Ruiyan Du;Long Li;Zhiqing Guan;Baozhu Shi;Zhuoyao Duan;Fulai Liu
{"title":"AFC-TH Hybrid Precoding With High Energy Efficiency for Millimeter Wave Communication Systems","authors":"Ruiyan Du;Long Li;Zhiqing Guan;Baozhu Shi;Zhuoyao Duan;Fulai Liu","doi":"10.1109/TGCN.2024.3394834","DOIUrl":null,"url":null,"abstract":"As a structure with lower power consumption and hardware cost, the adaptive fully-connected (AFC) structure can improve energy efficiency significantly for hybrid precoding. Based on this, this paper proposes an energy-efficient AFC Tomlinson-Harashima (AFC-TH) hybrid precoding algorithm. Specifically, to alleviate inter-user interference and enhance system performance, a TH algorithm based on the mean square error minimization of signals (S-MMSE-TH) is proposed to obtain the optimal digital precoding matrix. Furthermore, to reduce the computational complexity of optimization the switch precoding matrix, a branch-and-bound based on subspace projection method is developed. Different from the traditional branch-and-bound method by the convex relaxation, the subspace projection method is used to obtain a closed-form lower bound of the objective function. It can reduce the computational cost effectively. Moreover, according to the norm and the nonlinear programming theories, a phase shifters precoding matrix optimization method is proposed. In this method, the phase-shifter precoding matrix optimization problem is transformed into a positive semidefinite quadratic form satisfying the KKT condition. Especially, a diagonal loading factor is introduced to satisfy the KKT condition to reduce the computational cost. Simulation results and complexity analysis show that the proposed method provides high energy efficiency while enjoying satisfactory spectral efficiency with a low computational complexity.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":"8 4","pages":"1622-1631"},"PeriodicalIF":5.3000,"publicationDate":"2024-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Green Communications and Networking","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10509819/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"TELECOMMUNICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
As a structure with lower power consumption and hardware cost, the adaptive fully-connected (AFC) structure can improve energy efficiency significantly for hybrid precoding. Based on this, this paper proposes an energy-efficient AFC Tomlinson-Harashima (AFC-TH) hybrid precoding algorithm. Specifically, to alleviate inter-user interference and enhance system performance, a TH algorithm based on the mean square error minimization of signals (S-MMSE-TH) is proposed to obtain the optimal digital precoding matrix. Furthermore, to reduce the computational complexity of optimization the switch precoding matrix, a branch-and-bound based on subspace projection method is developed. Different from the traditional branch-and-bound method by the convex relaxation, the subspace projection method is used to obtain a closed-form lower bound of the objective function. It can reduce the computational cost effectively. Moreover, according to the norm and the nonlinear programming theories, a phase shifters precoding matrix optimization method is proposed. In this method, the phase-shifter precoding matrix optimization problem is transformed into a positive semidefinite quadratic form satisfying the KKT condition. Especially, a diagonal loading factor is introduced to satisfy the KKT condition to reduce the computational cost. Simulation results and complexity analysis show that the proposed method provides high energy efficiency while enjoying satisfactory spectral efficiency with a low computational complexity.