Abstract
In this work, we talk about the problem of joint power allocation and user association based on quality-of-service for non-orthogonal multiple access (NOMA) to downlink networks. The problem is especially difficult due to its non-convex form and the large number of optimization variables, which are solved using two different nature-inspired algorithms with low complexity. We investigate the effect of different network parameters on increasing users. Numerical results show that, for a growing number of users, the problem is becoming increasingly difficult, which indicates the increasing network resources required to solve it. The results of the simulations show that using evolutionary algorithms is a fast and effective way to solve this kind of problem. Moreover, the NOMA advantage over OMA becomes clear as the number of users increases. Evolutionary techniques outperform randomly generated solutions, as expected.
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