Please use this identifier to cite or link to this item:
http://bura.brunel.ac.uk/handle/2438/31520
Title: | QoS-Aware Precoding for Dual-Polarized Downlink Massive MIMO LEO Satellite Communications |
Authors: | Huang, Y You, L Wang, K Gao, X |
Issue Date: | 6-Nov-2024 |
Publisher: | American Association for the Advancement of Science (AAAS) |
Citation: | Huang, Y. et al. (2024) 'QoS-Aware Precoding for Dual-Polarized Downlink Massive MIMO LEO Satellite Communications', Space Science and Technology United States, 4, 0178, pp. 1 - 10. doi: 10.34133/space.0178. |
Abstract: | Low Earth Orbit (LEO) satellite communications (SATCOM) are important for wireless networks and offer better global wireless access services than higher altitude SATCOM options. SATCOM performance is affected by the number of antennas, which is usually constrained by the satellite space. In this paper, the application of dual-polarized technology is considered to assist LEO SATCOM. Compared with single-polarized antennas, dual-polarized antennas utilize two different polarization orientations to transmit and receive data. This can improve the quality of service (QoS) performance, as it allows for twice the amount of data to be transmitted over the same time–frequency resources. Specifically, we characterize the dual-polarized channel in massive multiple-input multiple-output (MIMO) LEO SATCOM and investigate the precoding design for enhancing the system performance. In particular, a precoding optimization problem is formulated, which aims to jointly optimize the system throughput and the QoS performance. We divide the problem into two stages and develop novel algorithms for each stage to obtain the precoding vectors. The numerical results demonstrate that the dual-polarized technology can improve the system throughput, and the proposed algorithm leads to a higher percentage of users achieving their QoS requirements compared to conventional approaches. |
Description: | Data Availability: All data needed to evaluate the conclusions of the study are presented in the paper. |
URI: | https://bura.brunel.ac.uk/handle/2438/31520 |
DOI: | https://doi.org/10.34133/space.0178 |
Other Identifiers: | ORCiD: Li You https://orcid.org/0000-0001-8600-1423 ORCiD: Kezhi Wang https://orcid.org/0000-0001-8602-0800 Article number: 0178 |
Appears in Collections: | Dept of Computer Science Research Papers |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
FullText.pdf | Copyright © 2024 Yan Huang et al. Exclusive licensee Beijing Institute of Technology Press. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY 4.0). | 2.68 MB | Adobe PDF | View/Open |
This item is licensed under a Creative Commons License