## 1 Introduction
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Reference** & **System Model** & **Research Objective** & **Method** \\ \hline \multirow{8}{*}{[15; 16; 17; 18]} & & & Greedy antenna elimination, \\  & & & SUS \\ \cline{3-4}  & & & Greedy antenna elimination, \\  & Multi-user & & User preselection based on \\  & Massive MIMO, & Maximize the system sum rate under & singular values, \\  & Single-antenna user & low computational complexity & SUS \\ \cline{3-4}  & & & MGEM-based user selection, \\  & & & maximum norm antenna selection \\ \cline{3-4}  & & & User scheduling based on the \\  & & & squared norm of the channel matrix \\ \hline \multirow{3}{*}{[19]} & Massive MIMO, & & Reduce feedback overhead while & Antenna group selection is \\  & antenna group, & & ensuring system sum rate & performed first, followed by \\  & CSI feedback & & intra-group user scheduling \\ \hline \multirow{3}{*}{[20; 21]} & Massive MIMO, & & Maximize the long-term average & POMDP-based joint design \\  & time-varying channel & & Maximize the system weighted & \\  & time-varying channel & & average sum rate while ensuring & \\  & & user QoS requirements & \\ \hline \multirow{3}{*}{[22]} & Multi-cell, & & Maximize the total sum rate of each & \\  & massive MIMO & & cell under multi-cell & \\  & & interference constraints & \\ \hline \multirow{3}{*}{[23]} & Massive MIMO-NOMA, & & Efficiently allocate antennas and & Joint antenna and user contribution \\  & multi-user multi-band & & users across multiple frequency & algorithm, \\  & & bands to maximize the sum rate & considering user pairing and power & \\  & & & allocation in NOMA \\ \hline \multirow{3}{*}{[24]} & Multi-antenna users, & & PFUS under block diagonalization & \\  & user-side antenna selection & & maximize the weighted sum rate & and successive optimization \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Comparison of related works. The key contributions of this paper are outlined below. 1. A system framework is constructed, where a base station fitted with multiple antennas communicates with several users equipped with one antenna. In order to realize simultaneous antenna and user selection strategy, an optimization task is defined with the goal of maximizing the system throughput. \(N_{RF}\) antennas are selected from \(N_{t}\) transmitting antennas, and \(K\) users are selected from \(U\) participants at the same instant. 2. We propose a joint antenna selection and channel orthogonality-based user scheduling algorithm, JAS-OUS, which leverages the spatial selectivity benefit from antenna allocation and multi-user diversity benefit from user allocation correspondingly, to optimize the system sum rate. The key idea of the introduced algorithm is to sequentially remove the weakest antenna, that is, the antenna with the least contribution to the system throughput. Also, the user set having the smallest channel correlation is selected using orthogonality-based user scheduling (OUS) for each antenna removal. 3. Further, in order to ensure the fairness of user scheduling, an improved PFUS user allocation strategy is introduced with the goal of maximizing the weighted throughout. An adjustable weight is set for each user so that different users are selected for communication in each time slot, which makes sure more users will have the opportunity to be served. 4. Simulation results and complexity assessments indicate that JAS-OUS has the potential to guarantee a high transmission rate with lower computational complexity. Compared with the traditional non-proportional fairness scheduling algorithm, the proposed JAS-PFUS algorithm shows good fairness and is able to schedule more users in communication without reducing the system sum rate. The paper is structured as follows. In Section 2, we introduce the joint antenna selection and user allocation model for multi-user massive MIMO and derive the system throughput expression. The specific JAS-OUS and improved JAS-PFUS algorithms are described in Section 3. In Section 4, the simulation data and complexity analysis are given.