윤원식 김우재 2017-02 24239 https://aurora.ajou.ac.kr/handle/2018.oak/11034 학위논문(석사)--아주대학교 일반대학원 :전자공학과,2017. 2 1 Introduction 1 1.1 Background and Motivation ……………………. 1 1.2 Contributions ……………………………………. 2 1.3 Thesis Outline ……………………………………. 3 2 Uplink Energy Efficiency maximization 4 2.1 System Model …………………………………….. 4 2.2 Uplink Channel Estimation ……………………….. 6 2.3 Downlink Energy Transfer ……………………….. 6 2.4 Uplink Information Transfer ……………………. 7 2.5 Problem Formulation ………………………………. 8 2.6 EE Maximization Scheme …………………………. 9 2.7 Simulation Results …………………………………. 11 3 Uplink Minimum Throughput Maximization 14 3.1 System Model …………………………………….. 14 3.2 Problem Formulation ……………………………… 15 3.3 Joint Beamforming and Resource Allocation ….. 16 3.4 Simulation Results ……………………………….. 18 4 Conclusion 21 Reference 23 eng The Graduate School, Ajou University 아주대학교 논문은 저작권에 의해 보호받습니다. 분산형 대규모 MIMO 시스템에서 WPCN 빔포밍 및 자원할당 통합 최적화 기법 KIM WOO JAE Thesis 아주대학교 일반대학원 KIM WOO JAE 일반대학원 전자공학과 2017. 2 Master http://dcoll.ajou.ac.kr:9080/dcollection/jsp/common/DcLoOrgPer.jsp?sItemId=000000024239 대규모 MIMO WPCN 통합 최적화 In this thesis, we study a joint optimization for wireless powered communication network (WPCN) with distributed massive multi-input multi-output (DM-MIMO) system. We maximize the uplink (UL) energy efficiency (EE) and max-min throughput by jointly optimize energy beamforming, time allocation, power allocation, and receive beamforming. Generally, in a WCPN, user terminals are charged wirelessly from signals radiated by transmitters and then use the harvested energy to transmit information signals. Thus, wireless energy transfer (WET) time affects both UL transmit power and capacity. When WET time has a small range, the average UL transmit power for the users is increased as time increase. However, when WET time becomes large, the wireless information transfer (WIT) time becomes the dominant factor and thus the user rates are decreased. Also, energy efficiency and guaranteeing minimum throughput has been recognized as a crucial issue in WPCN. It is due to the harvested energy from radiated signal is usually very small. Therefore, in this thesis, joint time allocation, power allocation, and beamforming optimization algorithms to solve EE maximization and max-min throughput maximization problem are proposed. The simulation results show that the proposed schemes can achieve a significant performance gain. Further, it reveals that the achievable EE and max-min capacity of the DM-MIMO is considerably higher than that of a conventional centralized massive multi-input multi-output (CM-MIMO) system.