Hybrid Grey Wolf Optimization and Crow Search Algorithm for Power allocation in MIMO-NOMA systems

Abstract

For 5G communication systems, Non-Orthogonal Multiple Access (NOMA) operates as the shows potential multiple access technologies, and the ability to enhance the system performance. It can be extended with MIMO systems using multi-users to make substantial gains. The Energy Efficiency (EE) of MIMO-NOMA systems require to be enhanced, for that the optimization algorithm called Grey Wolf and Crow Search algorithm for Power allocation (GWCSPA) method is proposed. The GWCS optimization approach is attained from the combination of Grey Wolf Optimization (GWO) and Crow Search Algorithm (CSA) and the proposed GWCSPA techniques schedules user based on EE and Spectral Efficiency (SE) so that it presents an effectual platform to present energy effectual power allocation. The scheduling is carried out exploiting the GWCSPA method which prioritizes users in the best manner based on the objective function. The simulation is carried out by exploiting the estimated measures, like Bit Error Rate (BER), attainable rate, spectral power, and energy. The efficiency of the proposed power allocation algorithm is shown during lesser BER and superior spectral power, achievable rate, and energy correspondingly.

References