A New HBS Model in Millimeter-Wave Beamspace MIMO-NOMA Systems Using Alternative Grey Wolf with Beetle Swarm Optimization

Beam selection is a major conflict in wireless communications. In the existing methods, the energy efficiency maximization problem is handled by the non-convex fractional programming algorithm. Yet, various traditional works have used the Single Beam Selection (SBS) scheme having the mmWave beamspace Multi-Input Multi-Output (MIMO) channel for minimizing the MIMO dimension. Still, multiple Radio-Frequency (RF) chain groups cannot be properly selected by users. Generally, the conventional (SBS) concept cannot work with a multiple beam group selection opportunities for all the types of supported users. So, the user suffers from a severe computational burden for measuring the decoded message and it also leads to a beam optimization problem. This paper plans to integrate the two meta-heuristic algorithms like Beetle swarm optimization (BSO) and Grey Wolf Optimization called the Alternative Grey Wolf with Beetle Swarm Optimization (AGW-BSO) for developing the Hybrid Beam Selection (HBS) scheme in MIMO-NOMA and the new HBS scheme could support the multiple SBS scheme in beamspace MIMO-NOMA systems. Here, the optimization of RF chain group by the proposed AGW-BSO is considered as the main contribution, in such a way to attain the multi-objective function concerning the maximization of beam power, energy efficiency, and spectral efficiency. Finally, the attained objective of the proposed model is analyzed by comparing the proposed model over the conventional models through computer simulations.