# Downlink transceiver beamforming and admission control for massive MIMO cognitive radio networks

## TL;DR

This paper introduces an optimization framework for joint beamforming and admission control in massive MIMO cognitive radio networks, aiming to maximize secondary user support while managing power, rate, and interference constraints.

## Contribution

It presents a novel three-step algorithm with two power allocation schemes and an ILP-based solution for a complex NP-hard problem in cognitive radio networks.

## Key findings

- Equal rate and equal power schemes perform differently under various constraints.
- The ILP approach provides an optimal solution benchmark.
- The framework effectively manages interference and supports maximum secondary users.

## Abstract

In this paper, an optimization framework is proposed for joint transceiver beamforming and admission control in massive MIMO cognitive radio networks. The objective of the optimization problem is to support maximum number of secondary users in downlink transmission with constraints on the total power allocated to users, the rate achieved at secondary users and the interference at the primary nodes. The proposed framework takes into account the imperfect knowledge of the channels between the secondary and the primary nodes and also mitigates the interference caused by the primary users at secondary receivers. In order to solve the underlying NP-hard problem, we propose a three-step algorithm with two alternative schemes for power allocation, namely: equal power and equal rate. In addition, we provide a solution by reducing the problem to an Integer Linear Program (ILP). The performances of equal rate, equal power, and ILP methods are studied in under different constraints.