چكيده به لاتين
Researches on the 5th generation of wireless networks (5G) have attracted much attention in academic and industrial environments. The 5G network is expected to increase the capacity of current networks by 1000 times. This increase in capacity causes the high energy consumption problem. Thus, it is important to provide power allocation solutions that are energy-efficient and meet technical requirements. Increasing the capacity of the wireless telecommunication system is largely dependent on spectral efficiency and bandwidth. Since the millimeter ware frequency band (mmWave) provides a hgue bandwidth available to the communication networks, it has been considered as a promising technique in 5G wireless networks. On the other hand, the Multi-Input Multi-Output (MIMO) technology which is very in line with mmWave frequencies has been considered to improve spectral efficiency. To further increase the spectral efficiency, research has been done on the integration of NOMA with mmWave mMIMO. NOMA can support more than one user per beam with the aid of Superposition Coding (SC) and Successive Interference Cancellation (SIC), which is quite different from the traditional mmWave mMIMO, in which one beam is used to support only one user at the same time-frequency resources. Due to the lack of full CSI in practical scenarios, it is important to consider the channel estimation error and involve it in capacity and EE expressions to better analyze the system performance. In this thesis, we assume an uplink mmWave mMIMO-NOMA system and derive a closed-form expression for clusters uplink sum-rate. Besides, a two-layer power allocation algorithm which maximizes the EE. Simulation results show that the proposed algorithm is robust against the channel estimation error and achieves better performance rather than other algorithms. For example, with having 30% channel estimation error, the energy-efficiency drop with the proposed algorithm would be only about 30%.
