NOMA-MEC系统中面向交互式多媒体应用的资源管理策略  

Resource Management Strategy for Interactive Multimedia Service in NOMA-MEC System

作　　者：党亚萍 任瑞敏 杨守义[1] DANG Yaping;REN Ruimin;YANG Shouyi(School of Electrical and Information Engineering,Zhengzhou University,Zhengzhou 450001,China)

机构地区：[1]郑州大学电气与信息工程学院,河南郑州450001

出　　处：《无线电通信技术》2025年第2期311-320,共10页Radio Communications Technology

基　　金：国家自然科学基金(62101499);国家重点研发计划(2019YFB1803200)。

摘　　要：随着互联网技术的发展,云游戏、虚拟现实和互动直播等新兴交互式多媒体应用引起了广泛关注。当前智能设备的计算能力难以满足多媒体内容对超高渲染和实时交互的需求,且云端赋能方式因存在高带宽、高延迟、高能耗等问题,限制了其在移动网络中的实际应用。为应对这些挑战,提出一种边缘计算辅助交互式多媒体应用的系统框架,旨在确保满足用户服务质量需求的前提下降低系统能耗。构建融合非正交多址(Non-Orthogonal Multiple Access,NOMA)与移动边缘计算(Mobile Edge Computing,MEC)技术的网络通信模型,考虑到MEC服务器资源受限以及用户服务质量需求各异等因素,提出联合用户关联和资源分配的优化方案。为高效解决优化问题,结合遗传算法(Genetic Algorithm,GA)和粒子群优化(Particle Swarm Optimization,PSO)的优势,设计了分层自适应搜索算法(Hierarchical GA and PSO Based Adaptive Search Algorithm,HGPASA)。通过一系列仿真实验,充分验证了所提算法的有效性。With the development of Internet technology,emerging interactive multimedia applications such as cloud gaming,virtual reality,and interactive live streaming have attracted widespread attention.However,the current computational capabilities of smart devices struggle to meet the demands for ultra-high rendering and real-time interaction of multimedia content.Meanwhile,the cloud-enabled approach limits its practical application in mobile networks due to problems such as high bandwidth consume,high response latency,and high energy consumption.To address these challenges,this research proposes a system framework for edge computing-assisted interactive multimedia applications,aiming to reduce system energy consumption while ensuring service quality.Firstly,a network communication model is constructed,integrating Non-Orthogonal Multiple Access(NOMA)technology and Mobile Edge Computing(MEC).Secondly,a joint optimization scheme is proposed for user association and resource allocation,taking into account factors such as limited MEC server resources and varying user service quality requirements.In order to solve the optimization problem efficiently,a Hierarchical Genetic Algorithm(GA)and Particle Swarm Optimization(PSO)Based Adaptive Search Algorithm(HGPASA)is designed by combining the advantages of GA and PSO.Finally,a series of simulation experiments thoroughly demonstrate the effectiveness of the proposed approach in this paper.

关 键 词：交互式多媒体 移动边缘计算 非正交多址技术 用户关联 资源分配 

分 类 号：TN929.5[电子电信—通信与信息系统]