Analysis of Energy Efficient Techniques for 5G Ultra Dense Wireless Communication Networks Using Massive MIMO
| dc.contributor.advisor | Yihenew, Wondie (PhD) | |
| dc.contributor.author | Halefom, Tswaslassie | |
| dc.date.accessioned | 2021-11-15T06:41:59Z | |
| dc.date.accessioned | 2023-11-28T14:09:15Z | |
| dc.date.available | 2021-11-15T06:41:59Z | |
| dc.date.available | 2023-11-28T14:09:15Z | |
| dc.date.issued | 2021-10 | |
| dc.description.abstract | In the modern wireless communication energy consumption becomes critical issue for wireless network operators. With the emergence of 5G wireless communication , the importance of energy efficiency (EE) has been appreciated since it is one of the significant performance analysis metrics of wireless networks. Energy can be saved in the design of wirless network if a proper analysis and design optimization is done. Massive MIMO and cell densfications are the latest encouraging technologies to maximize energy efficiency of 5G wireless communications. This thesis work mainly aims on the analysis of energy efficiency techniques of 5G wireless communication using Massive MIMO technology.The techniques to be analysis are in the precoding , in channel state information and massive MIMOtechnology. The analysis begins from circuit power consumption model using zero forcing precoding schemes with TDD communication protocol. The main design parameters are the number of massive antennas at the base station (M), the number of active user equipment terminals (K) , the system throughput (R) and cell density . Then EE is defined as the number of bits transferred per Joule of energy consumed. MATLAB tool is used to prove the impact of the main design parameters on energy efficiency. The impact of massive number of antenna , user equipments and system throughput on energy efficiency with perfect channel state information and imperfect channel state information is analyze . The simulation result shows that we can design optimal values of (M, K and R) that maximize energy efficiency of the system with perfect channel state information than imperfect channel state at the base station. The final results sows that zerforcing precoding and perfect channel state information at the base station saves more energy as compared to iperfect channel state information. | en_US |
| dc.identifier.uri | http://etd.aau.edu.et/handle/12345678/28645 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | Addis Ababa University | en_US |
| dc.subject | 5G | en_US |
| dc.subject | Massive MIMO | en_US |
| dc.subject | Ultra Dense | en_US |
| dc.subject | Linear Precoding | en_US |
| dc.subject | CSI | en_US |
| dc.subject | Energy Efficiency | en_US |
| dc.title | Analysis of Energy Efficient Techniques for 5G Ultra Dense Wireless Communication Networks Using Massive MIMO | en_US |
| dc.type | Thesis | en_US |