Next Article in Journal
A Reproducible Method for Growing Biofilms on Polystyrene Surfaces: Biomass and Bacterial Viability Evolution of Pseudomonas fluorescens and Staphylococcus epidermidis
Next Article in Special Issue
A Dropout Compensation ILC Method for Formation Tracking of Heterogeneous Multi-Agent Systems with Loss of Multiple Communication Packets
Previous Article in Journal
Flow Visualization of Spinning and Nonspinning Soccer Balls Using Computational Fluid Dynamics
Previous Article in Special Issue
Distributed Localization with Complemented RSS and AOA Measurements: Theory and Methods
Open AccessArticle

An Enhanced Precoder for Multi User Multiple-Input Multiple-Output Downlink Systems

1
Department of Information and Communication Engineering, Sejong University, Seoul 05006, Korea
2
Department of Computer Engineering, Sejong University, Seoul 05006, Korea
*
Author to whom correspondence should be addressed.
Appl. Sci. 2020, 10(13), 4547; https://doi.org/10.3390/app10134547
Received: 9 June 2020 / Revised: 26 June 2020 / Accepted: 27 June 2020 / Published: 30 June 2020
(This article belongs to the Special Issue Multi-Channel and Multi-Agent Signal Processing)
Recently, as the demand for data rate of users has increased, wireless communication systems have aimed to offer high throughput. For this reason, various techniques which guarantee high performance have been invented, such as massive multiple-input multiple-output (MIMO). However, the implementation of huge base station (BS) antenna array and decrease of reliability as the number of users increases are chief obstacles. In order to mitigate these problems, this paper proposes an adaptive precoder which provides high throughput and bit error rate (BER) performances to achieve the desired data rate in multi user (MU) MIMO downlink systems which have a practical BS antenna array (up to 16). The proposed scheme is optimized with a modified minimum mean square error (MMSE) criterion in order to improve BER gain and reduce data streams in order to obtain diversity gain at low signal to noise ratio (SNR). It is shown that the BER and throughput performances of the proposed scheme are improved. View Full-Text
Keywords: minimum mean square error (MMSE); multi user multiple-input multiple-output (MU-MIMO); block diagonalization (BD) minimum mean square error (MMSE); multi user multiple-input multiple-output (MU-MIMO); block diagonalization (BD)
Show Figures

Figure 1

MDPI and ACS Style

Lee, W.-S.; Ro, J.-H.; You, Y.-H.; Hwang, D.; Song, H.-K. An Enhanced Precoder for Multi User Multiple-Input Multiple-Output Downlink Systems. Appl. Sci. 2020, 10, 4547. https://doi.org/10.3390/app10134547

AMA Style

Lee W-S, Ro J-H, You Y-H, Hwang D, Song H-K. An Enhanced Precoder for Multi User Multiple-Input Multiple-Output Downlink Systems. Applied Sciences. 2020; 10(13):4547. https://doi.org/10.3390/app10134547

Chicago/Turabian Style

Lee, Woon-Sang; Ro, Jae-Hyun; You, Young-Hwan; Hwang, Duckdong; Song, Hyoung-Kyu. 2020. "An Enhanced Precoder for Multi User Multiple-Input Multiple-Output Downlink Systems" Appl. Sci. 10, no. 13: 4547. https://doi.org/10.3390/app10134547

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop