Department of Electrical and Electronics Engineering, Sunyani Technical University, Sunyani P.O. Box 206, Ghana.
Electrical Engineering Department, National University of Computer and Emerging Sciences, Lahore 54770, Pakistan.
Sensors (Basel). 2023 May 12;23(10):4711. doi: 10.3390/s23104711.
The problem of energy optimization for Internet of Things (IoT) devices is crucial for two reasons. Firstly, IoT devices powered by renewable energy sources have limited energy resources. Secondly, the aggregate energy requirement for these small and low-powered devices is translated into significant energy consumption. Existing works show that a significant portion of an IoT device's energy is consumed by the radio sub-system. With the emerging sixth generation (6G), energy efficiency is a major design criterion for significantly increasing the IoT network's performance. To solve this issue, this paper focuses on maximizing the energy efficiency of the radio sub-system. In wireless communications, the channel plays a major role in determining energy requirements. Therefore, a mixed-integer nonlinear programming problem is formulated to jointly optimize power allocation, sub-channel allocation, user selection, and the activated remote radio units (RRUs) in a combinatorial approach according to the channel conditions. Although it is an NP-hard problem, the optimization problem is solved through fractional programming properties, converting it into an equivalent tractable and parametric form. The resulting problem is then solved optimally by using the Lagrangian decomposition method and an improved Kuhn-Munkres algorithm. The results show that the proposed technique significantly improves the energy efficiency of IoT systems as compared to the state-of-the-art work.
物联网 (IoT) 设备的能源优化问题至关重要，原因有二。首先，由可再生能源供电的 IoT 设备的能源资源有限。其次，这些小型低功率设备的总能源需求转化为大量的能源消耗。现有研究表明，物联网设备的很大一部分能量消耗在无线电子系统上。随着第六代 (6G) 的出现，能效是显著提高物联网网络性能的主要设计标准。为了解决这个问题，本文重点研究如何最大化无线电子系统的能效。在无线通信中，信道在确定能源需求方面起着重要作用。因此，本文通过混合整数非线性规划问题，根据信道条件，以组合方式联合优化功率分配、子信道分配、用户选择和激活的远程无线电单元 (RRU)。尽管这是一个 NP 难问题，但通过分数规划特性将其转化为等效的可处理和参数形式，从而可以对优化问题进行求解。然后，通过使用拉格朗日分解方法和改进的 Kuhn-Munkres 算法来最优地解决这个问题。结果表明，与现有技术相比，所提出的技术显著提高了物联网系统的能源效率。
