scholars” of Shandong Province (TS20081330), Shandong Province Natural Science Foundation (ZR2023MD045)

摘要

摘要: 为了提升海上异构无线网络中移动节点业务完成率和网络资源配置效率，针对现有网络选择算法与业务需求匹配性较差、动态环境下业务完成率不高的问题，该文提出一种基于Hilbert空间向量赋权的网络接入选择算法。该算法采用基于Hilbert空间的网络-业务匹配模型，将网络特征与业务需求映射至同一空间，在同一坐标系内衡量网络是否满足业务需求；同时，采用基于优劣解距离法的预切换网络选择算法，引入网络-业务匹配权重对优劣解距离法标准化矩阵进行修正，确保所选网络与业务需求相匹配，克服传统网络选择中业务需求考虑较少、网络特征与业务需求难以进行统一衡量的问题。此外，采用基于空间距离的网络切换控制算法，将匹配权重、空间距离引入网络切换控制，保证业务传输连续性，提高动态环境下的业务完成率。仿真结果表明，相较于对比算法，该算法的业务平均完成率提高6.81%以上，有效提升了网络的业务传输能力和通畅度，间接实现了网络资源的有效配置。
- 海上异构无线网络 /
- 接入选择 /
- Hilbert空间 /
- 业务需求 /
- 优劣解距离法
Abstract: In order to improve the service completion rate of mobile nodes and the efficiency of network resource allocation in maritime heterogeneous wireless network, a network access selection algorithm based on Hilbert space vector assignment is proposed to address the problems of poor matching between existing network selection algorithms and service demands, and low service completion rate in dynamic environment. The algorithm adopts the network-service matching model based on Hilbert space, maps the network characteristics and service requirements to the same space, and measures whether the network meets the service requirements in the same coordinate system; at the same time, it adopts the pre-switching network selection algorithm based on the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method, and introduces the network-service matching weights to correct the normalization matrix of the distance-to-preferred-solution method, so as to ensure that the selected network matches the service requirements, and to ensure that the network matches the service requirements. This ensures that the selected network matches the service requirements and overcomes the problems of traditional network selection where the service requirements are less considered and the network characteristics and service requirements are difficult to be measured uniformly. In addition, the network switching control algorithm based on spatial distance is adopted, and matching weight and spatial distance are introduced into the network switching control to ensure the continuity of service transmission and improve the service completion rate in the dynamic environment. Simulation results show that compared with the comparison algorithm, the service completion rate of this algorithm is improved by at least 6.81%, which effectively improves the service transmission capacity and smoothness of the network, and indirectly realizes the effective allocation of network resources.
- Maritime heterogeneous wireless network /
- Access selection /
- Hilbert space /
- Business requirement /
- TOPSIS

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图 1 海上异构无线网络架构

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图 2 基于Hilbert空间向量赋权的网络选择模型

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图 3 算法流程图

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图 4 机动站点初始位置图

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图 5 移动节点实时网络参数和业务传输情况对比

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1 基于Hilbert空间向量赋权的网络选择算法

输入：可用网络C；可用网络数据B；待处理业务S；时间T_t；　阈值D
输出：网络选择结果策略集合$\Pi _{m \in M}^C$
1：$\forall {N_m} \in C$，$\forall {{\text{s}}_t} \in S$：$ U\left({s}_{i},{N}_{j}\right)，{s}_{i}\in S,{N}_{j}\in C $
2：for n = 1, 2, ···, T_t
3：　更新当前连接网络N_j ，
4：　for k = 1, 2, ···, m
5：　　计算业务权重向量$ {w_{yw}} $，网络权重向量$w_{wl}^{}$，匹配权重　　　　向量$ \Delta w $
6：　　改进的TOPSIS算法得到最大贴合度网络　　　　 ${N_{r \in m}},{S_{\max }} = {S_r}$
7：　　计算切换度量值${d_{jr}}$
8：　　if ${d_{jr}} < D$ 　　　　　　保持原网络连接
9：　　 else 　　　　　　进行网络切换
10：　 end
11： end
12：end

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表 1 网络属性参数表

网络属性	包延时(ms)	网络速率(kbps)	丢包率(×$1{0^{ - 5}}$)	抖动(ms)
参数范围	20～250	10～1800	5～120	1～25

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表 2 业务参数表

业务类别	交互类业务	会话类业务	流媒体类业务
包延时(ms)	50～270	30～100	200～1000
速率(kbps)	10～100	64～300	400～1000
丢包率(×$1{0^{ - 5}}$)	1～10	1～300	1～100
抖动(ms)	1～10	1～40	1～50
服务时间均值(s)	1	5	8
个数	300	100	50

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表 3 业务传输和切换情况对比

网络选择情况	网络匹配率(%)	业务完成率(%)	业务丢弃率(%)	切换次数	50次业务平均完成率(%)	50次业务平均丢弃率(%)	50次平均切换次数
Dmin	35.00	56.29	4.55	↓0	52.43	11.07	↓0.60
SNRmax	↓27.90	57.43	3.28	1	54.18	8.84	5.74
TOPSIS	32.10	↓52.14	↑12.44	6	↓51.12	↑14.01	3.80
DAHP+S	49.10	58.43	8.96	8	69.35	4.70	8.04
本文算法	↑87.30	↑80.43	↓0.00	↑13	↑76.16	↓2.18	↑11.00

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