Abstract:
Massive Multiple Input Multiple Output (MIMO) technology, characterized by deploying numerous
antennas at base stations, represents a breakthrough in wireless communication. It facilitates substantial
enhancements in spectral efficiency and streamlines transmission processing. However, its notable
drawback lies in its high power consumption. Consequently, Beamspace MIMO has emerged as a pivotal
technology in the realm of advanced 5G technology, offering a solution to address these challenges. In
this thesis we study and analyze the beam selection algorithms in beamspace MIMO systems. This thesis
presents a performance analyze of beam selection techniques for beamspace MIMO-NOMA systems. In
the beamspace MIMO-NOMA system, beam selection plays a critical role in enhancing the spectral
efficiency and energy efficiency of the system. For this, first we analyze recent works on beam selection
techniques, channel modeling, power allocation, clustering and precoding in massive MIMO systems.
In this thesis, is evaluate the performance of beam selections techniques for beamspace MIMO-NOMA
systems, including the maximal-magnitude (MM) beam selection technique, the maximum-SINR
(MSINR) beam selection technique, and the minimum-capacity (MC) beamspace MIMO-NOMA beam
selection technique. Specifically, after UEs select a beam, we receive a new channel matrix the user
selects the same beam is clustered in one group and served by a single beam by deploying NOMA scheme
in each cluster. Finally, to maximize achievable sum-rate (ASR) optimization of power allocation of user
in given cluster is solved and optimizing power allocation factors using power coefficient optimization
approach is optimized the power coefficients for each user in the given cluster M by power allocation
scheme. Computer simulations validate the numerical results; The MSINR improves the capacity of a
system than MC and MM as number of users is increase, where the number of users is reached 50 users
the spectral efficiency served user is 110, 85 and 75 respectively. Moreover, MSINR is enhance two
methods as SNR and number of user increases. The simulation further confirms that MSINR has a higher
energy efficiency than alternative approaches due to the selected beam's lower relative consumption of
power. Finally, proposed MSINR beamspace MIMO-NOMA schemes achieve higher spectrum efficiency
(SE) and energy efficiency (EE) than the MC and MM beamspace MIMO-NOMA schemes.
