# A Scheduling Scheme for Improving the Performance and Security of MU-MIMO Systems
###### Abstract
The performance of the schemes is analyzed in terms of the sum-rate capacity via simulations in presence of Rayleigh fading, and it is shown that capacity-based algorithms, such as the Frobenius norm algorithm, guarantee the best sum-rate for the MIMO system. A critical aspect that has gained attention in new generation mobile networks is information security, mainly for devices with low processing capacity, since here it is not possible to use complex encryption algorithms [28]. Therefore, physical layer security (PLS) becomes an interesting alternative for providing security in these scenarios [29]. In particular, PLS proposals must be adapted to work in conjunction with MIMO, because the latter technique must be implemented in a mandatory way to ensure the key-performance-indicators (KPIs) established for fifth-generation (5G) and beyond 5G (B5G) networks [30]. As a consequence, PLS in MIMO systems has recently been investigated in the literature. In [31], PLS is studied in MIMO systems that employ singular value decomposition (SVD) schemes, where it is determined that the higher the distance between an eavesdropper and the transmitter/receiver, the higher the system secrecy rate. In [32],the secrecy outage probability (SOP) of diversity schemes that employ antenna-user selection and user selection with space-time block coding (US-STBC) over Nakagami fading channels is analyzed. A similar scenario is investigated in [33], where the impact of the number of users, eavesdroppers, and antennas on secrecy performance is demonstrated by employing an asymptotic analysis. In both works, the single-user MRC technique is considered. Finally, in [34], transmit antenna selection is also considered in the downlink of a MIMO system in the presence of some trusted and untrusted users. In the system model, the BS selects a desired legitimate user and the transmitting antenna pair. Then, once the instantaneous SNR of the previously selected legitimate user is below a threshold, the legitimate user with the highest SNR is selected for transmitting in the next symbol period. In all these works, scenarios with perfect channel estimation at the receiver are considered. Table 1 summarizes the MIMO research areas on which the contributions of previous cited works are focused. Based on this literature review and to the best of the authors' knowledge, imperfect channel estimation has not been previously considered when channel scheduling schemes have been proposed or analyzed in MIMO systems operating over generalized fading channels, such as Rician fading. In addition, scheduling schemes constitute an interesting technique for guaranteeing security in the physical layer of MIMO systems. However, these schemes have been little explored so far in the literature for this purpose. Therefore, this is the main motivation for the proposal presented in this work. By the above, this paper proposes a novel scheduling scheme for the uplink of MU-MIMO systems using the multiuser ZF detector at the receiver in the BS considering the presence of imperfect channel estimation at the receiver. At this point, it is important to indicate that it is well known that the ZF detector loses diversity in exchange for eliminating interference [35], and therefore, the proposed scheme aims to maintain system diversity while mitigating interference between users. In addition, it seeks to counteract the undesirable effects produced by the imperfect channel estimation. The presented proposal is evaluated in a Rician fading channel in terms of the mean BER and the OP. In addition, the computational complexity of the presented scheduling scheme is analyzed. Finally, the proposed scheme is employed in a network with the presence of an external eavesdropper trying to decode the information sent by the users. In this case, the system performance is analyzed in terms of the SOP. The remainder of this work is organized as follows. The system model is detailed in Section 2. The instantaneous SNR for each user is obtained in Section 3.