对于物联网网络而言,一种新的用户集群和高效的资源分配在非对角的多重访问中
Syed Muhammad Hamedoon1, Jawwad Nasar Chattha1, Muhammad Bilal2
1Department of Electrical Engineering, School of Electrical Engineering, University of Management and Technology, Lahore, Pakistan.
PloS one
|September 9, 2024
概括
这项研究优化了许多物联网设备的5G非直角多重访问 (NOMA) 网络的资源配置. 一种新的部分粗暴力搜索 (P-BFS) 方法提高了系统吞吐量和能源效率.
科学领域:
- 无线通信网络是无线通信网络.
- 资源分配优化资源分配优化
- 物联网 (IoT) 的物联网 (IoT) 的物联网.
背景情况:
- 优化资源配置对于5G和超越网络至关重要,特别是连接众多物联网设备.
- 非直角多重接入 (NOMA) 提供高系统吞吐量,但面临电池有限物联网设备的能源消耗和服务质量 (QoS) 的挑战.
- 现有的用户集群方法缺乏适应多种道条件的适应性,影响了整体吞吐量.
研究的目的:
- 调查用户集群和电力分配,以在多载波NOMA系统中加强资源管理.
- 为了提高系统总和率和能源效率,同时满足物联网设备的 QoS 要求.
- 开发一个计算效率高的资源分配方案.
主要方法:
- 一个代的优化过程,涉及用户聚类,其次是功率分配.
- 用户集群使用部分暴力搜索 (P-BFS) 方法来减少复杂性.
- 通过卡鲁什-库恩-塔克尔 (KKT) 条件的拉格朗日乘法确定最佳功率分配.
- 一个与P-BFS集成的深度神经网络 (DNN),以进一步降低资源分配的复杂性.
主要成果:
- 拟议的P-BFS用户集群与详尽的搜索方法相比,大大降低了复杂性.
- 为每个集群和子频道内的用户实现最佳的功率分配.
- 基于DNN的P-BFS方案进一步提高了资源分配的效率.
- 模拟结果显示,网络的总比率大幅提高.
结论:
- 开发的P-BFS技术有效地解决了NOMA系统中的用户集群挑战.
- 将DNN与P-BFS集成为复杂的资源分配问题提供了一个有希望的方法.
- 拟议的方法在NOMA-enabled物联网网络的总比率方面带来了显著的性能提升.
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