增强型斑马优化算法及其在SDWN功率分配中的应用

李佳佳; 董黎刚; 蒋献

doi:10.11959/j.issn.1000-0801.2025017

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增强型斑马优化算法及其在SDWN功率分配中的应用

研究与开发 | 更新时间：2025-02-07

- 增强型斑马优化算法及其在SDWN功率分配中的应用
- Enhanced zebra optimization algorithm and applications of power allocation in SDWN
- 电信科学 2025年41卷第1期页码：148-163
- 作者机构：
  
  浙江工商大学信息与电子工程学院（萨塞克斯人工智能学院），浙江杭州 310018
- 作者简介：
  
  [ "李佳佳（2000- ），女，浙江工商大学信息与电子工程学院（萨塞克斯人工智能学院）硕士生，主要研究方向为通信与网络。" ]
  [ "董黎刚（1973- ），男，博士，浙江工商大学信息与电子工程学院（萨塞克斯人工智能学院）院长、教授、硕士生导师、博士生导师，中国电子学会高级会员，浙江省计算机学会理事，主要研究方向为新一代网络和分布式系统。" ]
  [ "蒋献（1988- ），男，浙江工商大学信息与电子工程学院（萨塞克斯人工智能学院）实验师，主要研究方向为智慧教育和智慧网络。" ]
- 基金信息：
  
  国家自然科学基金资助项目(62301488);浙江省重点研发计划基金资助项目(2021C01036)
- DOI：10.11959/j.issn.1000-0801.2025017
  中图分类号： TN929.5
- 收稿日期：2024-11-01，
  
  修回日期：2024-12-24，
  
  纸质出版日期：2025-01-20
- 稿件说明：
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李佳佳,董黎刚,蒋献.增强型斑马优化算法及其在SDWN功率分配中的应用[J].电信科学,2025,41(01):148-163.

LI Jiajia,DONG Ligang,JIANG Xian.Enhanced zebra optimization algorithm and applications of power allocation in SDWN[J].Telecommunications Science,2025,41(01):148-163.
李佳佳,董黎刚,蒋献.增强型斑马优化算法及其在SDWN功率分配中的应用[J].电信科学,2025,41(01):148-163. DOI： 10.11959/j.issn.1000-0801.2025017.

LI Jiajia,DONG Ligang,JIANG Xian.Enhanced zebra optimization algorithm and applications of power allocation in SDWN[J].Telecommunications Science,2025,41(01):148-163. DOI： 10.11959/j.issn.1000-0801.2025017.

摘要

为解决多用户通信中共享软件定义无线网络（software defined wireless network，SDWN）资源导致的互扰问题，提出一种增强型斑马优化算法（enhanced zebra optimization algorithm，EZOA），实现保密率最大化的功率分配。在斑马优化算法中引入探索因子和扰动参数，增强其全局搜索和局部开发能力，并改进觅食策略以提升算法多样性。实验结果表明，相较于其他6种成熟算法，EZOA在IEEE CEC 2014基准函数集上，表现出优异的竞争力，并在SDWN功率分配问题中，与其他5种算法相比，EZOA的用户保密率平均提高5.46%，且收敛速度最快。

Abstract

To address the issue of interference caused by shared resources in multi-user communications in software defined wireless network (SDWN)

an enhanced zebra optimization algorithm (EZOA) was proposed to achieve power allocation that maximizes the secrecy rate. By introducing exploration factors and perturbation parameters into the zebra optimization algorithm

EZOA enhanced global search and local exploitation capabilities

while also improving the foraging strategy to increase algorithm diversity. Experimental results demonstrate that EZOA exhibits superior competitiveness compared to six other well-established algorithms on the IEEE CEC 2014 benchmark function set. In the SDWN power allocation problem

EZOA achieves an average improvement of 5.46% in user secrecy rate and the fastest convergence speed compared to five other algorithms.

