Total and Minimum Energy Efficiency Tradeoff in Robust Multigroup Multicast Satellite Communications

作     者：Bin Jiang Yingchun Yan Jingjing Zhao Xiang Xiao Li You Di Zhang Jizhao Lei Kezhi Wang Wenjin Wang Xiqi Gao 

作者机构：National Mobile Communications Research LaboratorySoutheast UniversityNanjing 210096China Purple Mountain LaboratoriesNanjing 211100China Department of Electronic Information EngineeringBeihang UniversityBeijing 100191China School of Information EngineeringZhengzhou UniversityZhengzhou 450001China China Aerospace Science and Technology CorporationBeijing 100094China Department of Computer ScienceBrunel University LondonUxbridgeMiddlesexUB83PHUK. 

出 版 物：《Space(Science & Technology)》 (空间科学与技术（英文）)

年 卷 期：2023年第3卷第1期

页      面：389-401页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 07[理学] 070105[理学-运筹学与控制论] 0701[理学-数学] 

基　　金：supported by the National Natural Science Foundation of China under Grant 62341110 the Key Technologies R&D Program of Jiangsu(Prospective and Key Technologies for Industry)under Grants BE2022067 and BE2022067-5,the Jiangsu Province Basic Research Project under Grant BK20192002 the Fundamental Research Funds for the Central Universities under Grants 2242021R41148 and 2242022k60007 the Young Elite Scientist Sponsorship Program by China Institute of Communications supported by the National Natural Science Foundation of China under Grant U2233216 

主　　题：convex eigenvalue sequentially 

摘      要：Satellite communication is an indispensable part of future wireless communications given its global coverage and long-distance *** satellite communication systems,channel acquisition and energy consumption are two critical *** this end,we investigate the tradeoff between the total energy efficiency(TEE)and minimum EE(MEE)for robust multigroup multicast satellite communication systems in this ***,under the total power constraint,we investigate the robust beamforming aimed at balancing the TEE-MEE,so as to achieve the balance between the fairness and total performance on the system *** this optimization problem,we first model the balancing problem as a nonconvex problem while deriving its approximate closed-form average user ***,the nonconvex problem is handled by solving convex programs sequentially with the help of the semidefinite relaxation and the concave-convex *** addition,depending on the solution rank value,Gaussian randomization and eigenvalue decomposition method are applied to generate the feasible ***,simulation results illustrate that the proposed approach can effectively achieve the balance between the TEE and MEE,thus realizing a tradeoff between fairness and system EE *** is also indicated that the proposed robust approach outperforms the conventional baselines in terms of EE performance.