Abdulbasit M. A. Sabaawi, Mohammed R. Almasaoodi, Sara El Gaily, S. Imre
{"title":"基于约束量子优化的MIMO系统","authors":"Abdulbasit M. A. Sabaawi, Mohammed R. Almasaoodi, Sara El Gaily, S. Imre","doi":"10.1109/CSNDSP54353.2022.9907967","DOIUrl":null,"url":null,"abstract":"The multiple-input multiple-output (MIMO) systems provide high data rates and spectral efficiency performance. However, the fundamental problems with these technologies are their rising computational complexity and power consumption. The aim of this paper is to minimize the total transmit power of the MIMO system subject to the target bit rate of the user. The procedure of assigning different transmit power values to transmiting antennas and selecting the optimum total transmit power with respect to the user’s bit rate constraint is computationally hard, especially when the size of the possible transmit power scenarios arises exponentially. To this end, an efficient quantum strategy called Constrained Quantum optimization Algorithm (CQOA) is proposed in this work, which searches faster (exponentially) for the optimum result. The proposed quantum strategy is compared with the various optimization algorithms such as Genetic Algorithm (GA). Simulation results highlight the fact that the CQOA outperforms the GA in terms of computational complexity.","PeriodicalId":288069,"journal":{"name":"2022 13th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP)","volume":"119 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"MIMO System Based-Constrained Quantum optimization Solution\",\"authors\":\"Abdulbasit M. A. Sabaawi, Mohammed R. Almasaoodi, Sara El Gaily, S. Imre\",\"doi\":\"10.1109/CSNDSP54353.2022.9907967\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The multiple-input multiple-output (MIMO) systems provide high data rates and spectral efficiency performance. However, the fundamental problems with these technologies are their rising computational complexity and power consumption. The aim of this paper is to minimize the total transmit power of the MIMO system subject to the target bit rate of the user. The procedure of assigning different transmit power values to transmiting antennas and selecting the optimum total transmit power with respect to the user’s bit rate constraint is computationally hard, especially when the size of the possible transmit power scenarios arises exponentially. To this end, an efficient quantum strategy called Constrained Quantum optimization Algorithm (CQOA) is proposed in this work, which searches faster (exponentially) for the optimum result. The proposed quantum strategy is compared with the various optimization algorithms such as Genetic Algorithm (GA). Simulation results highlight the fact that the CQOA outperforms the GA in terms of computational complexity.\",\"PeriodicalId\":288069,\"journal\":{\"name\":\"2022 13th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP)\",\"volume\":\"119 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-07-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 13th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CSNDSP54353.2022.9907967\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 13th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSNDSP54353.2022.9907967","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
MIMO System Based-Constrained Quantum optimization Solution
The multiple-input multiple-output (MIMO) systems provide high data rates and spectral efficiency performance. However, the fundamental problems with these technologies are their rising computational complexity and power consumption. The aim of this paper is to minimize the total transmit power of the MIMO system subject to the target bit rate of the user. The procedure of assigning different transmit power values to transmiting antennas and selecting the optimum total transmit power with respect to the user’s bit rate constraint is computationally hard, especially when the size of the possible transmit power scenarios arises exponentially. To this end, an efficient quantum strategy called Constrained Quantum optimization Algorithm (CQOA) is proposed in this work, which searches faster (exponentially) for the optimum result. The proposed quantum strategy is compared with the various optimization algorithms such as Genetic Algorithm (GA). Simulation results highlight the fact that the CQOA outperforms the GA in terms of computational complexity.