关键词

Keywords

references

NAROTTAMA B , SHIN S Y . Quantum neural networks for resource allocation in wireless communications [J ] . IEEE Transactions on Wireless Communications , 2022 , 21 ( 2 ): 1103 - 1116 .

POOR H V . Information and inference in the wireless physical layer [J ] . IEEE Wireless Communications , 2012 , 19 ( 1 ): 40 - 47 .

MUKHERJEE A , ALI A FAKOORIAN S , HUANG J , et al . Principles of physical layer security in multiuser wireless networks: a survey [J ] . IEEE Communications Surveys & Tutorials , 2014 , 16 ( 3 ): 1550 - 1573 .

NAZIR M , SABAH A , SARWAR S , et al . Power and resource allocation in wireless communication network [J ] . Wireless Personal Communications , 2021 , 119 ( 4 ): 3529 - 3552 .

JAVED F , KHAN Z A , RIZWAN S , et al . A novel energy-efficient reservation system for edge computing in 6G vehicular ad hoc network [J ] . Sensors , 2023 , 23 ( 13 ): 5817 .

RAI P , SARMA H K D . Reliable data delivery in software-defined networking: a survey [M ] //SARMA H K D, BALAS V E, BHUYAN B, et al, eds. Lecture Notes in Networks and Systems . Singapore : Springer Singapore , 2021 : 3 - 17 .

PHAM Q V , LE L B , CHUNG S H , et al . Mobile edge computing with wireless backhaul: joint task offloading and resource allocation [J ] . IEEE Access , 2019 , 7 : 16444 - 16459 .

TROJOVSKÁ E , DEHGHANI M , TROJOVSKÝ P . Zebra optimization algorithm: a new bio-inspired optimization algorithm for solving optimization algorithm [J ] . IEEE Access , 2022 , 10 : 49445 - 49473 .

PHAM Q V , MIRJALILI S , KUMAR N , et al . Whale optimization algorithm with applications to resource allocation in wireless networks [J ] . IEEE Transactions on Vehicular Technology , 2020 , 69 ( 4 ): 4285 - 4297 .

SHEHAB M , MASHAL I , MOMANI Z , et al . Harris Hawks optimization algorithm: variants and applications [J ] . Archives of Computational Methods in Engineering , 2022 , 29 ( 7 ): 5579 - 5603 .

SEYYEDABBASI A , KIANI F . Sand cat swarm optimization: a nature-inspired algorithm to solve global optimization problems [J ] . Engineering with Computers , 2023 , 39 ( 4 ): 2627 - 2651 .

KENNEDY J , EBERHART R C . A discrete binary version of the particle swarm algorithm [C ] // Proceedings of the 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation . Piscataway : IEEE Press , 1997 : 4104 - 4108 .

MITTAL H , TRIPATHI A , PANDEY A C , et al . Gravitational search algorithm: a comprehensive analysis of recent variants [J ] . Multimedia Tools and Applications , 2021 , 80 ( 5 ): 7581 - 7608 .

SOCHA K , DORIGO M . Ant colony optimization for continuous domains [J ] . European Journal of Operational Research , 2008 , 185 ( 3 ): 1155 - 1173 .

ZHONG C T , LI G , MENG Z . Beluga whale optimization: a novel nature-inspired metaheuristic algorithm [J ] . Knowledge-Based Systems , 2022 , 251 : 109215 .

POCHET Y , WOLSEY L A . Production planning by mixed integer programming [M ] . New York : Springer , 2006 .

GAO W , QU L Z , WANG L . Multi-objective optimization of joint resource allocation problem in multi-beam satellite [C ] // Proceedings of the 2022 IEEE 10th Joint International Information Technology and Artificial Intelligence Conference (ITAIC) . Piscataway : IEEE Press , 2022 : 2331 - 2338 .

COCCO G , DE COLA T , ANGELONE M , et al . Radio resource management optimization of flexible satellite payloads for DVB-S2 systems [J ] . IEEE Transactions on Broadcasting , 2018 , 64 ( 2 ): 266 - 280 .

