Resource allocation strategies for improved mayfly algorithm in cognitive heterogeneous cellular network

Damin ZHANG; Yi WANG; Chengcheng ZOU; Peiwen ZHAO; Linna ZHANG

doi:10.11959/j.issn.1000-436x.2022115

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Resource allocation strategies for improved mayfly algorithm in cognitive heterogeneous cellular network

Papers | 更新时间：2024-06-06

- Resource allocation strategies for improved mayfly algorithm in cognitive heterogeneous cellular network
- Journal on Communications Vol. 43, Issue 6, Pages: 156-167(2022)
- 作者机构：
  
  1. 贵州大学大数据与信息工程学院，贵州贵阳 550025
  2. 贵州大学机械工程学院，贵州贵阳 550025
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China(62062021);The National Natural Science Foundation of China(61872034);The Science and Technology Foundation of Guizhou Province([2020]1Y254);The Natural Science Foundation of Guizhou Province([2019]1064)
- DOI：10.11959/j.issn.1000-436x.2022115
  CLC： TN929
- Online First：2022-06，
  
  Published：25 June 2022
- 稿件说明：
移动端阅览
Damin ZHANG, Yi WANG, Chengcheng ZOU, et al. Resource allocation strategies for improved mayfly algorithm in cognitive heterogeneous cellular network[J]. Journal on Communications, 2022, 43(6): 156-167.
DOI：

Damin ZHANG, Yi WANG, Chengcheng ZOU, et al. Resource allocation strategies for improved mayfly algorithm in cognitive heterogeneous cellular network[J]. Journal on Communications, 2022, 43(6): 156-167. DOI： 10.11959/j.issn.1000-436x.2022115.

摘要

针对认知异构蜂窝网络中上行链路资源分配的优化问题，提出认知异构蜂窝网络中改进离散蜉蝣算法的资源分配算法。认知异构蜂窝网络模型中，考虑用户层间干扰和带外干扰引入功率控制策略控制发射功率来干扰抑制，基于用户服务质量（QoS）需求和干扰阈值约束，最大化能量效率为优化目标，利用改进离散蜉蝣算法优化求解得出最优分配方案。引入不完全Gamma和Beta分布函数的动态自适应权重、黄金正弦位置更新策略，提升蜉蝣算法的收敛速度和搜索能力。仿真实验表明，基于接收SINR的闭环功率控制动态调整用户端的发射功率，能有效抑制用户间的干扰，GSWBMA 求解资源分配问题具有良好的寻优效率和收敛性能，有效提升系统能量效率和用户传输速率，保证用户QoS需求。

Abstract

Aiming at the optimization of uplink resource allocation in cognitive heterogeneous cellular networks

a resource allocation algorithm based on improved discrete mayfly algorithm was proposed.In the cognitive heterogeneous cellular network model

the power control strategy was introduced to control the interference suppression of transmitted power

and the improved discrete mayfly algorithm was used to optimize and solve the optimal distribution scheme based on the user’s quality of service (QoS) requirements and interference threshold constraints to maximize the energy efficiency (EE).In order to improve the convergence rate and search ability of the mayfly algorithm

the dynamic adaptive weights of incomplete Gamma and Beta distribution functions and the golden sine position updating strategy were introduced.The simulation results show that the closed-loop power control based on SINR can dynamically adjust the transmitting power of users and effectively restrain the interference between users.The GSWBMA has good optimization efficiency and convergence performance to solve the resource allocation problem

effectively improve the energy efficiency of the system and the transmission rate of users

and ensure the QoS requirements of users.

关键词

Keywords

references

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