| Full text | |
| Author(s): |
Carvajal, Henry
;
Orozco, Nathaly
;
Cacuango, Stalin
;
Salazar, Paola
;
Rosero, Edgar
;
Almeida, Fernando
Total Authors: 6
|
| Document type: | Journal article |
| Source: | SENSORS; v. 22, n. 14, p. 21-pg., 2022-07-01. |
| Abstract | |
For the receiver of multiple-input multiple-output (MIMO) systems, linear detectors are an interesting option due to their good performance and low complexity. Nevertheless, MIMO systems lose diversity in exchange for eliminating interference when linear detectors are used. Aiming to maintain the system diversity while mitigating interference between users, this work proposes a scheduling scheme for the uplink of multiuser MIMO (MU-MIMO) systems that employ A antennas and the zero-forcing (ZF) detector at the receiver in the base station (BS). The channel model includes Rician fading and additive white Gaussian noise (AWGN) in an imperfect channel estimation scenario. The proposed scheme selects U users from a group of U-t users to transmit simultaneously, so that the signal-to-noise ratio (SNR) is maximized. For this, an exact expression to evaluate the SNR of the users is obtained. With this result, the scheduling strategy is proposed. Results show that as U-t increases, the outage probability (OP), and the bit error rate (BER) decrease as the system diversity increases, even when the system is completely loaded, i.e., when U = A. Moreover, it is shown that the scheduling scheme counteracts the imperfect channel estimation effects as U-t increases. Finally, the proposed scheme is tested in presence of an external eavesdropper trying to decode the information sent by the users. The results show that the presented proposal allows for a reduction of the secrecy-outage-probability (SOP) as U-t increases. (AU) | |
| FAPESP's process: | 21/03923-9 - An improved framework for sums of Gaussian-class random variables with applications to radar and communication systems |
| Grantee: | Fernando Darío Almeida García |
| Support Opportunities: | Scholarships in Brazil - Post-Doctoral |