Dynamic Bandwidth Allocation and Precoding Design for Highly-Loaded Multiuser MISO in Beyond 5G Networks

Multiuser techniques play a central role in the fifth-generation (5G) and beyond 5G (B5G) wireless networks that exploit spatial diversity to serve multiple users simultaneously same frequency resource. It is well known multi-antenna base station (BS) can efficiently number of not exceeding antennas at BS via precoding design. However, when there are more than BS, conventional design methods perform poorly because inter-user interference cannot be eliminated. In this paper, we investigate performance highly-loaded multiuser system which serves larger antennas. We propose dynamic bandwidth allocation framework apply it two important problems systems: i) User fairness maximization ii) Transmit power minimization, both subject predefined quality service (QoS) requirements. The premise proposed dynamically assign orthogonal channels different user groups carefully vectors within every group. Since formulated non-convex, iterative algorithms based on successive convex approximations (SCA), whose convergence theoretically guaranteed. Furthermore, low-complexity grouping policy singular value decomposition (SVD) further improve performance. Finally, demonstrate numerical results significantly outperforms existing designs literature.