A cognitive spectrum allocation scheme for data transmission in smart distribution grids

IF 3.2 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS High-Confidence Computing Pub Date : 2024-01-11 DOI:10.1016/j.hcc.2024.100198
Zhongguo Zhou , You Li , Ziming Zhu , Qinghe Gao , Sisi Xiao , Tao Yan , Yan Huo
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Abstract

As the communication needs in the smart distribution grid continue to rise, using existing resources to meet this growing demand poses a significant challenge. This paper researches on spectrum allocation strategies utilizing cognitive radio (CR) technology. We consider a model containing strong time-sensitive and regular communication service requirements such as distribution terminal communication services, which can be seen as a user with primary data (PD) and weak time-sensitive services such as power quality monitoring, which can be seen as a user with secondary data (SD). To fit the diversity of services in smart distribution grids (SDGs), we formulate an optimization problem with two indicators, including the sum of SD transmission rates and the maximum latency of them. Then, we analyze the two convex sub-problems and utilize convex optimization methods to obtain the optimal power and frequency bandwidth allocation for the users with SD. The simulation results indicate that, when the available transmission power of SD is low, Maximization of Transmission Sum Rate (MTSR) achieves lower maximum transmit time. Conversely, when the available transmission power is high, the performance of Minimization of the Maximum Latency (MML) is better, compared with MTSR.

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用于智能配电网数据传输的认知频谱分配方案
随着智能配电网的通信需求不断增加,如何利用现有资源满足日益增长的需求成为一项重大挑战。本文研究了利用认知无线电(CR)技术的频谱分配策略。我们考虑了一个包含强时间敏感性和常规通信服务需求的模型,如配电终端通信服务,它可以被看作是拥有一次数据(PD)的用户,以及弱时间敏感性服务,如电能质量监测,它可以被看作是拥有二次数据(SD)的用户。为了适应智能配电网(SDGs)中服务的多样性,我们提出了一个优化问题,其中包含两个指标,包括 SD 传输速率之和及其最大延迟。然后,我们分析了这两个凸子问题,并利用凸优化方法获得了标清用户的最优功率和频率带宽分配。仿真结果表明,当 SD 的可用传输功率较低时,最大化传输总和速率(MTSR)能获得较低的最大传输时间。相反,当可用传输功率较高时,最大延迟最小化(MML)与 MTSR 相比性能更好。
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