Throughput Maximization in Hybrid NOMA assisted Beyond 5G Heterogeneous Networks

The increasing number of mobile devices and multimedia applications demands enormous capacity that requires innovative network designs. A hybrid non-orthogonal multiple access (NOMA) scheme with user clustering has been considered a promising solution to meet the increasing demand for capacity. Successive interference cancellation (SIC) is applied to minimize interference in NOMA. Also, in addition to this, heterogeneous networks (HetNets) improve network throughput. It is necessary to find optimal resource allocation for throughput maximization. In this paper, a mixed-integer non-linear programming (MINLP) problem has formulated for throughput maximization using a hybrid NOMA scheme with user clustering in a macro base station (MBS) only network and HetNets. MINLP problems are non-deterministic polynomial time-hard (NP-hard) in general. An exhaustive search algorithm with the exponential increase in complexity with the number of users restricts it to use for the problem's solution. The throughput maximization problem is solved using an outer approximation algorithm. The proposed algorithm is evaluated with extensive simulations to show that the proposed solution is effective regarding network throughput and user association. Also, the proposed algorithm compares user admission in clusters, user association with BSs in MBS only network, and HetNets. The results clearly show that HetNet outperforms MBS only network in terms of the network throughput, the number of users admitted in clusters, and the number of users associated.