Energy-Minimization Resource Allocation for FD-NOMA Enabled Integrated Sensing, Communication, and Computation in PIoT

IF 6.7 2区计算机科学 Q1 ENGINEERING, MULTIDISCIPLINARY

IEEE Transactions on Network Science and Engineering Pub Date : 2024-09-17 DOI:10.1109/TNSE.2024.3462602

Xiaobo Liu;Xinru Wang;Xiongwen Zhao;Fei Du;Yu Zhang;Zihao Fu;Jing Jiang;Peizhe Xin

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引用次数: 0

Abstract

The integration of power Internet of Things (PIoT) with integrated sensing, communication, and computation (ISCC) has become crucial for achieving hierarchical co-regulation and sustainable development in power systems. However, traditional PIoT models designed for edge computing are facing complex challenges due to more intricate and coupled resource allocation in the ISCC design. In this work, we propose a full-duplex (FD) and non-orthogonal multiple access (NOMA) assisted ISCC framework (FD-NOMA-ISCC) in PIoT and investigate the main challenges of FD-NOMA-ISCC from the perspective of joint resource optimization. We jointly optimize the receive beamformer, transmit beamforming design, uplink power control, task offloading decision, and computing resource allocation to minimize the total energy consumption. This forms a complex mixed integer nonlinear programming (MINLP) problem due to the strong correlation between uplink and downlink, as well as the coupling between communication and computing resource allocation. To tackle this, we propose an alternating optimization algorithm based on linear constrained minimum variance (LCMV) that decouples the problem into two iteratively solved subproblems: 1) joint transmit beamforming and power control problem, and 2) joint computing resource allocation and offloading decision problem. Numerical results show that the proposed scheme has a significant advantage in reducing system energy consumption compared with the benchmark schemes.

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PIoT 中支持 FD-NOMA 的集成传感、通信和计算的能量最小化资源分配

电力物联网（PIoT）与集成传感、通信和计算（ISCC）的整合对于实现电力系统的分层协同调节和可持续发展至关重要。然而，由于 ISCC 设计中的资源分配更加复杂和耦合，为边缘计算设计的传统 PIoT 模型面临着复杂的挑战。在这项工作中，我们提出了 PIoT 中的全双工（FD）和非正交多址（NOMA）辅助 ISCC 框架（FD-NOMA-ISCC），并从联合资源优化的角度研究了 FD-NOMA-ISCC 的主要挑战。我们对接收波束形成器、发射波束形成设计、上行链路功率控制、任务卸载决策和计算资源分配进行了联合优化，以最小化总能耗。由于上行链路和下行链路之间的强相关性，以及通信和计算资源分配之间的耦合性，这形成了一个复杂的混合整数非线性编程（MINLP）问题。为解决这一问题，我们提出了一种基于线性约束最小方差（LCMV）的交替优化算法，将问题分解为两个迭代求解的子问题：1）联合发射波束成形和功率控制问题；2）联合计算资源分配和卸载决策问题。数值结果表明，与基准方案相比，拟议方案在降低系统能耗方面具有显著优势。

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来源期刊

IEEE Transactions on Network Science and Engineering Engineering-Control and Systems Engineering

CiteScore

12.60

自引率

9.10%

发文量

393

期刊介绍： The proposed journal, called the IEEE Transactions on Network Science and Engineering (TNSE), is committed to timely publishing of peer-reviewed technical articles that deal with the theory and applications of network science and the interconnections among the elements in a system that form a network. In particular, the IEEE Transactions on Network Science and Engineering publishes articles on understanding, prediction, and control of structures and behaviors of networks at the fundamental level. The types of networks covered include physical or engineered networks, information networks, biological networks, semantic networks, economic networks, social networks, and ecological networks. Aimed at discovering common principles that govern network structures, network functionalities and behaviors of networks, the journal seeks articles on understanding, prediction, and control of structures and behaviors of networks. Another trans-disciplinary focus of the IEEE Transactions on Network Science and Engineering is the interactions between and co-evolution of different genres of networks.