RESOURCE ALLOCATION FOR 5G MOBILE COMMUNICATION-BASED NOMA USING EVOLUTIONARY APPROACH: AN ARCHIMEDES OPTIMIZATION ALGORITHM

Cellular network users are always on the lookout for excellent broadband connections, even when device density is high and channel conditions are critical. To meet this need, non-orthogonal multiple access (NOMA) technology was recently presented as a new technology for future wireless access to improve the network quality of service (QoS) between users. This technology allows the coexistence of two or more users per subcarrier. The allocation of resources in these networks also presents its own problems, such as scalability and resource distribution variability. To solve these problems, researchers are focusing on evolutionary algorithms (EA), such as particle swarm optimization (PSO), discrete particle swarm optimization (DPSO), genetic algorithm (GA), differential evolution (DE), etc. This paper presents a new method for resource allocation in the 5G mobile network, using the Archimedes optimization algorithm (AOA), while taking into account channel conditions, user mobility in the cell, and different types of services. Simulation results show the effectiveness of the AOA algorithm, which can guarantee high throughput for the user, as well as better spectral and energy efficiency compared with other scalable algorithms.