{"title":"Cross-layer Bandwidth and Antenna Configuration for Smart Grid under MIMO Transmission","authors":"Yixuan Zhang, Nan Liu, Zhiwen Pan","doi":"10.1145/3603781.3603918","DOIUrl":null,"url":null,"abstract":"This paper studies the statistical observability of the power grid with multiple-input multiple-output (MIMO) transmission while satisfying the QoS requirement, which is characterized by effective capacity. The problem is to maximize the observability of the power grid over all possible bandwidth allocation, antenna configuration, and the QoS exponent for each PMU. To solve the proposed optimization problem, an alternating optimization algorithm is adopted, where, the simulated annealing algorithm is applied to conduct the antenna configuration, and the deep Q-network (DQN) is adopted to conduct bandwidth allocation. Numerical results demonstrate bandwidth and antenna savings of the proposed algorithm compared with equal allocation scheme.","PeriodicalId":391180,"journal":{"name":"Proceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things","volume":"71 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3603781.3603918","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper studies the statistical observability of the power grid with multiple-input multiple-output (MIMO) transmission while satisfying the QoS requirement, which is characterized by effective capacity. The problem is to maximize the observability of the power grid over all possible bandwidth allocation, antenna configuration, and the QoS exponent for each PMU. To solve the proposed optimization problem, an alternating optimization algorithm is adopted, where, the simulated annealing algorithm is applied to conduct the antenna configuration, and the deep Q-network (DQN) is adopted to conduct bandwidth allocation. Numerical results demonstrate bandwidth and antenna savings of the proposed algorithm compared with equal allocation scheme.