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基于HAGA的D2D-NOMA资源分配优化算法
引用本文:宋勇春,王茜竹,高正念. 基于HAGA的D2D-NOMA资源分配优化算法[J]. 计算机工程, 2022, 48(2): 275-280+290. DOI: 10.19678/j.issn.1000-3428.0060148
作者姓名:宋勇春  王茜竹  高正念
作者单位:1. 重庆邮电大学 电子信息与网络工程研究院, 重庆 400065;2. 新一代信息网络与终端协同创新中心, 重庆 400065
基金项目:重庆市科技重大主题专项重点示范项目(cstc2018jszx-cyztzxX0035);;重庆市教委科学技术研究项目(KJQN201800642);
摘    要:针对无线系统带宽资源有限、基站负载压力大、传输时延长等问题,提出一种基于非正交多址接入技术的D2D系统吞吐量最大化资源分配算法。在不同用户的服务质量约束条件下,建立D2D系统吞吐量最大化资源分配模型。该模型的优化目标是一个混合整数非线性规划问题,将其解耦为信道匹配与功率分配2个子问题并分别进行处理,利用自适应惩罚函数法处理约束条件并提出一种基于爬山策略的自适应遗传算法以对问题进行求解。仿真结果表明,与GA、AGA算法相比,该算法能够有效提高D2D系统的吞吐量,且收敛性能更好。

关 键 词:非正交多址接入  资源分配  爬山策略  自适应遗传算法  惩罚函数法  
收稿时间:2020-11-30
修稿时间:2021-01-12

D2D-NOMA Resource Allocation Optimization Algorithm Based on HAGA
SONG Yongchun,WANG Qianzhu,GAO Zhengnian. D2D-NOMA Resource Allocation Optimization Algorithm Based on HAGA[J]. Computer Engineering, 2022, 48(2): 275-280+290. DOI: 10.19678/j.issn.1000-3428.0060148
Authors:SONG Yongchun  WANG Qianzhu  GAO Zhengnian
Affiliation:1. Institute of Electronic Information and Network Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China;2. Collaborative Innovation Center for Information Communication Technology, Chongqing 400065, China
Abstract:To address the limited bandwidth resources for wireless systems, heavy loading pressure of base stations, and long-distance transmission delay, this paper proposes a resource allocation algorithm to maximize the throughput of Device-to-Device(D2D) systems based on the Non-Orthogonal Multiple Access(NOMA).A resource allocation model is constructed to maximize the throughput of D2D systems based on Quality of Service(QoS) constraints of different users.The optimization problem is simplified into a mixed integer nonlinear programming problem, which is subsequently decoupled into two sub-problems:channel matching and power allocation.On this basis, the constraint conditions are treated with the adaptive penalty function method, and an adaptive genetic algorithm based on Hill-climbing strategy is proposed to solve the problem.Simulation results show that compared with GA and AGA, the proposed algorithm can effectively improve the throughput of D2D systems and provide better convergence performance.
Keywords:Non-Orthogonal Multiple Access(NOMA)  resource allocation  Hill-climbing  Adaptive Genetic Algorithm(AGA)  penalty function method
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