基于遗传算法的混叠式非正交多址接入方法  

Hybrid non-orthogonal multiple access method based on genetic algorithm

作　　者：闫珍珍 李波[1] 杨懋[1] 闫中江[1] YAN Zhenzhen;LI Bo;YANG Mao;YAN Zhongjiang(School of Electronics and Information, Northwestern Polytechnical University, Xi’an 710072, China)

机构地区：[1]西北工业大学电子信息学院,陕西西安710072

出　　处：《系统工程与电子技术》2021年第3期832-838,共7页Systems Engineering and Electronics

基　　金：国家自然科学基金(61871322,61771392,61771390,61501373,61271279);国家科技重大专项(2016ZX03001018-004);航空电子系统综合技术重点实验室和航空科学基金(20185553035,201955053002)资助课题。

摘　　要：为了提高稀疏码多址接入(sparse code multiple access,SCMA)系统的资源利用率,提出一种基于遗传算法的混叠式非正交多址接入(non-orthogonal multiple access,NOMA)方法。该方法利用NOMA的过载特性,允许相同的资源单元同时混叠承载调度接入和随机竞争接入业务,从而实现了两种接入方式的细粒度融合。进而,设计基于遗传算法的混叠式NOMA资源分配算法,将两种接入方式的总容量作为优化目标以及遗传算法的适应度,通过交叉和变异操作的多次迭代来优化资源分配效果。仿真结果表明,所提方法相较于其他方法在各种场景下均能够获得更高的吞吐量性能,能够有效地联合支撑调度接入和随机竞争接入,提高NOMA系统的资源利用率。In order to improve the resource utilization of sparse code multiple access system(SCMA),a hybrid non-orthogonal multiple access(NOMA)method based on genetic algorithm is proposed.This method makes use of the overload characteristics of NOMA,and allows the same resource unit to carry both scheduled access and random competitive access services simultaneously,thus realizing the fine-grained integration of the two access modes.Furthermore,a hybrid NOMA resource allocation algorithm based on genetic algorithm is designed.Taking the total capacity of the two access modes as the optimization objective and the fitness of genetic algorithm,the resource allocation effect is optimized through multiple iterations of crossover and mutation operations.Simulation results show that compared with other methods,the proposed method can achieve higher throughput performance in various scenarios,effectively support scheduling access and random competitive access,and improve resource utilization of NOMA system.

关 键 词：非正交多址接入 稀疏码多址接入 资源分配 遗传算法 多址接入 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]