BRAHMI I , HAMDI M , ZARAI F . Chaotic grey wolf optimization-based resource allocation for vehicle-to-everything communications [J ] . International Journal of Communication Systems , 2021 , 34 ( 13 ): 4908 .

杨青青 , 韩卓廷 , 彭艺 , 等 . 基于多密度流聚类的UAV-NOMA用户分簇与功率分配算法 [J ] . 湖南大学学报(自然科学版) , 2024 , 51 ( 6 ): 86 - 97 .

YANG Q Q , HAN Z T , PENG Y , et al . User clustering and power allocation algorithm for UAV-NOMA based on multi-density stream clustering [J ] . Journal of Hunan University (Natural Sciences) , 2024 , 51 ( 6 ): 86 - 97 .

SAMIDI F S , RADZI N A M , AHMAD W S H M W , et al . 5G new radio: dynamic time division duplex radio resource management approaches [J ] . IEEE Access , 2021 , 9 : 113850 - 113865 .

王朝炜 , 庞明亮 , 王粟 , 等 . 基于决策性能评估的多波束低地球轨道卫星网络资源分配算法 [J ] . 通信学报 , 2024 , 45 ( 7 ): 37 - 47 .

WANG C W , PANG M L , WANG S , et al . Resource allocation algorithm for multi-beam LEO satellite based on decision performance evaluation [J ] . Journal on Communications , 2024 , 45 ( 7 ): 37 - 47 .

彭艺 , 马晓霖 , 杨青青 . 基于自适应细菌觅食优化策略的CR-NOMA功率分配算法 [J ] . 山东大学学报(理学版) , 2024 , 59 ( 1 ): 62 - 71 .

PENG Y , MA X L , YANG Q Q . Power allocation algorithm for CR-NOMA based on adaptive bacterial foraging optimization strategy [J ] . Journal of Shandong University (Natural Science) , 2024 , 59 ( 1 ): 62 - 71 .

LABONI N M , SAFA S J , SHARMIN S , et al . A hyper heuristic algorithm for efficient resource allocation in 5G mobile edge clouds [J ] . IEEE Transactions on Mobile Computing , 2024 , 23 ( 1 ): 29 - 41 .

罗斯宁 , 王化龙 , 李弘宇 , 等 . 基于改进蚁群算法的云计算用户任务调度算法 [J ] . 电信科学 , 2020 , 36 ( 2 ): 95 - 100 .

LUO S N , WANG H L , LI H Y , et al . Improved ant colony algorithm based cloud computing user task scheduling algorithm [J ] . Telecommunications Science , 2020 , 36 ( 2 ): 95 - 100 .

SUN Q S , WU H T , PETROSIAN O . Optimal power allocation based on metaheuristic algorithms in wireless network [J ] . Mathematics , 2022 , 10 ( 18 ): 3336 .

CARO T , IZZO A , Jr REINER R C , et al . The function of zebra stripes [J ] . Nature Communications , 2014 , 5 ( 1 ): 3535 .

STORN R , PRICE K . Differential evolution–a simple and efficient heuristic for global optimization over continuous spaces [J ] . Journal of Global Optimization , 1997 , 11 ( 4 ): 341 - 359 .

YUAN C , ZHAO D , HEIDARI A A , et al . Artemisinin optimization based on malaria therapy: algorithm and applications to medical image segmentation [J ] . Displays , 2024 , 84 : 102740 .

SHENG Z C , TUAN H D , NASIR A A , et al . Power allocation for energy efficiency and secrecy of wireless interference networks [J ] . IEEE Transactions on Wireless Communications , 2018 , 17 ( 6 ): 3737 - 3751 .

LI Y Z , SHENG M , YANG C G , et al . Energy efficiency and spectral efficiency tradeoff in interference-limited wireless networks [J ] . IEEE Communications Letters , 2013 , 17 ( 10 ): 1924 - 1927 .

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