A genetic algorithm based hybrid non-orthogonal multiple access protocol

Both high-dense wireless connectivity and ultra-huge network capacity are main challenges of next generation broadband networks. As one of its key promising technologies, non-orthogonal multiple access (NOMA) scheme can solve those challenges and meet those needs to some extent, in the way that different user equipments (UEs) multiplex on the same resource. Researchers around the world have presented numerous NOMA solutions. Among those, sparse code multiple access (SCMA) technology is a typical NOMA solution. It supports scheduled access and random access which can be called granted access and grant-free access respectively. But resources allocated to granted UEs and grant-free UEs are strictly separated. In order to improve resource utilization, a hybrid non-orthogonal multiple access scheme is proposed. It allows granted UEs and grant-free UEs sharing the same resource unit in terms of fine-grained integration. On the basis, a resource allocation method is further brought forward based on genetic algorithm. It optimizes resource allocation of all UEs by mapping resource distribution issue to an optimization problem. Comparing throughputs of four methods, simulation results demonstrate the proposed genetic algorithm has better throughput gain.